Determinants and Timing of Radiographic Stabilization of Intracranial Hemorrhage After Neurosurgical

Procedures for Traumatic Brain Injury.

Ross Finesmith M.D.

INTRODUCTION

Traumatic brain injury is a leading cause of morbidity and mortality in the US. The United States annual head injury incidence is approximately 200 per 100,000 admitted to a hospital with TBI, and 20 to 30 per 100,000 die per year[1]. One of the most common non-neurological complications of TBI is deep vein thrombosis (DVT) and pulmonary embolism (PE). The increase in morbidity and mortality associated with venous thromboembolism (VTE) after trauma have been well described[2].

VTE manifests in up to 58 percent of all major trauma patients[3]. The frequency of VTE increases with the severity of the injuries and the time confined to bed with immobility[4]. Pulmonary embolism has been observed in up to 22 percent of patients with trauma and fatal pulmonary embolism is the third most common cause of death in patients who survive the first 24 hours[5].

The benefits of prophylaxic anticoagulation post-operatively in hip or knee surgery and those immobile, such as spinal cord injuries, are well established[6-8] In addition, prophylactic anticoagulation in major trauma patients has also been shown to be safe and effective[3, 9]. However, there have not been enough studies to recommend prophylaxis in patients recovering from hemorrhagic brain injury associated with head trauma.

The anti-coagulation strategy in non-brain-injured trauma patients is to administer low-molecular weight heparin enoxaparin 24 hours after the injury. The occurrence of subdural hematoma has been reported in non-TBI patients receiving prophylactic anti-coagulation in the form of IV heparin and warfarin[10]. Overall the safety and efficacy of prophylaxic anticoagulation in general trauma patients has ben accepted, but the indication to include use in brain-injured patients has yet to be established. This is a major health concern because of the frequency of TBI and the subsequent incidence of complications DVT and PE in those patients.

A randomized, double blind trial, utilizing contrast venography as the means of assessing anticoagulation prophylaxis efficacy in preventing venous thromboembolism, confirmed that patients with major trauma are at very high risk for venous thromboembolism and demonstrated that low-molecular-weight heparin, is efficacious in preventing such events[3]. A subsequent prospective observational study treating TBI patients with enoxaparin in the first 48 hours,

found that the occurrence of significant cerebral bleeding after anti-coagulation prophylaxis was 1.1% compared to the known risk of DVT (18%) and PE (4.8%)[11].

The controversy of treating TBI patients with enoxaparin arises from the potential of exacerbating cerebral bleeding and causing irreversible neural damage. This factor has impeded research trials on prophylaxic anticoagulation in TBI. Unfortunately, this results in over 50% of patients with TBI developing either deep vein thrombosis or a pulmonary embolism[3].

The main factor is the concern of iatrogenically propagating an intracranial hemorrhage before the bleeding injury in TBI has stabilized. There is minimal data that provides a timeframe of stabilization of traumatic intracerebral hemorrhages and therefore clinicians have no formal guidelines to apply. Anti-coagulation therapy is proposed to be safe after cerebral hemorrhages stabilize and begin the healing process. There is general consensus that anticoagulation is necessary in patients with TBI [12], however, there are no recommendations as to the optimal timeframe to initiate therapy. Limited data exists as to when these high-risk patients can safely receive prophylaxis. This is the critical link that must be addressed to safely initiate protocols. The initial step is to determine when a cerebral hemorrhage stops progressing in TBI and which factors contribute to its stabilization. This will begin to provide an algorithm in developing protocols to prospectively study the use of anti-coagulation therapy in TBI.

METHODS

Study Design and Patient Population

The University of Texas-Southwestern Medical Center compiles a prospective database of clinical parameters, laboratory and imaging studies as well as outcome data on all patients admitted to the trauma service. A total of 432 consecutive adult patients with traumatic intracranial hemorrhage presenting to our academic, urban, Level I trauma center between February 2010 and November 2011 were identified. In this retrospective analysis of patient data, the entrance criteria for this study included those presenting with traumatic intracranial hemorrhage requiring neurosurgical intervention. The clinical and imaging criteria for requiring neurosurgical intervention was progressive worsening of clinical status with increasing size of hemorrhage or ventricular size on CT. A total of 139 patients qualified for the study. See figure 1. There were 12 patients that expired in the first 24 and were excluded from the analysis, resulting in 127 patients meeting study entrance criteria. To evaluate potential interventional factors effecting hemorrhage stabilization, the patients were

stratified into surgical treatments groups: craniotomy group, ventriculostomy group, and a ventriculostomy converted to craniotomy group.

The aim of this study was to determine the factors influencing hemorrhage stabilization of a patient within 72 hours of brain injury because this is a precondition for initiation of anti-coagulation prophylaxis.

Cranial CT scans and Definitions

All patients underwent serial computed tomography (CT) scans during their hospitalization to assess intracranial status and to determine the time from injury to stabilization. Radiographic stabilization time was defined as the time from injury to the final cranial CT scan showing no worsening from the prior scan. A worsening was defined as an enlargement in any dimension of a hemorrhage, mass effect ventricular size or ischemic injury, or the identification of a new injury on subsequent cranial CT scans.

StatisticsKaplan-Meier curves were used to determine the time to radiographic stabilization for each group, and longrank tests were used to compare the Kaplan-Meier curves (GraphPad Prism, v5.0 for Macintosh). Subsequently, the entire cohort was then used to create a logistic regression model. We included relevant clinical factors for univariate analyses to determine which factors were the strongest contributors to stabilization within 72 hours, using a threshold value of p<0.25 for inclusion in the regression. The clinical factors are listed in table 1.Binary logistic regression analysis was used to identify the most important variables that predicted the hypothesized clinically desirable outcome event, the hemorrhage stabilization of a patient within 72 hours of brain injury. These strongest factors were used in a backwards stepwise regression to develop our model, with α=0.05. Using the model, predicted probabilities were calculated to determine sensitivity and specificity, as well as to develop a ROC curve for the data (SPSS v20 for mac). The dependent variable was patient hemorrhage stabilization within 72 hours of brain injury.

Results

There were 36 patients in the craniotomy group, 58 in the ventricular group and 33 in the combined ventriculostomy/craniotomy group. There were no significant differences in age, sex, head AIS, hospital or ICU length of stay or discharge GCS. There were significant difference in the ISS and GCS in the ventriculostomy-only group, which may be a function of predicted survival in that cohort. See table 2.

The results of the Kaplan-Meier curve calculations revealed no statistically significant difference in the time to CT scan stabilization between the three surgical intervention courses. See figure 2.

The results of the logistic regression analysis are presented in Table 3. Sex, age, the Glasgow Coma Scale (1 relative to 3); and the size of the contusion were significant predictors at α = .05 of the likelihood of a patient stabilizing within 72 hours of brain injury. The injury severity score, presence of subarachnoid hemorrhage, subdural size, and the admission base deficit, were not significant predictors at α = .05.

The interpretation of the odds ratios for the statistically significant predictors at α = .05 in Table 3 is as follows: (a) A male patient was, on average, about 3 times more likely to stabilize than a female patient, but with very wide 95% confidence intervals (CI) ranging from about 2 to 84. Because the sex ratio in this study was heavily weighted towards males, this odds ratio may have been biased; (b) For every one year increase in the age of a patient, the likelihood of him/her stabilizing was decreased on average, by about .96, with a relatively small CI, ranging from .92 to .99, implying that the older a patient was, the less likely he/she would stabilize; (c) If a patient's GCS level was 3, corresponding to minor injury (GCS ≥ 13) then the likelihood of him/her stabilizing was, on average, about 23 times greater than if his/her GCS level was 1, corresponding to severe injury (GCS ≤ 8) with very wide CI, ranging from about 3 to 180. If a patient's GCS level was 2, corresponding to moderate injury (GCS 9-12) then the likelihood the patient stabilizing was not improved relative to a patient with a minor GCS level of 3; (d) For every one mm increase in the contusion size of a patient, the likelihood of him/her stabilizing was about the same as him/her not stabilizing, because although the p-value was marginally less than .05, the 95% CI included 1.0. The odds ratios for the injury severity score, subarachnoid hemorrhage, subdural size, and admission base deficit, were not significantly different from 1, implying that these factors had no statistically significant effects on patient stabilization. No statistically significant effects at α = .05 did not necessarily imply that these factors had no clinical significance.

Comparing the observed frequencies of patients who were observed to stabilize within 72 hours to the frequencies of patients predicted by the model to stabilize revealed that correlated with the statistical prediction model. Of the 104 that were predicted to have hemorrhage stabilization at 72 hours, 101 actually did stabilize. Of the 14 that were predicted not to stabilize, 6 were correctly predicted. The sensitivity of the prediction (i.e., the conditional probability that the logistic regression model correctly predicted stabilization within 72 hours among the patients who were actually observed to stabilize) was 92.7% (95% CI = 85.6% to 96.5%). The specificity of the prediction (i.e., the conditional probability that the model correctly predicted no stabilization in patients who actually did not stabilize) was 66.7% (95% CI = 30.9% to 91.0%). These corresponding positive and negative predictive values were 97.1% (95% CI = 91.2% to 99.3%) and

42.8% (95% CI = 18.8% to 70.4%) respectively; however, the purposive sample used in this study may not have fulfilled all the necessary theoretical criteria required to estimate population-based predictive values[13].

Discussion

A critical issue for neurosurgeons in the treatment course of patients with TBI with cerebral hemorrhage is whether the risk of VTE, especially PE, is higher than the risk of extending a hemorrhagic brain lesion from anti-coagulating prophylaxis that subsequently results in worse neurologic outcome.

Although there is consensus that TBI patients are at high risk of developing VTE, it is not clear if certain surgical and demographic factors influence time to hemorrhage stabilization signaling safety in initiating prophylactic ant-coagulation therapy.

The results of this retrospective study suggest the type of surgical intervention is not a significant factor in stabilization time. The Kaplan-Meier curves tracking time to stabilization of hemorrhage were similar in all three surgical groups.

In an effort to identify factors associated with a shorter time to hemorrhage stabilization, our regression analysis revealed three factors that were statistically significant; male gender, age, and presenting GCS. Males had a much higher odds of stabilizing within 72 hours compared with female counterparts, however it should be noted that this result is biased because of the large male population in this study. For every increase in one year of age, subjects were less likely to stabilize by a small factor of 0.96, and for those patients presenting with a high GCS score, they had a much higher odds of stabilizing early when compared with those that presented with GCS scores lower than 8.

It should be taken into consideration that binary logistic regression assumes that all of the predictor variables are independent. The interval level variables were collapsed into ordinal level variables for the purpose of the correlation analysis. The strengths of the inter-correlations between the predictor variables were consistently weak, indicated by correlation coefficients < 0.4. Multicollinearity, which is conventionally indicated by correlation coefficients > .8 or larger[14] was therefore not considered to be a problem.

In conclusion, our data suggests that patients presenting with intracranial injuries severe enough to warrant neurosurgical intervention have similar times to CT

scan stabilization, regardless of the surgical intervention approathey received. Younger, male patients that present with higher GCS scores are indicators of a higher likelihood to demonstrate stabilization of their hemorrhage within 72 hours. Additional studies aimed at prospectively assessing the safety of early prophylactic anticoagulation in high-risk subsets of TBI patients are required.

Figure 1. Patient consort diagram

Figure 2. Kaplan Meier curve. Time to hemorrhage stabilization

The numbers in parenthesis are the number of right-censored subjects in each group. There was no statistically significant difference in the time to CT scan stabilization between the three surgical intervention courses

Table 1 Clinical factors used in the binary logistic regression model

Clinical factors(predictor variables)

Outcome Measure

Patient stabilized within 72 hours of brain injury

0 = No1 = Yes

Sex of patient 0 = Male1 = Female

Age of patient 15 to 91 yearsInjury Severity Score 1 = Lowest score

75 = Highest scoreInitial Glasgow Coma Scale 1 = Severe (GCS ≤ 8)

2 = Moderate (GCS 9- 12)3 = Minor (GCS ≥ 13)

Subarachnoid hemorrhage present 0 = No1 = Yes

Subdural size 0 mm (no injury) to 70 mmContusion size 0 mm (no injury) to 80 mmAdmission base deficit (decreased level of a serum marker, indicative of metabolic acidosis or respiratory alkalosis)

Measured in bicarbonate concentration, above and below zero

Table 2. Demographics and Clinical data

Table 3 Binary logistic regression statistics

β coefficient

Standard Error of β coefficient Wald χ2 p-value Odds Ratio

95% Confidence Interval Odds Ratio

Predictor variable Lower Upper

SEX(male relative to female) 2.580 .946 7.439 .006* 13.2 2.1 84.3

AGE -.044 .022 4.091 .043* .96 .92 .99

ISS -.040 .030 1.756 .185 .96 .91 1.02

GCS (1 relative to 3) 3.127 1.055 8.786 .003* 22.8 2.9 180.4

GCS (2 relative to 3) 2.146 1.397 2.358 .125 8.5 .55 132.2

SAH(0 relative to 1) .564 .896 .397 .529 1.8 .30 10.2

SDH .097 .063 2.377 .123 1.1 .97 1.2

CON .158 .079 3.970 .046* 1.2 1.0 1.4

ABD -.107 .095 1.268 .260 .90 .75 1.1

* Significant predictor of a patient stabilizing within 72 hours of brain injury at α = .05

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