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ACTAUNIVERSITATIS
UPSALIENSISUPPSALA
2015
Digital Comprehensive Summaries of Uppsala Dissertationsfrom the Faculty of Medicine 1129
Prevalence and Prognostic Impactof Periodontal Disease andConventional Risk Factors inPatients with Stable CoronaryHeart Disease
OLA VEDIN
ISSN 1651-6206ISBN 978-91-554-9308-0urn:nbn:se:uu:diva-260564
Dissertation presented at Uppsala University to be publicly examined in Konferensvinge,Gustavianum, Akademigatan 3, Uppsala, Friday, 9 October 2015 at 13:00 for the degree ofDoctor of Philosophy. The examination will be conducted in Swedish. Faculty examiner: Mai-Lis Hellenius (Institutionen för Medicin, Karolinska Institutet).
AbstractVedin, O. 2015. Prevalence and Prognostic Impact of Periodontal Disease and ConventionalRisk Factors in Patients with Stable Coronary Heart Disease. Digital ComprehensiveSummaries of Uppsala Dissertations from the Faculty of Medicine 1129. 77 pp. Uppsala: ActaUniversitatis Upsaliensis. ISBN 978-91-554-9308-0.
The purpose of this thesis was to assess the prevalence and management of establishedcardiovascular (CV) risk factors and the prevalence and influence of self-reported markers(number of teeth and frequency of gum bleeding) of periodontal disease (PD), a less exploredCV risk factor, in patients with stable chronic coronary heart disease (CHD).
We studied patients from the global STabilization of Atherosclerotic plaque By Initiation ofdarapLadIb TherapY (STABILITY) trial (n=15,828), in which patients with stable chronic CHDwere randomized to either darapladib or placebo. Our studies were performed using descriptivestatistics and multivariable linear, logistic and Cox regression models.
The use of secondary preventive medications was generally high across the whole studypopulation. Despite this, CV risk factors were highly prevalent, including obesity, hypertensionand hypercholesterolemia. Achievement of guideline-recommended treatment targets waslacking and little improvement was seen throughout the study duration.
Approximately 40% of patients reported having <15 remaining teeth and 25% reported gumbleeding. More tooth loss was associated with a greater CV risk factor burden after adjustment,while the associations for gum bleeding were less evident.
After multivariable adjustment for CV risk factors and socioeconomic status, more tooth losswas associated with an increased risk of major adverse CV events (a composite of CV death,myocardial infarction and stroke), CV mortality, all-cause mortality and fatal or non-fatal stroke.
We found associations between a higher degree of tooth loss and elevated levels of severalprognostic biomarkers known to reflect various pathophysiological mechanisms involved inCV morbidity and mortality. Most biomarkers had little attenuating effect on the relationshipbetween tooth loss and outcomes in a multivariable model.
In conclusion, we found an inadequate CV risk factor control despite a high use of evidence-based pharmacological therapies, likely to explain some of the excess risk in CHD patients.Further, we demonstrated a high prevalence of PD markers, tooth loss in particular, thatwere associated with a wide range of established CV risk factors, prognostic biomarkers andoutcomes. Collectively, these findings indicate that tooth loss may be a significant risk factoramong patients with stable chronic CHD.
Keywords: Coronary heart disease, Secondary prevention, Prevention, Periodontal Disease,Tooth loss, Risk prediction, Risk factors, Myocardial infarction
Ola Vedin, Department of Medical Sciences, Akademiska sjukhuset, Uppsala University,SE-75185 Uppsala, Sweden.
© Ola Vedin 2015
ISSN 1651-6206ISBN 978-91-554-9308-0urn:nbn:se:uu:diva-260564 (http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-260564)
“To have his path made clear for him is the aspiration of every human being in our beclouded and tempestuous existence.”
Joseph Conrad To my wife and children
List of Papers
This thesis is based on the following papers, which are referred to in the text by their Roman numerals.
I Vedin O, Hagström E, Stewart R, Brown R, Krug-Gourley S, Davies R,
Wallentin L, White H, Held C. (2013) Secondary prevention and risk factor target achievement in a global, high-risk population with established coronary heart disease: baseline results from the STABILITY study. Eur J Prev Cardiol, 20(4):678–85.
II Vedin O, Hagström E, Gallup D, Neely ML, Stewart R, Koenig W, Bu-
daj A, Sritara P, Wallentin L, White HD, Held C. (2015) Periodontal disease in patients with chronic coronary heart disease: Prevalence and association with cardiovascular risk factors. Eur J Prev Cardiol, 22(6):771-8.
III Vedin O, Hagström E, Budaj A, Denchev S, Harrington RA, Koenig W,
Soffer J, Sritara P, Stebbins A, Stewart R, Swart HP, Viigimaa M, Vinereanu D, Wallentin L, White HD, Held C. Tooth loss is inde-pendently associated with poor outcomes in stable coronary heart dis-ease. Submitted.
IV Vedin O, Hagström E, Koenig W, Stewart R, White HD, Wallentin L,
Östlund O, Held C. Associations between tooth loss and prognostic bi-omarkers and cardiovascular events in patients with coronary heart dis-ease. Manuscript.
Reprints were made with permission from the respective publishers.
Contents
Introduction ................................................................................................... 11
Background ................................................................................................... 12 Coronary heart disease – pathophysiology ............................................... 12 Coronary heart disease – prevalence and prognosis ................................. 12 Established modifiable risk factors ........................................................... 13 Pharmacological treatment in secondary prevention ................................ 15 Previous assessments of secondary prevention ........................................ 16 Potential novel risk factors ....................................................................... 17 Periodontal disease – pathophysiology and etiology ................................ 17 Periodontal disease – diagnosis and prevalence ....................................... 18 Evidence linking periodontal disease to coronary heart disease .............. 19 Hypotheses on association ........................................................................ 21
Main hypothesis ............................................................................................ 22
Aims .............................................................................................................. 23
Methods ......................................................................................................... 24 The STABILITY trial ............................................................................... 24 Study population ....................................................................................... 24 Data collection .......................................................................................... 25 Study outcomes ......................................................................................... 26 Statistical methods .................................................................................... 27
Results ........................................................................................................... 29 Paper I – Secondary prevention in a global coronary heart disease population ................................................................................................. 29 Paper II – Prevalence of periodontal disease markers and associations with cardiovascular risk factors ................................................................ 33 Paper III – Associations between tooth loss and outcomes ...................... 38 Paper IV – Associations between tooth loss and biomarkers ................... 43
Discussion ..................................................................................................... 48 Main findings ............................................................................................ 48 An appraisal of contemporary secondary coronary heart disease prevention (Paper I) .................................................................................. 49
Periodontal disease – significance of a potential risk factor for coronary heart disease (Papers II-IV) ...................................................................... 51 Limitations ................................................................................................ 59 General conclusion and future perspectives ............................................. 60
Acknowledgments ......................................................................................... 61
References ..................................................................................................... 63
Abbreviations
ACE Angiotensin Converting Enzyme BMI Body Mass Index BP Blood Pressure CABG Coronary Artery Bypass Grafting CHD Coronary Heart Disease CI Confidence Interval CRP C-Reactive Protein CV Cardiovascular eGFR Estimated Glomerular Filtration Rate EUROASPIRE European Action on Secondary Prevention
through Intervention to Reduce Events GDF-15 Growth Differentiation Factor 15 HDL High-Density Lipoprotein HS High-Sensitivity IL-6 Interleukin 6 L Litre LDL Low-Density Lipoprotein Lp-PLA2 Lipoprotein-Associated Phospholipase A2 MDRD Modification of Diet in Renal Disease Formula MI Myocardial Infarction NCD Non-Communicable Diseases NT-proBNP N-Terminal pro B-type Natriuretic Peptide PCI Percutaneous Coronary Intervention PD Periodontal Disease REACH Reduction of Atherothrombosis for Continued
Health SANZA South Africa, New Zealand and Australia STABILITY STabilization of Atherosclerotic plaque By
Initiation of darapLadIb TherapY US United States WBCC White Blood Cell Count WHO World Health Organization
11
Introduction
In recognition of the extensive problem of coronary heart disease (CHD) and other major non-communicable diseases (NCD), the United Nations passed a declaration during the high-level meeting in September 2011 committing countries to take political action to reduce the burden of disease.1 The World Health Organization (WHO) and other important organizations have fol-lowed suit, concluding that a large part of CHD and other NCDs are pre-ventable by adopting low-cost preventive strategies at a global and national widespread level, aimed at a few common and modifiable risk factors.2-4 The proposed interventions are a result of decades of CHD research; knowledge which has been integrated in international guidelines and which has im-proved prognosis considerably.5-7 However, despite these advances mortality remains high,8 especially among individuals with manifest CHD who require intensive prevention measures.7 To further improve the prognosis for these patients, we need to advance our knowledge about all aspects of the disease, including assessments of established therapies and by exploring novel areas of prevention.
Similar to CHD, periodontal disease (PD) is a chronic affliction affecting millions of individuals worldwide.9 During the WHO World Congress in 2015, the Tokyo Declaration was adopted, acknowledging the growing prob-lem of oral disease and “calling upon health policy-makers and professionals to significantly reduce the global disease burden, promote greater equity, and integrate oral health promotion into the NCD prevention and control and development agenda.”10 In recent years, an escalating interest for oral health and PD as potential risk factors for cardiovascular (CV) disease has emerged. However, epidemiological and mechanistic evidence is limited, particularly in certain populations, and causality has yet to be established.11 As the health care implications of a possible causative association would be immense in view of the considerable prevalence of PD and given the fact that it is treatable, further scientific efforts exploring this link should be made.
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Background
Coronary heart disease – pathophysiology CHD evolves as a result of complex interactions between genetic factors and metabolic effects on cellular and molecular mechanisms.8 The formation of the atherosclerotic plaque in the coronary artery begins in early age as a fatty streak, a relatively benign manifestation resulting from low-density lipopro-tein (LDL) cholesterol infiltrating the vessel wall where it may be retained. The cholesterol subsequently undergoes enzymatic modification and oxidi-zation, giving rise to various phospholipids and oxidized LDL particles. The latter are partially absorbed by macrophages, which are subsequently trans-formed to foam cells, an important component of the atherosclerotic plaque. The by-products of the LDL modification process further serve as activators of the endothelium, leading to recruitment of inflammatory cells to the core of the plaque. They also induce proliferation of smooth muscle cells, which form a cap covering the plaque.12,13 This so-called stable plaque may grow to partially obstruct the coronary artery, thereby reducing the supply of oxygen and nutrients to the myocardium, which in instances of increased demand leads to myocardial ischemia and angina pectoris.5 However, the stable plaques are rarely the cause of an acute coronary syndrome, i.e. myocardial infarction (MI) or unstable angina, which is more likely to occur as a result of a ruptured unstable plaque.12,14 Plaque instability is promoted by degrada-tion of the fibrous cap by proteolytic enzymes and through the continued recruitment of inflammatory cells. This ultimately renders the plaque prone to rupture, which exposes prothrombotic substances to the bloodstream where they constitute substrate for coagulation activation and platelet aggre-gation. This can lead to the formation of a thrombus, which can partially or completely impede the blood flow and cause ischemia and necrosis of the myocardium.8
Coronary heart disease – prevalence and prognosis According to the WHO, MI causes more than 7 million deaths per year and an estimated 54 million people worldwide are suffering from chronic CHD with angina pectoris.15,16 Within the European Union, 700,000 deaths are attributed to CHD annually17 and in the United States 16.3 million adults are
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believed to have chronic CHD, corresponding to 7% of the adult popula-tion.18 Despite rising mortality rates in parts of the world, age-related mortal-ity is decreasing, especially in many developed countries.15,19 However, the combination of improved survival and a growing and ageing population is resulting in a steady rise in CHD prevalence, which constitutes a major and increasing source of disability and financial burden on society.15,20–24
The decline in age-related mortality has been attributed to improved treat-ment of established CHD (e.g. revascularization, secondary preventive ther-apies) and risk factor control (e.g. smoking cessation strategies, increasing physical activity, improving cholesterol and blood pressure levels), in rough-ly equal measure.23,25 Despite these advances, however, patients with CHD remain at significantly higher risk of recurring MI and death compared to the general population.26,27 Data from the REduction of Atherothrombosis for Continued Health (REACH) registry showed that event rates among patients with established CHD were nearly twice that of individuals without CHD but with multiple CV risk factors.28 Moreover, although the immediate con-sequences of the acute coronary syndrome have been ameliorated by new invasive and pharmacological treatment strategies,29–31 such measures do not address or diminish atherosclerosis progression against which attention to co-morbidity and lifestyle-related etiological factors is crucial.
Established modifiable risk factors A number of groundbreaking studies, including the Framingham and INTERHEART study, have identified a number of CV risk factors that joint-ly explain a large part of the overall risk of MI. The majority are either in-fluenced by or are a direct consequence of behaviour and include smoking, hypercholesterolemia, hypertension, diabetes mellitus, obesity, unhealthy diet, physical inactivity, and low socioeconomic status.32–35 In addition to the recognized combined importance of these risk factors, there is an abundance of evidence of their individual significance and of the beneficial effects that result from their modification.
Smoking The harmful effects and prognostic implications of smoking have been pre-viously well documented.36 Furthermore, smoking cessation appears to have consistent beneficial effects among all patients with a previous MI, produc-ing an estimated 36% risk reduction for all-cause mortality in one study and thus constituting one of the most effective preventive interventions.37
14
Hypercholesterolemia Elevated cholesterol levels and LDL cholesterol in particular are closely linked to the development of atherosclerosis and have been independently linked to CV outcomes.38 Reduction of LDL cholesterol levels has been shown to improve the outcome of CHD patients,39 with a seemingly linear beneficial association to levels as low as 1.8 mmol/L,40,41 perhaps even in low-risk patients.42
Hypertension According to the INTERHEART study, hypertension constitutes a major determinant of the overall risk of MI.35 CHD patients with a blood pressure less than 140/90 mmHg during the majority of their outpatient clinic visits had a lower risk of CV events compared to those with less rigid control.43 However, there have been indications of a non-linear, possibly J-shaped relationship, suggesting that an overly aggressive blood pressure-lowering strategy may be imprudent in CHD patients. Therefore current practice guidelines do not recommend a systolic blood pressure treatment target be-low 130 mmHg in this patient category.44
Diabetes mellitus The detrimental effects of diabetes mellitus on CHD progression have been demonstrated in large epidemiological studies and recent meta-analyses.32,35,45,46 Patients with a previous MI and diabetes have a poorer prognosis compared to non-diabetics.47 There is presently no consensus on how to optimally treat diabetic patients with respect to glycaemic control in relation to CV outcomes. Conversely to the ostensibly safe and effective “the lower you go the better”-strategy for the treatment of hypercholesterol-emia, some studies of intensive glucose lowering therapy in diabetic patients have demonstrated unfavourable effects on mortality.48 However, a recent study with long-term follow-up has put some of the concerns to rest, show-ing a reduction of CV events in patients allocated to intensive glucose-lowering therapy, but no mortality effects, neither positive nor negative.49
Obesity Obesity has been associated with all-cause mortality and several established CV risk factors and its high prevalence has been described as a modern global epidemic.50,51 Although considered an established risk factor for the development of CHD, its role in patients with chronic CHD and the effects of weight reduction on CV outcome appear somewhat conflicting.52 Some studies even demonstrate an “obesity paradox”, suggesting that increased
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body weight could have a protective effect with a reduced risk of CV events in patients with established CHD.53,54 However, current guidelines recom-mend weight reduction in all patients as a means to achieve favourable ef-fects on other CV risk factors.7
Physical activity Physical activity is an integral part of weight reduction but more importantly physical inactivity and a sedentary lifestyle are closely linked to an elevated risk of CV mortality, irrespective of body weight.55 Further, physical activity and exercise-based rehabilitation initiatives for patients with established CHD have documented favourable effects on prognosis, with high-risk indi-viduals benefitting the most.56,57
Diet Dietary patterns have been studied extensively, and observed differences in CV mortality between Northern and Southern Europe has led to the belief that a so-called Mediterranean diet (including vegetables, fruits, unsaturated fatty acids, fish, wholegrain, nuts, and a low intake of red meats) may be beneficial in patients with CHD.34 This has since been supported by findings from other studies58 and now constitutes a part of guideline recommenda-tions.7
Socioeconomic status There are numerous ways of measuring the socioeconomic status of an indi-vidual, for example by income or education level. While the former appears to correlate with CV outcome mainly through associations with other CV risk factors, the latter has predicted CV outcome independent of other risk factors and can therefore be considered an important and useful marker.59
Pharmacological treatment in secondary prevention CHD risk can be modified not only by lifestyle-related measures but also with pharmacotherapy. Some drugs do not only exert their influence through positive effects on CV risk factors but are specifically directed at various pathophysiological aspects of CHD. Platelet inhibition, most commonly in the form of aspirin, has become mandatory in all patients with established CHD unless contraindicated due to demonstrated risk reductions for recur-rent CV events and death.60 Statins are well documented effective lipid-lowering agents with possible beneficial pleiotropic effects and should be prescribed to all patients with established CHD.40 Randomized studies
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demonstrating favourable effects of beta-blockers in patients with CHD were performed in an era prior to widespread treatment with statins and ACE-inhibitors but their use is still recommended, especially in patients with prior MI.61,62 Finally, several studies have shown that ACE-inhibitors lower the risk of recurrent events and death in patients with established CHD and their use in this patient group have become increasingly prevalent in later years.63
Previous assessments of secondary prevention Several reports on the prevalence of risk factors and medication use from various secondary prevention populations have demonstrated substantial differences between developing and developed countries, rural and urban areas, and even between countries within the same geographic region.64–71 The cross-sectional EUROASPIRE (European Action on Secondary and Primary Prevention by Intervention to Reduce Events) reports64–67 have eval-uated similar European populations at different points in time, showing a temporal improvement in the use of medications. Disappointingly, risk fac-tor control (e.g. smoking rates and obesity prevalence) and achievement of guideline-recommended treatment targets did not improve correspondingly. In fact, the prevalence of obesity and diabetes was higher in EUROASPIRE III72 (published in 2009) compared to EUROASPIRE I64 (published in 1997) while smoking rates and attainment of blood pressure goals remained essen-tially unchanged. The only substantial improvement was seen for total cho-lesterol for which 57% reached a target <4.5 mmol/L in EUROASPIRE III compared to 8% in EUROASPIRE I, most likely a result of a progressive adaptation to current evidence. Data from the recently published EU-ROASPIRE IV67 showed a similar pattern when compared to EUROASPIRE III, i.e. an increased use of cardioprotective medications but little improve-ment seen in terms of risk factor control.
Other noteworthy assessments of secondary prevention include the REACH registry68, which represents a larger and more geographically diverse popula-tion than EUROASPIRE. Although medication use and attainment of treat-ment goals was somewhat poorer overall in REACH, the general pattern was similar. In conclusion, the results from these reports demonstrate the value of continued evaluation of secondary prevention efficacy, and signal a dire need for improved lifestyle modification among CHD populations.
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Potential novel risk factors Although much of the risk for CHD can be attributed to genetic susceptibil-ity and traditional CV risk factors,35 an important part remains unaccounted for. It could possibly be explained by novel, or hitherto unrecognized fac-tors. If significantly prevalent, such potential risk factors could be important on a population level even if the risk increase they incur is small. According-ly, efforts toward the discovery, assessment and treatment of such risk fac-tors are crucial in the continued strive to prevent and diminish the impact of CHD. Moreover, it is possible that the likelihood of finding evidence for less explored risk factors is greater in populations with established CHD, who represent a phenotype with a demonstrated vulnerability to etiological fac-tors.
In recent decades, several possible novel determinants of CHD have been explored, including components of the lipid metabolism, markers of in-flammation, various microbes, and physiological conditions.11,73–78 Nonethe-less, while seeming independently associated with CHD, they have not nec-essarily been deemed sufficiently relevant,79 nor have they always proven to be viable treatment targets.80–84 PD is one of these emerging risk factors, which has received increasing attention in recent years. However, the evi-dence in favour of a link between PD and CHD has not been deemed suffi-cient to support causality; nor has the association been adequately explored in certain populations and possible pathophysiological mechanisms connect-ing the two conditions remain uncertain.85,86
Periodontal disease – pathophysiology and etiology PD is a chronic condition that can span several decades. It is initiated by the formation of a bacterial biofilm consisting of gram-negative and anaerobic pathogens adjacent to the tooth and gingiva. This bacterial plaque triggers a local host-mediated response consisting of immune cells, cytokines, eico-sanoids and matrix metalloproteinases. The ensuing inflammation initially affects the gums alone, known as gingivitis. It is an early, acute and reversi-ble form of PD but if not addressed adequately by means of dental care, it may progress to a more permanent destruction of the dental support tissue. Deepening pockets between the tooth and gingiva will eventually form, fol-lowed by destruction of alveolar bone and loss of teeth as the final and ir-revocable outcome.87,88
The host-mediated response triggered by the presence of the bacterial plaque constitutes the most important prerequisite for the initiation of PD.87 Howev-er, the susceptibility and progression of disease are also influenced by nu-
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merous other factors, several of which are shared with CHD. Genetic factors could possibly explain a large part of the between-person variation in PD prevalence. Several gene polymorphisms associated with PD have been sug-gested but the overall knowledge about the interplay between genetics and PD warrants further elucidation.89 The age association with PD is well known but there are also important modifiable risk factors, including smok-ing and diabetes mellitus. Smoking is the strongest risk factor and has been demonstrated to increase the risk of PD between 2-14 times across different age groups.89 Diabetes mellitus, particularly if poorly controlled, is also a significant risk factor for PD and recent evidence point to the possibility of a bidirectional relationship, i.e. that PD could aggravate the diabetic condi-tion.90 Other CV risk factors, including socioeconomic status, obesity and nutrition have also been suggested to play a part in PD etiology but their specific roles are less clear.88,89
Periodontal disease – diagnosis and prevalence In a dental health care setting, the diagnosis of PD is principally based on clinical and/or radiographic examination. Due to the wide range of manifes-tations of the disease, the diagnosis depends on multiple disease measures including pocket depth, tissue support, dental plaque, dental calculus and gingival bleeding on probing, to name a few.87 In an epidemiological setting, however, comprehensive clinical examinations are both impractical and expensive and surrogates may be useful, for instance self-reported markers. Two examples thereof used in this thesis include self-reported gum bleeding and tooth loss, markers of early reversible PD and chronic end-stage PD, respectively.
The heterogeneous use of PD definitions is a likely cause of some of the disparities between PD prevalence estimates. However, a substantial varia-tion is also evident between countries, regions and socioeconomic catego-ries, with PD generally more prevalent in developing countries and under-privileged groups.87,91 Gingivitis, by some estimates, affects as many as 50-90% of adults worldwide.87 In the US, approximately half of the adult popu-lation have gingival bleeding,89 a sign of gingivitis, and 30-50% are believed to suffer from periodontitis.88,89 According to the WHO, the prevalence of edentulism among patients in Europe aged 65 years and above ranges be-tween 15-78% depending on country, and severe PD that can result in tooth loss affects 5-15% of most populations.92 While many of these prevalence estimates appear high already, they are often based on limited dental exami-nations which could actually underestimate the true prevalence as they may not detect all stages of disease.87
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Evidence linking periodontal disease to coronary heart disease Although a relationship between oral health and systemic disease has been suspected for at least a century,93 it is only in the past 25 years that the scien-tific community has taken a marked interest in the association between PD and CHD.94 During that time, numerous publications have addressed the purported association by assessing various measures of PD in relation to different aspects of CHD.
Periodontal disease and functional and morphological markers of coronary heart disease Both carotid intima media thickness and endothelial dysfunction have been associated with adverse CV outcomes and can be used as markers of sub-clinical atherosclerosis.95,96 Three studies demonstrated a relation between intima media thickness and different measures of PD, including levels of systemic antibodies against periodontal pathogens,97 subgingival bacterial load,98 and clinical examination criteria.99 A Swedish study using number of teeth as marker of PD found an association with atherosclerotic plaque bur-den in the carotid arteries but not with intima media thickness.100 Varying degrees of endothelial dysfunction has been demonstrated in PD patients compared to healthy controls in several studies.101–103 Interestingly, these differences were only evident when an endothelium-dependent method was used, indicating that PD could have selective detrimental effects on the en-dothelium, possibly through negative effects on nitric oxide production.102
Periodontal disease and cardiovascular biomarkers Several biomarkers with prognostic capabilities independent of traditional CV risk factors have emerged in recent years. Many of these, including C-reactive protein (CRP), interleukin-6 (IL-6), lipoprotein-associated phospho-lipase A2 (Lp-PLA2), growth differentiation factor 15 (GDF-15), high-sensitivity troponin T (hs-Troponin T), and N-terminal pro B-type natriuretic peptide (NT-proBNP) also reflect different pathophysiological mechanisms that have been related to various aspects of CHD.77,78,104–107 Evidence of their associations with PD could therefore further the knowledge about possible pathophysiological connections between PD and CHD. However, such pre-vious observations are mainly limited to CRP and IL-6 and come from small studies with limited adjustment, but show modest associations possibly sup-porting the hypothesis of an inflammatory link between the two condi-tions.108,109
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Observational studies of periodontal disease and coronary heart disease The assumption of an independent link between PD and CHD is primarily based on observational studies with considerable heterogeneity regarding PD exposure measures, sample size, adjustment for confounding factors, and outcome verification. Most are also geographically limited and important populations, such as patients with established CHD, are underrepresented.86
Notwithstanding, evidence in favour of a positive association include cross-sectional,110–117 case-control,94,118–125 and cohort studies126–137 using either clini-cal examinations or self-report questionnaires as their source of PD diagno-sis. Some studies have demonstrated partly positive findings, for instance among older age groups and not in younger,138–141 or only for some PD expo-sure measures but not others.142–148 In contrast, several moderate to large size studies, most of them prospective cohort studies, did not observe any associ-ation between different measures of PD and CHD outcomes.149–156 Despite this, at least four meta-analyses based on studies of varying methodology found a modest association between PD and CHD with odds ratios (cross-sectional and case-cohort studies) and relative risks (cohort studies) ranging between 1.59-2.35 and 1.14-1.44, respectively.157–160 In addition to the geo-graphical limitations mentioned above – all studies were performed in single centres or single countries – only four studies evaluated the PD-CHD asso-ciation in patients with established CHD. Of these only one study of 214 patients found a positive relationship;137 another demonstrated an association in never-smokers but not ever-smokers;130 and two studies found no evidence of PD elevating the risk of recurring events in CHD patients.149,152
Periodontal disease intervention and coronary heart disease Intervention studies have a vital role in the assessment of causality but no randomized trials have been performed in the context of PD and CHD, as they require large sample sizes, long term follow-up and pose ethical chal-lenges.161 However, there are studies that have assessed the effect of PD treatment on surrogate markers of CHD and CV biomarkers. For instance, a few studies have reported improved endothelial function and reduced carotid intima media thickness after periodontal therapy.102,162,163 One of these com-pared intensive periodontal therapy to community-based dental care and observed an initial deterioration of endothelial function 24 hours after inten-sive therapy, only to demonstrate a subsequent improvement after 6 months compared to the group receiving community-based care.162 Studies evaluat-ing the effect of periodontal therapy on biomarker levels are relatively small and mainly include CRP and IL-6. Nonetheless, some of them have demon-strated moderate reductions in the levels of these biomarkers following
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treatment.108,164,165 Finally, a small pilot study attempting to elucidate the in-fluence of PD treatment on CV outcomes could not detect a significant dif-ference in adverse events or outcomes in less than three hundred patients that were randomized to either intensive periodontal treatment or communi-ty-based care over the study duration of approximately two years.166
Hypotheses on association The identification of plausible pathogenic mechanisms between PD and CHD is another critical step when establishing causality. There are numer-ous existing theories, of which some propose localized actions of periodon-tal pathogens in the coronary arteries, based on findings of bacterial compo-nents and DNA in atherosclerotic plaques. A more widespread belief em-phasizes the host-mediated response to periodontal pathogens as an im-portant prerequisite for systemic inflammation with subsequent detrimental effects on CHD development, although the specific characteristics of these steps are unclear.167 In fact, multiple studies, mostly in-vitro, have suggested effects on various aspects of the atherosclerotic process.168 One hypothesized mechanism is endothelial dysfunction resulting from invasion of the endo-thelium by periodontal pathogens inducing apoptosis. Other evidence has demonstrated activation of the endothelium by periodontal bacteria, leading to increased adhesion and recruitment of immune cells into the vascular wall, promoting foam cell formation. There are also numerous other pro-posed mechanisms supported by various degrees of evidence by which PD could affect different aspects of CHD, including LDL oxidation, vascular cell proliferation, platelet aggregation, chemokine and cytokine release, and fibrous cap degradation.168
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Main hypothesis
CHD is a globally widespread condition conferring a high risk of mortality. As new medications and other therapeutic improvements have become available, long-term prognosis has improved but mortality remains high, especially among patients with established disease. Reasons for this may include continued impact by traditional CV risk factors despite secondary preventive measures. There may also be an influence from less explored risk factors, the study of which may be particularly advantageous in populations with established CHD as they have an already demonstrated vulnerability to etiological factors. We hypothesized that there is a widespread lack of risk factor control among chronic CHD patients despite a frequent use of cardio-protective medications, which could possibly explain part of their excess mortality. We further hypothesized that markers of periodontal disease, a less explored risk factor for CHD, may be highly prevalent in this large global population and could contribute to an adverse prognosis through a wide association with CV risk, including risk factors, prognostic biomarkers, and outcomes.
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Aims
I: To describe the prevalence of CV risk factors, use of preventive medica-tions, and guideline-recommended risk factor target achievement in a large global population with chronic CHD. II: To assess the influence of PD in a global chronic CHD population by:
a. Describing the prevalence of self-reported gum bleeding and tooth loss – indicators of PD – and their association with socioeconomic and CV risk factors. b. Investigating whether self-reported tooth loss is independently as-sociated with CV outcomes. c. Investigating associations between self-reported tooth loss and prognostic biomarkers known to reflect various pathophysiological mechanisms linked to CV disease, and to investigate the influence of these biomarkers on the association between tooth loss and clinical outcomes.
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Methods
The STABILITY trial The STABILITY trial (STabilization of Atherosclerotic plaque By Initiation of darapLadIb TherapY) was a randomized, prospective, placebo-controlled, double blind, multi-centre trial designed to determine the efficacy of dara-pladib, a reversible and highly selective oral inhibitor of Lp-PLA2, versus placebo in chronic CHD patients. All participants provided written informed consent, and the relevant ethics committee of each participating country approved the study. A detailed account of the STABILITY study design has been previously published.169 At the end of study, after a median follow-up of 3.7 years, no significant differences were seen between the darapladib and placebo arms with respect to the primary endpoint, a composite of CV death, non-fatal MI or non-fatal stroke.80
Study population A total of 15,828 patients from 39 countries worldwide were recruited for participation in the STABILITY study. Details on participating countries by region are provided in Table 1. All patients had chronic CHD, defined as prior MI (>1 month prior to randomization), prior coronary revascularization (percutaneous coronary intervention or coronary artery bypass grafting) or multi-vessel CHD without revascularization. In addition, at least one of the following risk enrichment criteria were required: age ≥60 years, diabetes mellitus requiring pharmacotherapy, high-density lipoprotein (HDL) choles-terol <1.03 mmol/L, current or previous smoker defined as ≥5 cigarettes per day on average, significant renal dysfunction (estimated glomerular filtration rate [eGFR] ≥30 and <60 mL/min per 1.73 m2 or urine albumin:creatinine ratio ≥30 mg albumin/g creatinine), or polyvascular disease (CHD and cere-brovascular disease or CHD and peripheral arterial disease). Exclusion crite-ria included planned revascularization (either percutaneous coronary inter-vention or coronary artery bypass grafting) or another major surgical proce-dure, current liver disease, severe renal impairment (eGFR <30 mL/min per 1.73 m2), a history of nephrectomy or kidney transplantation, current New York Heart Association class III or IV heart failure, or severe asthma that was poorly controlled with standard medical therapy.
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Table 1. Region definitions and population distribution. Region (n; % of total population)
Countries (n; % of total population)
US/Canada (3882; 25%) United States (3102; 20%); Canada (780; 5%)
Eastern Europe (3531; 22%)
Bulgaria (222; 1%); Czech Republic (774; 5%); Estonia (77; <1%); Hungary (410; 3%); Poland (510; 3%); Roma-nia (411; 3%); Russian Federation (654; 4%); Slovakia (120; <1%); Ukraine (353; 2%)
Western Europe (3599; 23%)
Belgium (202; 1%); Denmark (102; <1%); France (250; 2%); Germany (1089; 7%); Greece (187; 1%); Italy (256; 2%); Netherlands (444; 3%); Norway (113; <1%); Spain (474; 3%); Sweden (299; 2%); United Kingdom (183; 1%)
Latin America (1340; 8%) Argentina (542; 3%); Brazil (384; 2%); Chile (195; 1%); Mexico (141; <1%); Peru (78; <1%)
Asia (2581; 16%)
China (369; 2%); India (398; 3%); Japan (318; 2%); Hong Kong (117; <1%); Korea (503; 3%); Pakistan (250; 2%); Philippines (219; 1%); Taiwan (200; 1%); Thailand (207; 1%)
SANZA (895; 6%) South Africa (387; 2%); New Zealand (202; 1%); Austral-ia (306; 2%)
Data collection Medical examination and biochemical analyses A medical history including concurrent medical conditions, current pharma-cotherapy and smoking status was obtained at baseline. A complete physical exam, using local instruments, was performed including measurements of weight, height, waist circumference, lung and heart status, abdominal exam and peripheral vascular exam. Blood pressure was calculated as the mean of three measurements performed in a sitting position in the same arm from visit to visit with a digital sphygmomanometer.
Blood samples for routine laboratory tests and storage for later analyses were obtained in all patients at baseline. eGFR was calculated according to the MDRD formula.170 Prognostic biomarker analyses were performed in the majority of patients, except for IL-6, which was analyzed in 4,642 patients. Plasma aliquots were stored at -70oC until biochemical analysis. All routine biochemical and hs-CRP analyses were performed at a central laboratory with standardized methods (Quest Diagnostics Clinical Laboratories, Inc., Valencia, California, USA). CRP was analyzed using the high sensitivity CardioPhase® hsCRP (Dade Behring, Deerfield, USA) two-site particle enhanced immunonephelometry sandwich assay. Lp-PLA2 activity was measured in an automated enzyme assay system (PLAC® Test for Lp-PLA2
Activity, diaDexus, San Francisco, CA, USA. The other biomarker assays were performed at the UCR Laboratory at Uppsala University, Uppsala,
26
Sweden. GDF-15 was measured with the GDF-15 precommercial assay (Roche Diagnostics, Penzberg, Germany), composed of a monoclonal mouse antibody for capture and a monoclonal mouse antibody fragment, [F(ab´)2], for detection in a sandwich assay format. Detection was based on an electro-chemiluminiscence immunoassay using a ruthenium (II) complex label. The levels of hs-troponin T and NT-proBNP were determined by an electro-chemiluminescence immunoassay (Roche Diagnostics, Penzberg, Germany). The Cobas Analytics e601 was used for the ROCHE immunoassays.
Lifestyle questionnaire The majority of study participants completed a baseline lifestyle question-naire, including questions on physical activity, diet, mood, stress, alcohol consumption, education, and dental health. Questions and possible responses relevant to this thesis are shown in Table 2.
Table 2. Questions and responses from the STABILITY lifestyle questionnaire. Question Response categories How active are you during your leisure time?
Mainly sedentary, mild exercise, moderate exercise, strenuous exercise
During a typical week, how much of the following alcoholic drinks do you have: Beers and other low alcohol drinks? (1 drink = 350 ml) Red wine? (1 drink = 150 ml) White wine? (1 drink = 150 ml) Spirits or liquor? (1 drink = 45 ml)
None, 1-4 drinks, 5-14 drinks, ≥15 drinks
How often have you experienced financial stress over the last year? Never, sometimes, often, always
How often have you experienced stress at home over the last year? Never, sometimes, often, always
How often have you experienced stress at work over the last year?
Never, sometimes, often, always, do not work
How many teeth do you have in your mouth? No teeth, 1-14, 15-19, 20-25, 26-32 (All)
How often do your gums bleed when brushing your teeth or at other times? Never/rarely, sometimes, often, always
Study outcomes The primary outcome was a composite of CV death, non-fatal MI or non-fatal stroke, collectively termed major adverse cardiovascular events (MACE). Secondary outcomes were non-fatal or fatal MI, non-fatal or fatal stroke, CV death, and all-cause mortality. Components of CV death included death from unknown cause, fatal MI, fatal stroke, complications of a cardiac procedure, arrhythmia, congestive heart failure/shock, other vascular cause
27
of death, and sudden death. All suspected endpoints were documented and reported by STABILITY study investigators and were adjudicated by an independent clinical events committee.80
Statistical methods All papers included in the thesis presented selected baseline characteristics for the study population based on relevance. In paper I, the characteristics of the STABILITY population (n=15,828) with particular focus on traditional CV risk factors were described. In paper II, baseline characteristics included self-reported number of teeth (n=15,533, 98.1%) and frequency of gum bleeding (n=15,512, 98.0%) presented by region and country. Due to the low proportion of patients responding ‘Often’ (3%) or ‘Always’ (1%) and for the purpose of the statistical analysis, the gum bleeding category was dichoto-mized into two categories: ‘Never/rarely’ and ‘Sometimes/Often/Always’. Papers III and IV presented baseline characteristics by tooth loss level and no data related to gum bleeding were included. The baseline parameters for all papers were summarized through descriptive statistics, including means, medians, standard deviations, percentiles and interquartile ranges for contin-uous variables and frequency and percentages for categorical variables.
The intent of paper I was entirely descriptive in nature, therefore no hypoth-esis testing was performed.
In paper II, assessment of associations between self-reported tooth loss and gum bleeding and CV risk factors was performed using linear and logistic regression models for continuous and categorical variables, respectively. Each CV risk factor was assessed as a function of number of teeth and gum bleeding, separately. The regression model was adjusted for age, smoking, diabetes mellitus, and education. For continuous variables, the model esti-mated the average unit change for each variable when moving from a higher (fewer teeth) to a lower (more teeth) tooth loss level and from any versus no gum bleeding. For categorical variables, the model calculated odds ratios of having a higher versus a lower value of a risk factor or having versus not having a risk factor when moving from a higher to a lower tooth loss level, and from any versus no gum bleeding. Importantly, the analysis in papers II-III assumes that the spacing between tooth loss levels is equal, i.e. that mov-ing from 1-14 teeth to 15-19 teeth has the same effect as moving from 20-25 teeth to 26-32 teeth.
In paper III, Cox proportional hazards models were used to determine asso-ciations between tooth loss levels and clinical outcomes. Both the assump-tion of linearity and proportional hazards was tested. Three models were
28
used adjusting for an increasing number of pre-specified baseline factors. Model 1 adjusted for randomized treatment alone. Model 2 adjusted for Model 1, age, systolic blood pressure, diastolic blood pressure, body mass index (BMI), LDL cholesterol, HDL cholesterol, history of diabetes melli-tus, prior MI, gender, smoking status, and waist-hip ratio. Model 3 adjusted for all factors in Model 2 with the addition of eGFR, family history of CHD, alcohol consumption, years of education, level of physical activity, and World Bank country income level (lower middle, upper middle, or high). Cumulative event rates over time were estimated using the Kaplan-Meier method.
In paper IV, each biomarker was modelled as a function of tooth loss level (five levels). All biomarkers were analysed on a log-transformed scale using linear models. Geometric mean ratios are presented with 95% confidence intervals (CI) with the lowest tooth loss level (26-32 teeth) as reference, and according to three adjustment models. Model 1 adjusted for randomized treatment. Model 2 adjusted for Model 1 and prior MI, prior coronary revas-cularization, multi-vessel CHD, age, gender, geographic region, diabetes mellitus, hypertension, significant renal dysfunction, body mass index, smoking (current, former or never), systolic blood pressure and polyvascular disease. Model 3 adjusted for Model 2 and eGFR (replacing significant renal dysfunction), hemoglobin, white blood cells, LDL cholesterol, HDL choles-terol and triglycerides. As an additional explorative analysis, Cox propor-tional hazards models were used to calculate hazard ratios for MACE and CV death in relation to tooth loss after adding adjustment for biomarkers to the multivariable model from paper III. In these models, all biomarkers ex-cept Lp-PLA2 activity were added after log-transformation.
A p-value <0.05 was considered statistically significant in all analyses.
29
Results
Paper I – Secondary prevention in a global coronary heart disease population Paper I described the prevalence of risk factors, use of secondary preventive medications and achievement of guideline-recommended6,171 risk factor goals. At the time, recommendations included a blood pressure <140/90 mmHg and <130/80 mmHg in patients with renal insufficiency or diabetes mellitus, total cholesterol <4.5 mmol/L, and LDL cholesterol <2.5 mmol/L. Overweight was defined as a BMI ≥25 kg/m2, obesity as a BMI ≥30 kg/m2, and central obesity as a waist circumference ≥102 cm in men and ≥88 cm in women. The study population consisted of 19% women and the mean age was 64.4 years. In 74% of the patients, more than one year had elapsed since the diagnosis of CHD. Baseline pharmacological treatment by geographic region is listed in Table 3.
Table 3. Reported pharmacological treatment at baseline by region. Region (n)
Anti-platelets, % (n)
β-blockers, % (n)
ACE-i/ARB, % (n)
Statins, % (n)
All subjects (15828)
96% (15165)
79% (12505)
77% (12196)
97% (15399)
US/Canada (3882)
96% (3715)
77% (3002)
73% (2853)
95% (3697)
Eastern Europe (3531)
95% (3371)
90% (3161)
87% (3087)
99% (3500)
Western Europe (3599)
94% (3377)
80% (2894)
77% (2774)
98% (3510)
Latin America (1340)
98% (1311)
78% (1047)
78% (1040)
98% (1316)
Asia (2581)
98% (2524)
71% (1821)
69% (1774)
97% (2503)
SANZA (895)
97% (867)
65% (580)
75% (668)
98% (873)
SANZA, South Africa/New Zealand/Australia; ACE-i, angiotensin converting enzyme inhibi-tor; ARB, angiotensin receptor blockers
A total of 79% of the population were overweight and 36% were obese, with considerable regional differences (Figure 1). The Asian region had a signifi-
30
cantly lower proportion of overweight and obese individuals compared to the other regions. More than half of all participants met the definition for central obesity.
Figure 1. Prevalence of overweight, obesity and central obesity.
Figure 2 lists the prevalence of several traditional CV risk factors. Of all participants, 38% had diabetes mellitus requiring pharmacotherapy. Among patients who did not have a history of diabetes, a fasting plasma glucose !7 mmol/L at baseline was observed in 5%. Elevated LDL cholesterol was found in 29% of the population but with substantial interregional variation and 33% had elevated total cholesterol. Elevated blood pressure was ob-served in 46% of patients but when applying a target of !130/80 mmHg to all patients, the proportion rose to 65%. Patients with diabetes or chronic kidney disease generally had poorer blood pressure control than patients without these conditions. Of all patients, 96% were on a blood pressure-lowering medication. The prevalence of current smoking at baseline was 18% for all with a somewhat greater proportion of smokers among men (19% of men vs. 14% of women). In Asia, there were few female smokers overall (2% of women vs. 21% of men).
"#! $"#! %"#! &"#! '"#! (""#!
)*+,-+./01!2#3!
)4+5.16!2#3!
7+81,9:!;4+5.16!2#3!
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D951+,8!D=,;E+!
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G9H8!<I+,.?9!
<5.9!
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31
Figure 2. Prevalence of current smoking, elevated blood pressure, elevated LDL cholesterol and diabetes mellitus.
Table 4 shows quantitative risk factors by region. Of patients with diabetes, 44% met the HbA1c target of <7% (IFCC HbA1c: 53 mmol/mol) with lower proportions in Latin America and South Africa/New Zealand/Australia (SANZA).
32
Tabl
e 4.
Qua
ntita
tive
risk
fact
ors b
y re
gion
.
Reg
ion
Bod
y m
ass
inde
x (k
g/m
2 , m
ean,
SD
)
Wai
st
circ
umfe
r-en
ce (c
m,
mea
n, S
D)
Syst
olic
BP
(mm
Hg,
m
ean,
SD
)
Dia
stol
ic
BP
(mm
Hg,
m
ean,
SD
)
Tot
al
chol
es-
tero
l (m
mol
/l,
mea
n, S
D)
LD
L c
ho-
lest
erol
(m
mol
/l,
mea
n, S
D)
HD
L
chol
es-
tero
l (m
mol
/l,
med
ian)
Fast
ing
plas
ma
gluc
ose
(mm
ol/L
, mea
n, S
D)
No
diab
etes
D
iabe
tes
All
subj
ects
29
.0 (5
.1)
101.
3 (1
3.2)
13
1.5
(16.
6)
78.7
(10.
4)
4.22
(1.1
) 2.
20 (0
.85)
1.
15
5.64
(0.9
1)
8.21
(3.1
2)
US/
Can
ada
31.0
(6.0
) 10
5.8
(14.
3)
129.
7 (1
6.6)
76
.9 (1
0.1)
3.
94 (1
.0)
1.92
(0.7
5)
1.15
5.
67 (0
.77)
7.
96 (3
.06)
Ea
ster
n Eu
rope
29
.4 (4
.5)
102.
0 (1
2.2)
13
2.3
(15.
2)
81.1
(9.5
) 4.
56 (1
.1)
2.51
(0.9
4)
1.19
5.
75 (0
.89)
8.
64 (3
.28)
Wes
tern
Eu
rope
29
.0 (4
.5)
103.
1 (1
2.0)
13
3.5
(16.
6)
79.7
(10.
1)
4.30
(0.9
) 2.
26 (0
.75)
1.
18
5.71
(0.9
1)
8.33
(2.8
0)
Latin
A
mer
ica
28.6
(4.3
) 10
0.4
(11.
2)
131.
6 (1
7.7)
76
.2 (1
1.0)
4.
33 (1
.1)
2.27
(0.9
0)
1.15
5.
70 (0
.99)
9.
15 (3
.90)
Asi
a 25
.2 (3
.5)
91.6
(9.9
) 12
8.7
(16.
8)
77.2
(10.
9)
4.03
(1.0
) 2.
06 (0
.82)
1.
15
5.34
(0.9
5)
7.44
(2.7
1)
SAN
ZA
29.4
(5.0
) 10
1.8
(13.
7)
136.
2 (1
7.0)
81
.0 (1
0.1)
4.
24 (1
.0)
2.25
(0.8
7)
1.14
5.
60 (1
.07)
8.
45 (3
.23)
33
Paper II – Prevalence of periodontal disease markers and associations with cardiovascular risk factors
Prevalence of tooth loss and gum bleeding Baseline characteristics are displayed in Table 5, showing a high overall prevalence of tooth loss: 16.4% reported having no teeth and 40.9% reported having less than 15 remaining teeth. Approximately one quarter of the pa-tients reported any frequency of gum bleeding.
Table 5. Baseline characteristics Characteristic Value Age (years) 65.0 (59, 71) Gender Female Male
N= 15828 2967 (18.7%) 12861 (81.3%)
Number of remaining teeth No teeth 1-14 15-20 21-25 26-32 (All)
N= 15533 2551 (16.4%) 3803 (24.5%) 2174 (14.0%) 3689 (23.2%) 3316 (21.3%)
Gum bleeding Never/Rarely Sometimes/Often/Always
N= 15512 11548 (74.4%) 3964 (25.6%)
Smoking status N= 15826 Never 4892 (30.9%) Former 8079 (51.0%) Current 2855 (18.0%) Education None/1-8 years
N= 15511 3566 (23.0%)
9-12 years 4750 (30.6%) Trade school 2831 (18.3%) College/university 4364 (28.1%) Ethnicity White Asian Other
N= 15828 12412 (78.4%) 2717 (17.2%) 699 (4.4%)
Diabetes1 N= 15828 No 9762 (61.7%) Yes 6066 (38.3%) Alcohol consumption (drinks/week) N= 15412 0 7243 (47.0%) 1-4 3747 (24.3%) 5-14 3370 (21.9%) ≥ 15 1052 (6.8%)
34
Characteristic Value Work stress N= 15455 Do not work/rarely/never 10737 (69.5%) Sometimes 3026 (19.6%) Often/Always 1692 (10.9%) Home stress N= 15146 Never/Rarely 6378 (42.1%) Sometimes 6964 (46.0%) Often/Always 1804 (11.9%) Financial stress N= 15117 Never/Rarely 7683 (50.8%) Sometimes 4935 (32.6%) Often/Always 2499 (16.5%) Leisure time physical activity N= 15170 Mainly sedentary 4929 (32.5%) Mild exercise 6701 (44.2%) Moderate/Strenuous exercise 3540 (23.3%) LDL cholesterol (mmol/L) 2.1 (2, 3) Systolic blood pressure (mmHg) 131.0 (120, 142) Waist circumference (cm) 100.5 (93, 109) Fasting p-glucose (mmol/L) 5.9 (5, 7) Estimated glomerular filtration rate (mL/min/1.73m2) 77.8 (65.9, 89.8)
White blood cell count (109/L) 6.6 (6, 8) High sensitivity C-reactive protein (mg/L) 1.3 (1, 3)
Data are median (25th, 75th) for continuous variables and n (%) for categorical variables. 1 Type 1 or type 2 diabetes with or without treatment
There were marked differences between geographic regions, particularly for prevalence of number of teeth, as demonstrated in Figure 3. Compared with tooth loss, the extent of gum bleeding in the population appeared less pro-nounced. Tooth loss was less prevalent in the Asian ethnic group compared to the White and Other ethnic groups.
35
Figure 3. Prevalence of tooth loss (<15 remaining teeth) and gum bleeding (some-times/often/always) by geographic region and ethnicity.
Table 6 lists all participating countries and the proportion of patients in each country with less than 15 teeth and any frequency of gum bleeding, demon-strating substantial variation in prevalence between countries, even within the same geographic region.
Table 6. Proportion of patients with evidence of periodontal disease by country
Country Region N participants (% of total)
% with < 15 teeth
% with gum bleeding
All Countries 15,533 (100%) 40.9% 25.6% Slovakia Eastern Europe 118 (0.8%) 68.6% 17.8% Poland Eastern Europe 490 (3.2%) 66.7% 28.5% South Africa SANZA 383 (2.5%) 62.7% 12.8% Hungary Eastern Europe 396 (2.5%) 62.4% 36.8% Czech Republic Eastern Europe 767 (4.9%) 60.4% 35.3% Brazil Latin America 376 (2.4%) 60.1% 13.6% Netherlands Western Europe 444 (2.9%) 59.2% 16.2% Chile Latin America 194 (1.2%) 54.1% 26.8% Argentina Latin America 537 (3.5%) 53.8% 16.2% Estonia Eastern Europe 77 (0.5%) 51.9% 44.2% Romania Eastern Europe 408 (2.6%) 49.8% 47.9% Italy Western Europe 196 (1.3%) 48.0% 25.0% Belgium Western Europe 202 (1.3%) 46.5% 19.9% Germany Western Europe 1,063 (6.8%) 46.4% 22.8% Bulgaria Eastern Europe 219 (1.4%) 46.1% 38.1% Philippines Asia 214 (1.4%) 45.3% 21.3% Canada USA/Canada 777 (5.0%) 45.0% 19.6% New Zealand SANZA 201 (1.3%) 43.3% 19.8% Japan Asia 316 (2.0%) 41.8% 30.2% Hong Kong Asia 116 (0.7%) 40.5% 36.8% Spain Western Europe 435 (2.8%) 40.5% 35.3%
36
Country Region N participants (% of total)
% with < 15 teeth
% with gum bleeding
United Kingdom Western Europe 183 (1.2%) 39.9% 21.3% Greece Western Europe 187 (1.2%) 38.5% 22.5% Peru Latin America 78 (0.5%) 37.2% 25.6% Russian Federa-tion Eastern Europe 652 (4.2%) 37.1% 42.5%
Ukraine Eastern Europe 352 (2.3%) 34.7% 46.9% Taiwan Asia 197 (1.3%) 32.5% 38.7% Mexico Latin America 137 (0.9%) 31.4% 31.9% United States USA/Canada 3,067 (19.7%) 31.4% 18.7% Australia SANZA 301 (1.9%) 30.6% 24.4% France Western Europe 236 (1.5%) 29.2% 34.4% Thailand Asia 206 (1.3%) 28.2% 24.8% Denmark Western Europe 100 (0.6%) 28.0% 23.2% South Korea Asia 502 (3.2%) 24.5% 19.0% Sweden Western Europe 296 (1.9%) 19.3% 28.0% Pakistan Asia 230 (1.5%) 18.3% 21.9% China Asia 369 (2.4%) 16.3% 31.3% Norway Western Europe 113 (0.7%) 14.2% 34.5% India Asia 398 (2.6%) 11.3% 15.6%
Tooth loss, risk factors and biomarkers Table 7 reports adjusted associations between tooth loss and CV risk factors, listing the estimated average change in the level of each risk factor and bi-omarker for every move from a higher to a lower tooth loss level; for in-stance when moving from ‘No teeth’ to ‘1-14 teeth’. Lower tooth loss levels were associated with lower levels of all continuous risk factors, except eGFR. Figure 4 shows that tooth loss was associated with all categorical risk factors, except physical activity. Lower tooth loss levels were associated with decreased odds of diabetes mellitus, smoking, home and financial stress, but with increased odds of higher education level, work stress, and more frequent alcohol consumption.
Gum bleeding, risk factors and biomarkers Table 7 shows the estimated average change of each continuous risk factor and biomarker for participants with gum bleeding versus those without. Compared to tooth loss, gum bleeding was not as strongly associated with the continuous risk factors, nevertheless demonstrating positive associations with LDL cholesterol and systolic blood pressure. Figure 5 shows that gum bleeding was associated with all categorical risk factors, with the exception of diabetes mellitus and physical activity. Gum bleeding was associated with decreased odds of smoking but increased odds of having a higher education, stress, and more frequent alcohol consumption.
37
Table 7. Association between tooth loss, gum bleeding and continuous CV risk fac-tors
Tooth loss Gum bleeding
Estimate (99.76% CI)1 p-value Estimate (99.76% CI)1 p-value
Fasting p-glucose (mmol/L)2 -0.03 (-0.04, -0.02) < 0.0001 0.01 (-0.01, 0.03) 1.000
eGFR (mL/min/1.73m2) 0.48 (0.18, 0.79) < 0.0001 0.28 (-0.67, 1.2) 1.000
LDL cholesterol (mmol/L) -0.03 (-0.04, -0.02) < 0.0001 0.04 (0.01, 0.07) 0.0003
Systolic blood pressure (mmHg) -0.41 (-0.71, -0.1) 0.0010 1.28 (0.36, 2.2) 0.0005
WBCC (109/L) -0.02 (-0.02, -0.01) < 0.0001 -0.01 (-0.03, 0.01) 1.000
Waist circumfer-ence (cm) -0.51 (-0.75, -0.27) < 0.0001 0.14 (-0.59, 0.88) 1.000
hs-CRP (mg/L) -0.14 (-0.17, -0.1) < 0.0001 0.01 (-0.09, 0.11) 1.000 1 Adjusted for age, smoking, diabetes and education level. 2 Adjusted for age, smoking and education level.
Figure 4. Association between tooth loss and categorical CV risk factors. All ORs are adjusted for age, smoking status, educational level and diabetes mellitus, except for diabetes mellitus (adjusted for age, smoking status, and education), smoking (adjusted for age, diabetes mellitus, and education) and education (adjusted for age, smoking, and diabetes mellitus). [1] Cumulative logit displays odds of vs. lower value of variable.
38
Figure 5. Association between gum bleeding and categorical CV risk factors. All ORs are adjusted for age, smoking status, educational level and diabetes mellitus, except for diabetes mellitus (adjusted for age, smoking status, and education), smok-ing (adjusted for age, diabetes mellitus, and education) and education (adjusted for age, smoking, and diabetes mellitus). [1] Cumulative logit displays odds of vs. lower value of variable.
Paper III – Associations between tooth loss and outcomes The median follow-up time was 3.7 years. Baseline characteristics are given in Table 8. There were no differences observed between the two treatment groups for any outcome, irrespective of tooth loss level. The relationship between gum bleeding and outcomes was also assessed, but not presented in paper III for reasons discussed elsewhere. Nevertheless, gum bleeding was not associated with any of the outcomes in the analysis. For all outcomes, risk factor associations observed after adjustment for randomized treatment were attenuated after adjustment for CV risk factors and socioeconomic sta-tus (Table 9). This attenuation was largely an effect of adjustment for the traditional CV risk factors in Model 2, with little additional impact of varia-bles added in Model 3.
MACE During follow-up, there were 1543 patients suffering from MACE. After adjusting for CV risk factors and socioeconomic status, there was a 6% in-creased risk of MACE associated with every increase in level of tooth loss (Table 9). Patients in the highest tooth loss level (no teeth) had a 27% higher risk of MACE vs. the lowest (26–32 teeth) after adjustment in Model 3 (Ta-
39
ble 10). A continuous separation of event curves throughout follow-up was observed, as pictured in Figure 6a.
Cardiovascular death and all-cause death CV and all-cause death occurred in 705 and 1120 patients, respectively. For every increase in tooth loss level a gradually increased risk of CV death (17% in Model 3) and all-cause death (16% in Model 3) was observed (Ta-ble 9). In comparison to the lowest tooth loss level, the highest level entailed an 85% and 81% increased risk of CV and all-cause death, respectively, after adjustment in Model 3 (Table 10). The event curves across tooth loss catego-ries for CV death showed a consistent separation, with the two lowest levels having similar event rates (Figures 6b and 6c).
MI There were a total of 746 patients with fatal or non-fatal MI. There was a 7% increased risk of MI for every increase in tooth loss level; however, after adjustment, no statistically significant association remained (Table 9).
Stroke Fatal or non-fatal stroke occurred in 301 patients. Every increase in tooth loss level was associated with a 14% (Model 3) increased risk of stroke (Ta-ble 9). Individuals in the highest tooth loss level had a 67% higher risk of stroke compared to those in the lowest level, in the fully adjusted model (Table 10). Estimates of event curves by tooth loss category showed a con-tinuous separation of curves that continued throughout follow-up (Figure 6d).
40
Tabl
e 8.
Bas
elin
e ch
arac
teris
tics b
y to
oth
loss
leve
l
T
ooth
Los
s Lev
el
Low
est
H
ighe
st
Cha
ract
eris
tics
All
Patie
nts
(n=1
5456
) 26
-32
Tee
th
(n=3
310)
20
-25
Tee
th
(n=3
680)
15
-19
Tee
th
(n=2
167)
1-
14 T
eeth
(n
=378
5)
No
Tee
th
(n=2
514)
A
ge, y
ears
64
.4 +
/- 9.
3 61
.1 +
/- 10
.0
63.2
+/-
9.2
64.5
+/-
9.0
65.8
+/-
8.5
68.2
+/-
8.0
Gen
der
Fem
ale
2882
(18.
6)
455
(13.
7)
555
(15.
1)
431
(19.
9)
816
(21.
6)
625
(24.
9)
Mal
e 12
574
(81.
4)
2855
(86.
3)
3125
(84.
9)
1736
(80.
1)
2969
(78.
4)
1889
(75.
1)
Smok
ing
stat
us
Nev
er sm
oked
47
55 (3
0.8)
12
88 (3
8.9)
12
12 (3
2.9)
65
0 (3
0.0)
10
30 (2
7.2)
57
5 (2
2.9)
F
orm
er sm
oker
79
18 (5
1.2)
15
30 (4
6.2)
18
59 (5
0.5)
10
92 (5
0.4)
20
14 (5
3.2)
14
23 (5
6.6)
C
urre
nt sm
oker
27
82 (1
8.0)
49
2 (1
4.9)
60
9 (1
6.5)
42
5 (1
9.6)
74
1 (1
9.6)
51
5 (2
0.5)
D
iabe
tes
5991
(38.
8)
1173
(35.
4)
1378
(37.
4)
794
(36.
6)
1565
(41.
3)
1081
(43.
0)
Chr
onic
kid
ney
dise
ase
4668
(30.
2)
791
(23.
9)
1004
(27.
3)
681
(31.
4)
1237
(32.
7)
955
(38.
0)
Prio
r MI
9101
(58.
9)
1829
(55.
3)
2137
(58.
1)
1299
(59.
9)
2361
(62.
4)
1475
(58.
7)
Prio
r rev
ascu
lariz
atio
n 11
582
(74.
9)
2547
(76.
9)
2757
(72.
8)
1593
(73.
5)
2783
(75.
6)
1902
(75.
7)
Educ
atio
n
N
one
551
(3.6
) 11
6 (3
.5)
97 (2
.6)
66 (3
.1)
142
(3.8
) 13
0 (5
.2)
1-8
yea
rs
2956
(19.
2)
484
(14.
7)
566
(15.
5)
363
(16.
8)
866
(23.
1)
677
(27.
1)
9-1
2 ye
ars
4713
(30.
7)
858
(26.
1)
1064
(29.
0)
701
(32.
5)
1231
(32.
8)
859
(34.
4)
Tra
de sc
hool
27
97 (1
8.2)
47
8 (1
4.5)
65
3 (1
7.8)
42
4 (1
9.7)
77
8 (2
0.7)
46
4 (1
8.6)
C
olle
ge/u
nive
rsity
43
48 (2
8.3)
13
56 (4
1.2)
12
83 (3
5.0)
60
2 (2
7.9)
73
9 (1
9.7)
36
8 (1
4.7)
A
lcoh
ol c
onsu
mpt
ion
per w
eek
Non
e 71
38 (5
4.8)
15
15 (5
3.6)
15
29 (5
0.1)
94
2 (5
1.8)
18
19 (5
7.1)
13
33 (6
2.1)
1
-4 d
rinks
24
68 (1
8.9)
54
1 (1
9.1)
61
9 (2
0.3)
36
7 (2
0.2)
58
9 (1
8.5)
35
2 (1
6.4)
5
-14
drin
ks
2063
(15.
8)
461
(16.
3)
551
(18.
0)
298
(16.
4)
476
(14.
9)
277
(12.
9)
≥15
drin
ks
1364
(10.
5)
310
(11.
0)
354
(11.
6)
213
(11.
7)
301
(9.5
) 18
6 (8
.7)
41
T
ooth
Los
s Lev
el
Low
est
H
ighe
st
Cha
ract
eris
tics
All
Patie
nts
(n=1
5456
) 26
-32
Tee
th
(n=3
310)
20
-25
Tee
th
(n=3
680)
15
-19
Tee
th
(n=2
167)
1-
14 T
eeth
(n
=378
5)
No
Tee
th
(n=2
514)
Le
isur
e tim
e ph
ysic
al a
ctiv
ity
Sed
enta
ry
4891
(32.
8)
1072
(33.
3)
1066
(30.
0)
635
(30.
4)
1271
(35.
1)
847
(35.
0)
Mild
exe
rcis
e 66
43 (4
4.6)
14
32 (4
4.4)
16
04 (4
5.1)
95
0 (4
5.5)
15
57 (4
3.0)
11
00 (4
5.4)
M
oder
ate
exer
cise
33
75 (2
2.6)
71
9 (2
2.3)
88
8 (2
5.0)
50
2 (2
4.1)
79
0 (2
1.8)
47
6 (1
9.6)
LD
L ch
oles
tero
l, m
mol
/L
2.2
± 0.
9 2.
1 ±
0.8
2.2
± 0.
8 2.
2 ±
0.8
2.3
± 0.
9 2.
2 ±
0.8
HD
L ch
oles
tero
l, m
mol
/L
1.2
± 0.
3 1.
2 ±
0.3
1.2
± 0.
3 1.
2 ±
0.3
1.2
± 0.
3 1.
2 ±
0.3
eGFR
, mL/
min
/1.7
3m2
75
.8 ±
18.
1 78
.7 ±
17.
8 77
.2 ±
17.
8 75
.3 ±
18.
1 74
.5 ±
18.
2 72
.3 ±
18.
0 Sy
stol
ic B
P, m
mH
g
131.
5 ±
16.6
12
8.8
± 16
.0
131.
3 ±
16.1
13
1.6
± 17
.0
132.
6 ±
16.4
13
3.4
± 17
.3
Dia
stol
ic B
P, m
mH
g
78.7
± 1
0.4
78.4
± 1
0.2
78.7
± 1
0.3
78.8
± 1
0.4
79.2
± 1
0.3
78.2
± 1
0.6
BM
I, kg
/m2
28
.9 ±
5.0
28
.5 ±
5.0
29
.1 ±
5.1
28
.9 ±
5.0
29
.0 ±
4.8
29
.3 ±
5.2
D
ata
are
n (%
) and
mea
n ±
SD
Tabl
e 9.
Haz
ard
ratio
s for e
very
incr
ease
in to
oth
loss
leve
l (“2
6-32
” [L
owes
t lev
el] t
o ‘N
o te
eth’
[Hig
hest
leve
l])
Out
com
e N
† M
odel
1
p-va
lue
Mod
el 2
p-
valu
e M
odel
3
p-va
lue
MA
CE
15
43
1.16
(1.1
2, 1
.20)
<0
.001
1.
08 (1
.04,
1.1
2)
<0.0
01
1.06
(1.0
2, 1
.10)
0
.004
C
V d
eath
70
5 1.
30 (1
.23,
1.3
7)
<0.0
01
1.18
(1.1
2, 1
.25)
<0
.001
1.
17 (1
.10,
1.2
4)
<0.0
01
MI
746
1.07
(1.0
2, 1
.13)
0
.008
1.
01 (0
.95,
1.0
6)
0.8
49
0.99
(0.9
4, 1
.05)
0
.822
St
roke
30
1 1.
22 (1
.13,
1.3
3)
<0.0
01
1.13
(1.0
4, 1
.24)
0
.005
1.
14 (1
.04,
1.2
4)
0.0
07
All-
caus
e de
ath
11
20
1.30
(1.2
5, 1
.36)
<0
.001
1.
17 (1
.12,
1.2
3)
<0.0
01
1.16
(1.1
1, 1
.22)
<0
.001
Mod
el 1
is a
djus
ted
for s
tudy
trea
tmen
t onl
y. M
odel
2: M
odel
1 a
nd a
ge, s
ysto
lic b
lood
pre
ssur
e, d
iast
olic
blo
od p
ress
ure,
BM
I, LD
L ch
oles
tero
l,
HD
L ch
oles
tero
l, hi
stor
y of
dia
bete
s, pr
ior M
I, ge
nder
, sm
okin
g st
atus
and
wai
st h
ip ra
tio. M
odel
3: M
odel
2 a
nd e
GFR
, fam
ily h
isto
ry o
f CH
D,
alco
hol c
onsu
mpt
ion,
yea
rs o
f edu
catio
n, le
vel o
f phy
sica
l act
ivity
and
cou
ntry
inco
me
leve
l. † N
umbe
r of p
atie
nts w
ith a
n ev
ent i
n M
odel
1.
42
Table 10. Accumulated hazard ratios for each tooth loss level relative to “26-32 teeth” (Lowest level)
Tooth Loss Level
Lowest Highest
Outcome 26-32 HR
20-25 HR (95% CI)
15-19 HR (95% CI)
1-14 HR (95% CI)
No Teeth HR (95% CI)
MACE 1 1.06 (1.02, 1.10) 1.13 (1.04, 1.22) 1.19 (1.06, 1.35) 1.27 (1.08, 1.49) CV death 1 1.17 (1.10, 1.24) 1.36 (1.21, 1.54) 1.59 (1.32, 1.91) 1.85 (1.45, 2.37) MI 1 0.99 (0.94, 1.05) 0.99 (0.88, 1.11) 0.98 (0.82, 1.17) 0.97 (0.77, 1.23) Stroke 1 1.14 (1.04, 1.24) 1.29 91.07, 1.55) 1.46 (1.11, 1.92) 1.67 (1.15, 2.39) All-cause death 1 1.16 (1.11, 1.22) 1.35 (1.22, 1.48) 1.56 (1.35, 1.80) 1.81 (1.50, 2.20)
Estimates are accumulated hazard ratios (HR, 95% CI) adjusted according to Model 3. a) b)
c) d)
Figure 6. Cumulative incidence by tooth loss level for: a) MACE (CV death, MI, or stroke); b) CV death; c) all-cause death; and d) stroke from 0-1400 days from ran-domization, stratified by tooth loss level (lowest to highest).
43
Paper IV – Associations between tooth loss and biomarkers
Baseline characteristics and associations with biomarkers Standard baseline characteristics have been previously presented in Table 8 and biomarker levels by tooth loss level are presented in Table 11. Patients with a higher tooth loss level had progressively higher baseline levels of the inflammatory biomarkers hs-CRP, IL-6 and Lp-PLA2 activity. Similar pat-terns of increasing biomarker levels with more tooth loss were also evident for the cardiac biomarkers hs-Troponin T and NT-proBNP, as well as for GDF-15. As demonstrated in Table 12, a higher tooth loss level entailed progressively greater relative increases for all prognostic biomarkers in rela-tion to the lowest tooth less level, according to Model 1. After multivariable adjustment in Model 2 and 3 the association remained for all biomarkers, except hs-Troponin T.
Associations between tooth loss and cardiovascular outcomes Table 13 demonstrates the association between one increase in tooth loss level and the risk of MACE and CV death as presented in paper III with the subsequent addition of prognostic biomarkers to the previously fully adjust-ed model as a means to assess the independent predictive ability of tooth loss further. In Model 3, which included adjustment for a wide range of CV risk factors, socioeconomic status and routine laboratory variables, every in-crease in tooth loss level entailed a relative risk increase to 1.06 and 1.17 for MACE and CV death, respectively. This result was only slightly attenuated by the addition of most biomarkers, except NT-proBNP, which eliminated the association with MACE. Despite adjustment for all biomarkers, the asso-ciation between tooth loss and CV death remained.
44
Tabl
e 11
. Bas
elin
e bi
omar
ker l
evel
s by
toot
h lo
ss le
vel
T
ooth
Los
s Lev
el
L
owes
t
Hig
hest
Bio
mar
ker
All
Patie
nts
(n=1
5456
) 26
-32
Tee
th
(n=3
310)
20
-25
Tee
th
(n=3
680)
15
-19
Tee
th
(n=2
167)
1-
14 T
eeth
(n
=378
5)
No
Tee
th
(n=2
514)
p-
valu
e
hs-C
RP,
mg/
L
n
Med
ian
(Q1;
Q3)
1407
6 1.
3 (0
.6; 3
.1)
2977
1.
1 (0
.5; 2
.6)
3389
1.
3 (0
.6; 2
.8)
1972
1.
4 (0
.7; 3
.0)
3467
1.
5 (0
.7; 3
.3)
2271
1.
7 (0
.8; 4
.0)
< 0.
0001
IL-6
, pg/
mL
n
M
edia
n (Q
1; Q
3)
4642
1.
8 (1
.2; 2
.9)
996
1.6
(1.1
; 2.5
)
1130
1.
8 (1
.2; 2
.7)
654
1.8
(1.2
; 2.8
)
1154
1.
9 (1
.3; 3
.0)
708
2.1
(1.4
; 3.4
)
< 0.
0001
Lp-
PLA
2, µm
ol/m
in/L
n
M
edia
n (Q
1; Q
3)
1415
5 17
3 (1
43; 2
04)
2960
17
1 (1
40; 2
03)
3366
17
2 (1
43; 2
02)
1984
17
2 (1
43; 2
04)
3520
17
3 (1
44; 2
06)
2325
17
6 (1
48; 2
07)
< 0.
0001
GD
F-15
, pg/
mL
n
M
edia
n (Q
1; Q
3)
hs-T
ropo
nin
T, n
g/L
n
M
edia
n (Q
1; Q
3)
1423
7 12
54 (9
15;1
827)
14
147
9.3
(6.2
; 14.
2)
2974
11
20 (8
24; 1
615)
29
52
8.5
(5.7
; 12.
7)
3385
11
81 (8
76; 1
709)
33
86
8.7
(6.0
; 13.
3)
2011
12
25 (9
07; 1
792)
19
96
9.4
(6.2
; 14.
3)
3528
13
14 (9
62; 1
888)
34
97
9.8
(6.4
; 14.
8)
2339
14
86 (1
069;
217
2)
2316
10
.4 (6
.9; 1
6.2)
< 0.
0001
<
0.00
01
NT
-pro
BN
P, n
g/L
n
M
edia
n (Q
1; Q
3)
1418
1 17
3 (8
3; 3
77)
2960
13
2 (6
4; 2
78)
3392
15
2 (7
2; 3
28)
2003
17
7 (8
8; 3
92)
3505
20
2 (9
7; 4
50)
2321
22
4 (1
08; 4
93)
< 0.
0001
45
Tabl
e 12
. Cha
nge
in b
iom
arke
r lev
els r
elat
ive
to th
e lo
wes
t too
th lo
ss le
vel (
26-3
2 te
eth)
by
step
wis
e ad
just
men
t
Bio
mar
ker
and
toot
h lo
ss le
vel
Mod
el 1
(Rel
ativ
e In
crea
se
[95%
CI]
) p-
valu
e M
odel
2
(Rel
ativ
e In
crea
se
[95%
CI]
) p-
valu
e M
odel
3
(Rel
ativ
e In
crea
se
[95%
CI]
) p-
valu
e
hs-C
RP
26-3
2
20-2
5 15
-19
1-14
N
o te
eth
IL-6
26
-32
20
-25
15-1
9 1-
14
No
teet
h L
p-PL
A2
26-3
2
20-2
5 15
-19
1-14
N
o te
eth
GD
F-15
26
-32
20
-25
15-1
9
1.00
1.
11 (1
.05;
1.1
7)
1.25
(1.1
7; 1
.33)
1.
31 (1
.24;
1.3
9)
1.55
(1.4
5; 1
.65)
1.
00
1.12
(1.0
6; 1
.18)
1.
12 (1
.05;
1.1
9)
1.21
(1.1
5; 1
.28)
1.
35 (1
.27;
1.4
4)
1.00
1.
01 (1
.00;
1.0
3)
1.02
(1.0
0; 1
.04)
1.
02 (1
.01;
1.0
4)
1.05
(1.0
3; 1
.06)
1.
00
1.06
(1.0
3; 1
.09)
1.
10 (1
.07;
1.1
3)
< 0.
0001
<
0.00
01
< 0.
0001
<
0.00
01
1.00
1.
01 (0
.96;
1.0
7)
1.10
(1.0
3; 1
.17)
1.
12 (1
.06;
1.1
9)
1.28
(1.2
0; 1
.36)
1.
00
1.05
(1.0
0; 1
.11)
1.
03 (0
.97;
1.1
0)
1.09
(1.0
3; 1
.16)
1.
18 (1
.10;
1.2
5)
1.00
1.
01 (1
.00;
1.0
3)
1.02
(1.0
0; 1
.04)
1.
03 (1
.02;
1.0
5)
1.06
(1.0
4; 1
.08)
1.
00
1.02
(1.0
0; 1
.04)
1.
04 (1
.01;
1.0
6)
< 0.
0001
<
0.00
01
< 0.
0001
<
0.00
01
1.00
1.
01 (0
.96;
1.0
7)
1.08
(1.0
2; 1
.15)
1.
08 (1
.02;
1.1
4)
1.22
(1.1
4; 1
.29)
1.
00
1.06
(1.0
0; 1
.11)
1.
06 (0
.99;
1.2
3)
1.09
(1.0
3; 1
.15)
1.
15 (1
.08;
1.2
2)
1.00
1.
01 (1
.00;
1.0
3)
1.02
(1.0
0; 1
.03)
1.
02 (1
.01;
1.0
4)
1.05
(1.0
3; 1
.06)
1.
00
1.03
(1.0
1; 1
.05)
1.
04 (1
.02;
1.0
7)
< 0.
0001
0.
0005
<
0.00
01
< 0.
0001
46
Bio
mar
ker
and
toot
h lo
ss le
vel
Mod
el 1
(Rel
ativ
e In
crea
se
[95%
CI]
) p-
valu
e M
odel
2
(Rel
ativ
e In
crea
se
[95%
CI]
) p-
valu
e M
odel
3
(Rel
ativ
e In
crea
se
[95%
CI]
) p-
valu
e
1-14
N
o te
eth
hs-T
ropo
nin
T
26-3
2
20-2
5 15
-19
1-14
N
o te
eth
NT
-pro
BN
P 26
-32
20
-25
15-1
9 1-
14
No
teet
h
1.18
(1.1
5; 1
.21)
1.
32 (1
.28;
1.3
6)
1.00
1.
05 (1
.01;
1.0
8)
1.10
(1.0
6; 1
.15)
1.
16 (1
.12;
1.2
0)
1.25
(1.2
0; 1
.30)
1.
00
1.16
(1.1
0; 1
.23)
1.
37 (1
.29;
1.4
7)
1.55
(1.4
7; 1
.64)
1.
71 (1
.61;
1.8
2)
< 0.
0001
<
0.00
01
1.07
(1.0
5; 1
.10)
1.
11 (1
.09;
1.1
4)
1.00
0.
98 (0
.95;
1.0
1)
1.01
(0.9
7; 1
.04)
1.
01 (0
.98;
1.0
4)
1.02
(0.9
9; 1
.06)
1.
00
1.04
(0.9
9; 1
.09)
1.
09 (1
.03;
1.1
6)
1.14
(1.0
8; 1
.20)
1.
17 (1
.11;
1.2
5)
0.07
55
< 0.
0001
1.07
(1.0
5; 1
.10)
1.
11 (1
.08;
1.1
3)
1.00
0.
98 (0
.95;
1.0
1)
1.01
(0.9
8; 1
.05)
1.
01 (0
.98;
1.0
4)
1.02
(0.9
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47
Table 13. Risk of MACE and CV death for one increase in tooth loss level after adjustment for risk factors and biomarkers
Adjustment MACE
(HR [95% CI]) p-value CV death
(HR [95% CI]) p-value
Model 1 Model 2 Model 3 Model 3 + hs-CRP Model 3 + Lp-PLA2 Model 3 + GDF-15 Model 3 + hs-Troponin T, NT-proBNP Model 3 + hs-CRP, Lp-PLA2, GDF-15 Model 3 + hs-CRP, Lp-PLA2, GDF-15, hs-Troponin T, NT-proBNP
1.16 (1.12-1.20) 1.08 (1.04-1.12) 1.06 (1.02-1.10) 1.05 (1.00-1.09) 1.06 (1.01-1.10) 1.05 (1.01-1.10) 1.03 (0.99-1.07) 1.05 (1.00-1.09) 1.03 (0.98-1.07)
<0.0001 0.0002 0.0041 0.0404 0.0091 0.0273 0.1893 0.0407 0.2561
1.30 (1.23-1.37) 1.18 (1.12-1.25) 1.17 (1.10-1.24) 1.16 (1.08-1.23) 1.16 (1.09-1.24) 1.15 (1.08-1.23) 1.12 (1.05-1.19) 1.14 (1.07-1.22) 1.11 (1.04-1.19)
< 0.0001 < 0.0001 <0.0001 <0.0001 <0.0001 <0.0001 0.0006 <0.0001 0.0024
Model 1 is adjusted for study treatment only. Model 2 is adjusted for Model 1 and age, systol-ic blood pressure, diastolic blood pressure, BMI, LDL cholesterol, HDL cholesterol, history of diabetes mellitus, prior MI, gender, smoking status and waist hip ratio. Model 3 is adjusted for Model 2 and eGFR, family history of coronary heart disease, alcohol consumption, years of education, level of physical activity and country income level.
48
Discussion
The aim of this thesis was to assess the prevalence and management of tradi-tional risk factors as well as the prevalence and prognostic influence of PD, a less explored risk factor, in a large global chronic CHD population – an en-deavour to elucidate mechanisms behind the excess risk prevailing in this vast patient category.
Main findings In paper I we found that a majority of patients in this global CHD cohort were on evidence-based secondary preventive medications. Nevertheless, CV risk factors known to confer adverse outcome were highly prevalent and a large proportion of patients did not meet guideline-recommended treatment goals for blood pressure, LDL cholesterol or glucose levels. Although re-gional differences were observed, the need for improved preventive efficacy was evident across all geographic regions.
The results in paper II represent the hitherto largest study on the prevalence of PD markers in a CHD population. They showed that self-reported tooth loss was common with approximately 40% of participants missing more than half of their teeth and one fourth reporting gum bleeding at baseline. There were substantial differences in prevalence between geographical regions and even among countries within the same region. Further, there were significant associations between a broad range of CV risk factors and the self-reported PD indicators, particularly for tooth loss.
In paper III, self-reported tooth loss was robustly associated with increased rates of the primary outcome, CV death, all-cause death, and stroke. The associations were independent of a wide range of CV risk factors and comorbidities associated with recurrent ischemic events, death, and socioec-onomic status. We did not detect an association between level of tooth loss and risk of MI.
In paper IV, we found that tooth loss was associated with gradually in-creased levels of several biomarkers known to predict CV events. The bi-omarker associations suggest that tooth loss may be related to several differ-
49
ent pathophysiological mechanisms affecting CHD morbidity and mortality, including inflammation, cellular stress and myocardial dysfunction. Adjust-ment for most of the biomarkers in addition to established CV risk factors had little attenuating effect on the risk of adverse outcome, which further supports tooth loss as an independent predictor of CV events, but also sug-gests that part of its prognostic influence is unaccounted for.
An appraisal of contemporary secondary coronary heart disease prevention (Paper I) The most noticeable conclusion to be drawn from this study is that a high use of pharmacological agents alone is clearly insufficient as secondary pre-vention, as evidenced by the comparatively low attainment of risk factor goals. Indirectly, this suggests that the other vital secondary preventive in-strument, lifestyle modification, is greatly underutilized. This assumption has been corroborated by other studies from the STABILITY cohort, demon-strating a low participation in cardiac rehabilitation programs, poor adher-ence to a ‘Mediterranean’ dietary pattern associated with favourable out-come, and inadequate physical activity.172–174 For example, a third of STA-BILITY patients engaged only in low-grade physical activity and almost half reported less exercise compared to before their CHD diagnosis. The decrease in physical activity was partly determined by CHD-related symptoms or co-morbidities, but importantly also by demographic and cultural factors, indi-cating challenges as well as room for improvement outside specific disease-modifying measures.172 These findings are in stark contrast to the convincing evidence supporting lifestyle intervention measures such as smoking cessa-tion175 and cardiac rehabilitation after an MI.176 Moreover, the favourable effects of physical activity in patients with established CHD have been shown to outweigh the risks.177 The STABILITY protocol specifically en-couraged attention to a high standard of care, both in terms of pharmacologi-cal and lifestyle intervention.169 The implementation of such measures is favoured by a clinical trial setting, which ensures regular follow-up and monitors treatment adherence. Nevertheless, during the median follow-up time of 3.7 years, aspirin use decreased (96% at trial initiation versus 90% at close-out). The use of statins, beta-blockers and ACE-inhibitors/ARBs was largely unchanged and there were only small improvements in LDL choles-terol (median 2.04 mmol/L at close-out vs. 2.07 mmol/L at baseline) and systolic blood pressure (131.0 mmHg vs. 131.5 mmHg).80
Repeated evaluations of the efficacy and implementation of secondary pre-vention are informative about transformations of the CV risk spectrum and can assist us in the appropriate direction of preventive efforts and resource
50
allocation. Other important assessments of risk factor prevalence and pre-vention in larger CHD populations include the comprehensive EU-ROASPIRE and REACH studies.66–68 Detailed comparisons between such studies, including ours, are precarious due to differing methodology and study populations. However, some general patterns and disparities are evi-dent as demonstrated in Figures 6 and 7. For instance, an improvement in the use of preventive medications is evident over time. Moreover, in the case of STABILITY, the use of anti-platelets and statins was superior, which to a large extent is likely attributed to selection bias and study protocol. As a consequence, cholesterol control was somewhat better in STABILITY but the prevalence of other CV risk factors, including smoking, hypertension and obesity was more or less similar. Overall, the findings from EUROASPIRE and REACH corroborate those from STABILITY and reveal a high preva-lence and profound undertreatment of risk factors despite a gradually im-proved use of pharmacotherapy. Lastly, the Prospective Urban Rural Epide-miology (PURE) study, evaluating secondary prevention from a more pro-nounced socioeconomic perspective, concluded that the lowest adherence to a healthy lifestyle, including use of preventive medications, was found in rural areas and low-income countries where a minority of patients were ade-quately treated.69,178
Figure 7. Prevalence of pharmacological treatment in STABILITY, EUROASPIRE III, EUROASPIRE IV, and the REACH registry
0% 20% 40% 60% 80% 100%
Anti-‐platelet
Beta-‐blockers
Statins
ACE/ARB
STABILITY (2014) EUROASPIRE III (2009) EUROASPIRE IV (2015) REACH (2006)
51
Figure 8. Prevalence of risk factors in STABILITY, EUROASPIRE III, EU-ROASPIRE IV, and the REACH registry. Hypertension: REACH, ≥140/90 mmHg; EUROASPIRE III and IV, BP ≥140/90 mmHg and BP ≥130/80 mmHg (≥140/80 mmHg in EUROASPIRE IV) in patients with diabetes). Elevated total cholesterol: REACH, total cholesterol >200 mg/dL (≈5 mmol/L); STABILITY and EU-ROASPIRE III, total cholesterol ≥4.5 mmol/L; EUROASPIRE IV, N/A).
In conclusion, CV risk factors beyond the inclusion enrichment criteria were highly prevalent in this global chronic CHD population and achievement of guideline-recommended treatment goals was generally poor despite a high use of cardioprotective medications. Moreover, there was little improvement in the risk factor continuum over time despite frequent follow-up and high standard of care aspirations in the study. The findings are in line with previ-ous assessments of secondary prevention and call for intensified efforts to-wards improved lifestyle modification through continued evidence-based individual interventions but importantly also through effective population-based strategies, including policy-making on a local, national and interna-tional level.179
Periodontal disease – significance of a potential risk factor for coronary heart disease (Papers II-IV) The measures of exposure In this thesis, two self-reported measures of PD/dental health were used: gum bleeding (paper II) and number of teeth (papers II-IV). They can be seen as markers of gingivitis, the early reversible form of PD and irreversible end-stage chronic PD, respectively. However, a formal PD diagnosis relies
0% 20% 40% 60% 80% 100%
Central Obesity
Obesity
Elevated Total Cholesterol
Diabetes
Hypertension
Smoking
STABILITY (2014) EUROASPIRE III (2009) EUROASPIRE IV (2015)
52
on clinical diagnostics and cannot be replaced by single self-reported measures alone. Therefore a certain amount of caution is warranted when interpreting their denotation. In validation studies, self-reported gum bleed-ing has generally demonstrated a lower sensitivity than specificity when compared to bleeding on clinical examination, although with varying results depending on the wording of the question. It also appears to be vulnerable to other factors, such as socioeconomic status and access to dental healthcare.180–182 Contrariwise, self-reported number of teeth correlates close-ly with the number of teeth on examination according to several stud-ies.181,183,184 While gum bleeding is almost always related to gingivitis, tooth loss can have other causes than PD including trauma and caries. Notwith-standing, PD has been demonstrated to be the most common cause of tooth loss in patients aged above fifty years of age,185,186 and may therefore be seen chiefly as a marker of PD in older populations.
Prevalence of tooth loss and gum bleeding in a large coronary heart disease population As demonstrated in paper II, tooth loss constituted a common co-morbidity with only 20% of patients having all of their teeth and 40% less than half of their teeth. We have found no previous study of this size and global scope reporting prevalence of tooth loss and gum bleeding in a CHD population. The recognized heterogeneity regarding methodology and populations among studies make inter-study comparisons hazardous.91 For instance, the prevalence of edentulism in our study was both higher115,132 and lower92,131 than that reported in other studies from general populations, but the great disparities between these populations render any conclusions uncertain. Co-variation of common risk factors such as smoking and diabetes mellitus like-ly explain part of the difference in prevalence observed between geograph-ical regions and countries in our study. Other unmeasured factors such as historical access to dental and general health care, socioeconomic differ-ences over time and trends in dental extractions could also have substantial impact. Compared to some prevalence estimates of gum bleeding in as many as 50% of the general population,89 it appeared much less common in this cohort. Moreover, little correlation was seen between gum bleeding and tooth loss, possibly a reflection of their representing opposing entities on the PD spectrum. However, it could also indicate unreliability and inaccuracy of the less validated gum bleeding measure, as also suggested by the relatively low gum bleeding prevalence, especially in light of the high use of platelet inhibitors.
53
Associations with cardiovascular risk factors A higher degree of tooth loss entailed a gradually greater burden of CV risk factors according to the analysis in paper II. Patients with tooth loss also had a lower socioeconomic status as evidenced by lower education, higher finan-cial stress and possibly also by less alcohol consumption and work stress.187 Patients with gum bleeding had higher levels of LDL cholesterol and systolic BP, but were less likely to be smokers, a finding in agreement with a previ-ous study showing a strong suppressing effect of smoking on gingival bleed-ing.188 They also had a higher education and reported more alcohol consump-tion and work stress, which could suggest that gum bleeding is more fre-quently reported by patients in higher socioeconomic categories with more regular dental care habits. The fact that there were relatively fewer associa-tions between gum bleeding and CV risk factors could indicate that gingivi-tis does not impact CV risk to the same extent as tooth loss, a marker of more severe chronic PD.
The relationship between smoking, diabetes and PD is established but asso-ciations between PD and other CV risk factors are less known and existing reports include evidence both in favour and against.189-192 Few, if any, studies prior to this one have investigated the relationship between PD and such a wide array of CV risk factors in the same population and although many of the associations herein were modest, they could have a significant effect on a population level considering the high prevalence of these conditions. Alt-hough causality cannot be claimed for any of the associations based on our analysis, the broad affiliation between the PD markers and CV risk factors consolidates the concept of chronic CHD and PD sharing common ground and it is possible that risk increases incurred by PD in CHD are partly medi-ated by these risk factors. Moreover, it highlights the need to evaluate these risk factors with respect to confounding in the analysis of the PD-CHD rela-tionship, not least the multiple socioeconomic and psychosocial factors.
Associations with outcomes As described in the introduction of this thesis, there is little and mostly con-flicting information about the impact of PD on outcome in patients with established CHD.130,137,149,152 Moreover, and to the best of our knowledge, the relationship between tooth loss and clinical outcomes in CHD patients has not been previously evaluated at all and as such, the results in paper III pro-vide generalizability to new patient populations and enhance the global scope of the concept of oral disease-associated CV risk. While no associa-tion was detected for MI, more tooth loss entailed a gradually increased risk of all other outcomes. These findings are consistent with some previous co-hort studies from non-CHD populations. For example, the Health Profes-
54
sionals Follow-up Study reported an increased risk of non-fatal and fatal CHD (RR 1.36 [1.11-1.67]) in participants with 10 or fewer teeth. The risk was higher (RR 1.79 [1.34-2.40]) when only fatal events were included,132 signalling an attenuated effect on total risk by including non-fatal MI, simi-lar to our findings. Another cohort study found that missing 9 or more teeth was associated with both all-cause (RR 1.43 [1.95-1.96]) and CV death (RR 1.88 [1.10-3.21]).133 Furthermore, a Swedish study of 7674 individuals eval-uated a number of clinical periodontal measures and found a dose-dependent association with CV and all-cause death only for number of teeth but not the other periodontal variables.127 In a Japanese cohort, an association was ob-served only among middle-aged but not older men, indicating that the effect of tooth loss may vary by age.138 In contrast, our findings contradict two cohort studies in which the initially positive association between varying degrees of tooth loss and CV outcomes was eradicated by adjustment for common confounders.155,156
The high reliability and detail of our baseline data paired with careful end-point ascertainment provide a good basis for validity of our results. Moreo-ver, the multivariable adjustment renders our findings an unlikely result of confounding alone. However, considering the positive associations with most outcomes, the lack of an independent relationship between tooth loss and MI was puzzling. It is a result in line with two previous studies showing no relation between tooth loss and MI150,154 but contradictive of a recently published large retrospective cohort study in which a robust association with MI was observed, even after multivariable adjustment.193 Our negative result could have several possible explanations. First; when subcategorized, the majority of CV deaths (N=705) were attributed to “unknown cause” (21%) and “sudden death” (44%). MI was possibly the underlying cause of many of those events194 and if so, the “true” MI association may in fact have been stronger. Second; as previously discussed, while tooth loss is a recognized and validated measure of oral health and considered a PD marker, it may also have other important causes. Given these imprecisions, tooth loss may not constitute a sufficiently specific marker of PD capable of exposing an existing relationship between PD and MI. Indeed, studies have shown that the association between PD and MI varies greatly depending on the exposure measure and that number of teeth may be a relatively weak measure in that respect.195 Moreover, the association with MI may also vary by the specific cause of tooth loss as evidenced in one study, showing that only tooth loss/extractions due to infection were linked with MI, information which was unavailable in our study.196 Third; it is possible that the segment of CHD patients who are most vulnerable to influence from PD, and therefore most likely to expose an association, are those with the gravest disease, i.e. the largest MIs causing death and severe heart failure. The fact that they were not part of the STABILITY population due to selection bias could explain
55
the absence of an association. Fourth; the negative finding could be subject to effect modification. For example, age has been a suggested effect modifier in the PD-CHD relationship, with certain studies finding a positive associa-tion between PD and CHD only among younger age groups.138–141,160 As a result, the relatively high mean age of the entire STABILITY population could explain why an association was not detected. Finally, the observation of a robust relationship with stroke in contrast to the negative MI association is intriguing and bewildering. Similar observations have been demonstrated previously129,131,150, thus rendering ours less likely to be a spurious chance finding. Reasons for this are unclear but the closer anatomical relationship between PD and stroke has been suggested in one study,150 and differing etiological factors197 and pathophysiology for MI and stroke is another possi-ble, but unexplored, hypothesis.
Associations with biomarkers The results in paper IV represent the largest study to date of the relationship between tooth loss or PD and prognostic biomarkers. Previous observations of associations with inflammatory markers are mainly limited to small size studies of CRP108 and IL-6,109,198 often with limited adjustments, and none have specifically studied tooth loss. With regard to Lp-PLA2 activity, a pro-inflammatory enzyme strongly expressed in vulnerable atherosclerotic plaques,199 a small study of 32 patients with moderate-severe clinical PD reported a relationship between enzyme levels and PD severity.200 The ob-served associations in our study, although modest and noticeable primarily among the higher tooth loss levels, were independent of multiple co-variables and evident for upstream (IL-6), downstream (hs-CRP), and alter-nate markers of inflammatory pathways (Lp-PLA2 activity), thus supporting an inflammation-mediated relationship between PD and CHD.
The positive correlation between tooth loss or PD and GDF-15 appears to be novel and not previously described in the literature. Increased expression of GDF-15 has been reported in various cardiac afflictions, including MI201 and heart failure,202 but also in conjunction with inflammation.107 Although it appears to be an independent predictor of CV risk, it is not a cardiac-specific biomarker but rather reflects cellular stress resulting from various stimuli, of which tooth loss-associated mechanisms appear to be one. An independent association between PD and cardiac biomarkers could support the existence of a causal relationship between PD and cardiac disease, including CHD. One study found higher levels of both troponin and NT-proBNP in 44 pa-tients with clinical PD compared to healthy controls.203 However, consider-ing that the results were unadjusted and from a small population, the findings in our study of a non-significant relationship between tooth loss and hs-troponin T but significant for NT-proBNP appear novel. The lack of associa-
56
tion in the fully adjusted model with troponin, a specific marker of myocar-dial injury,106 suggests that tooth loss is not primarily related to mechanisms generating elevated troponin levels in stable chronic CHD patients. Never-theless, the observation of a clearly positive association with NT-proBNP does indicate a relationship between tooth loss and cardiac dysfunction alt-hough we did not evaluate associations between tooth loss and heart failure specifically. However, assuming that the relationship between tooth loss and NT-proBNP does signal a relationship with heart failure, the underlying mechanism is unclear. While ischemia is the most commonly recognized cause of heart failure, the results from paper III did not support a relationship between tooth loss and MI and other important etiological factors for heart failure were included in the multivariable model. This could indicate that other less established pathways also may be of relevance. For instance, cross-reactivity and molecular mimicry between bacterial and myocardial antigens conferring autoimmunity have been implicated in heart failure, as has long-term activation of toll-like receptors possibly in response to chronic exposure to bacterial antigens.204 Collectively, these findings suggest a com-plex relationship between tooth loss and CHD, possibly involving several pathophysiological mechanisms embodied by various biomarkers related to CV disease.
Tooth loss and other markers of PD have previously been linked to adverse outcomes and CHD in this population and others, even after adjustment for background factors.127,205 Most of the biomarkers studied in paper IV also have demonstrated independent predictive abilities in both CHD and non-CHD populations,77,78,104–107 with recently presented data from the STABIL-ITY cohort showing associations between a majority of the studied bi-omarkers and major adverse CV events.206-208 In addition to the cross-sectional analysis of the association between tooth loss and biomarker levels we also added the biomarkers as co-variables to the outcome analysis from paper III. Although their inclusion in the multi-variable model could impli-cate adjustment for mediators in the tooth loss-CHD relationship and does not allow for causal inference, it generated noteworthy results. Interestingly, adjustment for most biomarkers, all with previously demonstrated independ-ent prognostic abilities, had little influence on the association between tooth loss and CV outcomes. Thus, tooth loss has a prognostic influence in these patients that extends beyond that of biomarkers and established CV risk fac-tors. Regardless of underlying cause, it is an important finding in terms of prognostication in this patient category. As a result, and given the simple and inexpensive nature of self-reported tooth loss, its clinical utility should be explored further, for instance as part of a simple risk stratification model.
As previously reported, we did not find an association between tooth loss and MI in this population. Thus, specific drivers of the stronger association
57
with CV death are not clear. They do not appear to involve heart failure to a large extent, at least not heart failure at study initiation, considering the per-sisting association despite adjustment for NT-proBNP. Other CV causes of death, such as malignant arrhythmias could be of relevance but little is cur-rently known about their relationship with PD and tooth loss. Periodontal pathogens have also been suggested as potential factors in other vascular pathologies, e.g. aortic aneurysms.209 The addition of NT-proBNP had a somewhat attenuating effect on the CV death association and eliminated the association with MACE (a composite that includes CV death). This implies that NT-proBNP, an established strong predictor of risk, shares some prog-nostic information with tooth loss and evaluating the relationship between tooth loss and heart failure could shed more light on this issue. Conversely, the other biomarkers that were associated with tooth loss in the cross-sectional analysis do not appear to contain any substantial degree of infor-mation pertinent to the prognostic influence of tooth loss. Importantly how-ever, this relates to the prognostic information of tooth loss and does not divulge specific information on possible causal pathophysiologic pathways between PD or tooth loss and CHD development.
Tooth loss and poor outcome – our findings and some possible mechanisms of association Similar to previous studies, the findings presented in this thesis cannot estab-lish whether a causal relationship exists between PD/tooth loss and CHD. In order to definitively settle the causality issue, a randomized intervention study of substantial magnitude and duration would be required, which would also present substantial ethical challenges. Nevertheless, the thesis consti-tutes a unique source of information in the respect that it contains studies of several aspects of the relationship between PD and CHD in the same large population, thus providing a solid basis for interpretation and discussion.
In paper II, we demonstrated that tooth loss (and gum bleeding) was closely linked to multiple socioeconomic and psychosocial factors. It could therefore be argued that the link between tooth loss and CV risk is a mere reflection of poor health behaviour secondary to low socioeconomic status. Education was the only socioeconomic variable used in the adjustment models in our studies and it is possible that other variables could have attenuated the asso-ciations further. However, education is known to be one of the strongest indicators of socioeconomic status and is likely to overshadow many others. In addition, as we also adjusted for potential surrogates for socioeconomic status, such as physical activity and alcohol consumption, the risk of signifi-cant residual confounding in this area is unlikely. This is further supported by a previous report of a persisting significant association between number
58
of missing teeth and outcomes despite adjustment for several socioeconomic variables, including education.135 We also demonstrated a relationship be-tween PD markers and several conventional CV risk factors, although some of these associations (e.g. LDL cholesterol) were minor and may not be clin-ically relevant. Nevertheless, it could indeed be contended that the tooth loss-CHD association is mediated by such common established risk factors, as lack of adjustment has been a recognized problem in many previous stud-ies.210 However, we used step-wise adjustment in both paper III and IV, achieving the greatest attenuating effect on the association by adding con-ventional CV risk factors, of which most known to impact CV risk were included. The subsequent addition of less established markers of risk did little in terms of attenuation. Therefore, the likelihood of significant residual confounding by established common risk factors seems improbable.
The findings in paper III indicated the highest risk of adverse outcome among those with no teeth suggesting that the CV risk possibly conferred by tooth loss-generating mechanisms is not an acute one, but rather an accumu-lation of risk resulting from long-term exposure. Several mechanisms by which PD could affect CHD have been suggested, including promotion of endothelial dysfunction, atherosclerosis progression and plaque destabiliza-tion. Irrespective of the specific nature of such a mechanism the host-mediated immune response to PD is widely believed to be a crucial prerequi-site, resulting in elevated levels of inflammation markers, as supported by the findings in paper IV. Conversely, the finding of the highest biomarker levels among those with no teeth could also be interpreted as a challenge to the concept of PD-generated inflammation as an instigator of CHD. As eden-tulous patients are likely rid of most of the substrate for periodontal infection and subsequent inflammation they would be expected to exhibit lower levels of inflammatory biomarker levels. The fact of the opposite in our study pos-sibly signals a continued presence of PD and persistent inflammation among edentulous patients, as substantiated by one study,211 while others have pointed to the opposite.212 It could also imply that systemic inflammation related to tooth loss is generated by other causes than PD, or that patients with both CHD and advanced PD are predisposed to an increased inflamma-tory response, possibly mediated by a common trait such as a genetic suscep-tibility to both diseases, as suggested in two studies.213,214 Indeed, the associa-tions between tooth loss and multiple biomarkers could be an indication that PD affects CHD by several pathways, not only inflammatory, but it could also signal that the two conditions share common causal mechanisms.
If the demonstrated influence of tooth loss on CV risk in this thesis is neither mediated by confounding nor PD, it could be a secondary and functional result of the tooth loss itself, leading to poor nutrition. Indeed, several stud-ies have confirmed that an impaired dentition leads to a deteriorated diet
59
with increased consumption of unhealthy food items and a reduced intake of healthy foods, such as fruits and vegetables.215–217 However, the magnitude of these dietary changes are sometimes questionable and although we did not adjust for dietary factors in our analysis, other studies have with only mini-mal attenuating effects as a result.132,145,194 A deterioration of diet secondary to loss of masticatory function therefore appears to be a minor factor in the context of tooth loss-associated CV risk.
Limitations A general limitation in this thesis concerns a possible lack of generalizability to other populations due to underrepresentation of certain regions, ethnicities and socioeconomic groups; patient selection by inclusion and exclusion cri-teria; and medication use affected by specific study requirements. In paper II, a control group void of CHD would have improved the assessment and interpretation of the PD prevalence.
For the purposes of paper I, it is also probable that participants in a clinical trial are better treated and more compliant than a general CHD population, which however is more likely to lead to an underestimation of the prevalence of poor risk factor control. Further, data in paper I were presented for broad geographical regions and do not illustrate differences between individual countries. Lastly, our data on medication use do not reveal potentially atten-uating factors such as inadequate dosing, lack of adherence or other reasons for possible pharmacological undertreatment.
In papers II-IV, the PD exposure measures constitute an important general limitation, which has been discussed previously. The possible unreliability and underestimation of self-reported gum bleeding could affect the degree of associations in paper II, and it was subsequently excluded from the discus-sions in papers III-IV, although included in the pre-specified analysis in pa-per III, which showed no relation with any outcome. In addition to the previ-ously mentioned possible weaknesses of the tooth loss measure, it may also reflect other unmeasured factors such as historical access to dental care, temporal and geographical trends in tooth extractions, possibly rendering it a less specific marker. Moreover, we had no information on the duration of tooth loss, incident tooth loss during follow-up or denture use, which could potentially affect the results and implications of the tooth loss measure itself. The arbitrarily assigned tooth loss levels may also introduce imprecision in the analyses.
Finally, although multivariable adjustment was performed, residual con-founding from unknown or unmeasured factors cannot be ruled out.
60
General conclusion and future perspectives Based on the findings in this thesis, part of the excess risk of death and re-current ischemic events observed among patients with established CHD is likely attributed to inadequate secondary prevention, of which lifestyle mod-ification constitutes an integral part. The implementation of conventional health care interventions addressing these issues is insufficient and multi-level approaches are presumably required for further improvement.
Additionally, a portion of the excess risk could possibly be attributed to the influence of less explored risk factors. We identified a significant relation-ship between highly prevalent markers of PD, particularly tooth loss, and multiple aspects of CHD, including CV risk factors, prognostic biomarkers, and outcomes. Stable chronic CHD patients with tooth loss were found to be at higher risk of adverse outcome than predicted by traditional risk factors and the mechanism by which this risk is conferred may involve multiple pathways. Considering these findings, it may be prudent to carefully evalu-ate CHD patients with evidence of tooth loss with respect to their CV risk profile. Conversely, including an assessment of dental status in the clinical examination of CHD patients can also be advocated as a means improve risk stratification. The utility of a simple clinical risk assessment model including self-reported tooth should be evaluated in the future.
PD treatment has beneficial effects on oral health and quality of life. As such, it is uncontroversial and should be recommended to all patients suffer-ing from any degree of disease. There is also evidence suggesting possible beneficial effects of PD treatment on surrogate markers of CHD, inflamma-tory markers and systemic conditions that constitute risk factors for CHD, such as diabetes. However, its effects on clinical outcomes are not known and in order to support its advocacy as a means to improve CHD prognosis, further studies are warranted.
61
Acknowledgments
I wish to extend my deepest gratitude and appreciation to those who have contributed to this thesis in any way, with a special mention to the following:
Claes Held – my supervisor, for your warm, experienced and intelligible guidance through the intricate world of research, for keeping it cool, and for your invaluable support and friendship. You have made it such an enjoyable ride!
Emil Hagström – my co-supervisor, for your never failing patience, availa-bility and knowledgeable advice on epidemiology, for great discussions in various places around the world and at home, and for your friendship and savant-like attention to detail.
Bertil Lindahl – my co-supervisor, for your insightful advice, clarity and encouraging comments along the way.
STABILITY participants, investigators and personnel – for making this at all possible.
Lars Wallentin, Ralph Stewart, Harvey White, Wolfgang Koenig, An-drzej Budaj, Rebekkah Brown, Richard Davies, Robert Harrington, Piyamitr Sritara, Susan Krug-Gourley, Stephan Denchev, Henk Swart, Dragos Vinereanu, Margus Viigimaa and Joseph Soffer – my co-authors, for your commitment, co-operation and advice on how to improve our anal-yses and manuscripts. I am grateful to have had the privilege to learn from your vast experience.
Diane Gallup, Megan Neely, Karen Chiswell, Amanda Stebbins and Ollie Östlund – statisticians at Duke Clinical Research Institute and Uppsala Clinical Research Center, for your hard work in spite of inhumane deadlines.
Johan Lugnegård, Jonas Oldgren and Gunnar Frostfeldt – present and previous heads of cardiology department, for hiring me back in the day (Gunnar), and for providing means.
The Swedish Heart-Lung Foundation – for research grants.
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Ebba Bergman – multi-tasking publications manager at Uppsala Clinical Research Center, for speedy and top-of-the-line support.
Anita Öström – secretary extraordinaire and so much more at Uppsala Clin-ical Research Center, for always helping out.
My colleagues – for making work such a great place to be! Special thanks to my friends and colleagues in the heart failure section: Gerhard Wikström, Per Kvidal, Christina Christersson, Erik Björklund, Johan Forsblad, Mo-hammad Kavianipour, Birgitta Jönelid, Stina Johansson, Gabriel Arefalk and Inga Ingimarsdottir. Every day working with you is a privilege and a never-ending learning experience.
Hans Wedel – for so graciously taking time out of your schedule to share your knowledge and discuss statistical issues.
My friends – for being such kind, charismatic, humorous, sincere, thought-ful and intelligent people and for wanting to share all those qualities with me.
Jonas Backström – my dear friend, for helping me see life just the way I like it. Forever missed, never forgotten.
The Gahm-Selander families – my wonderful extended family, for your friendship and “child support”.
My mother, father and brother – for your love, unwavering support and guidance through good times and bad, for being an inspiration through life. For always being there, for caring not just for me but also for my family.
Elin, Einar and Judith – Love. Unconditional. Always.
“I think the knowledge came to him at last — only at the very last.”
Joseph Conrad
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Acta Universitatis UpsaliensisDigital Comprehensive Summaries of Uppsala Dissertationsfrom the Faculty of Medicine 1129
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A doctoral dissertation from the Faculty of Medicine, UppsalaUniversity, is usually a summary of a number of papers. A fewcopies of the complete dissertation are kept at major Swedishresearch libraries, while the summary alone is distributedinternationally through the series Digital ComprehensiveSummaries of Uppsala Dissertations from the Faculty ofMedicine. (Prior to January, 2005, the series was publishedunder the title “Comprehensive Summaries of UppsalaDissertations from the Faculty of Medicine”.)
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