can we simplify the management of complicated pneumonia in children? samir s. shah, md, msce...

Can We Simplify the Management of Complicated

Pneumonia in Children?

Samir S. Shah, MD, MSCE

Divisions of Infectious Diseases and General PediatricsThe Children’s Hospital of Philadelphia

Departments of Pediatrics and Biostatistics and EpidemiologyUniversity of Pennsylvania School of Medicine

Objectives

Explore the use of administrative data to clarify the changing epidemiology of pneumonia and

complicated pneumonia role of operative vs. non-operative interventions in

the management of children with complicated pneumonia

Background: Pneumonia

Community-acquired pneumonia (CAP) is a common serious bacterial infection in children >600,000 hospitalizations in the U.S. each year

Up to one-third of children hospitalized with CAP have a pleural effusion (complicated pneumonia)

What do we mean by the term complicated pneumonia?

Case

3-year-old boy with cough and fever Evaluated 2 weeks ago

Diagnosed with asthma and clinical pneumonia Treated with albuterol and amoxicillin

Returns with continued cough and fevers to 39.2°C

Case: Chest X-ray

Case: Chest CT

Changing Epidemiology of Invasive Pneumococcal Disease

Licensure of a 7-valent pneumococcal conjugate vaccine in 2000 Decrease in invasive pneumococcal infections Subsequent increase in the rate of infections

caused by penicillin-resistant S. pneumoniae serotypes not included in the current vaccine

Increasing prevalence of infections caused by methicillin-resistant S. aureus

National Hospital Discharges (all ages)

■= Bacteremia of any etiology

▲= Pneumococcal bacteremia

Shah SS, et al. Clin Infect Dis 2006;42:e1-5

Pneumococcal Bacteremia By Serotype Category

♦=vaccine serotype

■=vaccine-related serotype

○=non-vaccine serotype

Steenhoff A, Shah SS, et al. Clin Infect Dis 2006;42:907-914

Invasive Disease Caused by Penicillin-Susceptible and Non-susceptible Pneumococci (ages <2)

Kyaw MH, et al N Engl J Med 2006;354:1455-1463

What does this have to do with pneumonia?

Have rates of pneumonia or complicated pneumonia changed

over time?

Datasource: National Hospital Discharge Survey (NHDS)

Created by the National Center for Health Statistics Includes only non-federal US hospitals

All hospitals with >1,000 beds Representative sample of others based on location, size &

specialty Includes ~500 hospitals & 250,000 discharges each year

Weighting of records by hospital size/region allows for calculation of nationally representative estimates

Eligibility

Inclusion Ages 1-18 years Discharged 1993-2006 Diagnosis of community-acquired pneumonia

Exclusion Age <1 to eliminate bronchiolitis Known underlying predisposition to pneumonia

(e.g., malignancy, HIV, cystic fibrosis)

Definitions of Pneumonia

Community-acquired pneumonia (CAP) Pneumonia as 1°diagnosis OR Pneumonia-related symptom as 1° diagnosis

(e.g., cough) & pneumonia as 2° diagnosis OR Empyema or pleurisy as 1° diagnosis and

pneumonia as 2° diagnosis Sensitivity of 89% and specificity of 80%

compared with medical record review

Whittle J, et al. Am J Med Qual 1997;12:187-193

Definitions of Complications

Local Metastatic Systemic

Bronchopleural fistula Endocarditis HUS

Empyema Intracranial abscess Respiratory failure

Lung abscess Mastoiditis Sepsis

Lung resection Meningitis SIRS

Osteomyelitis

Pericarditis

Septic arthritis

Abbreviations: HUS, hemolytic-uremic syndrome; SIRS, systemic inflammatory response syndrome

Challenges

Accuracy of ICD-9 codes to identify conditions of interest Does our definition exclude the sickest patients?

Change in ICD-9 codes over time (e.g., addition of 4th or 5th digits) Review annual ICD-9 addendum

Complex survey statistics (i.e., sample weights) to calculate national estimates May limit accuracy of data for subpopulations

Insufficient data in publicly available dataset to calculate standard errors for some subpopulations

Gorton CP, et al. Pediatrics 2006;117:176-180

Regional Variation in Pediatric CAP Hospitalizations (Pennsylvania)

The epidemiology of pneumonia and complicated pneumonia is complex and

changing

Evolution of Empyema

Exudative Neutrophil migration into pleural space

Fibrinopurulent Fibrin deposition Loculations impair lung expansion

Organizing Fibroblast formation produces an inelastic

membrane or “fibrinous peel”

Management of Empyema

Radiologic assessment CXR (upright & decubitus) Ultrasound CT scan


Surgical options Thoracentesis (needle aspiration) Tube thoracostomy (+ fibrinolysis) Video-assisted thoracoscopy* Thoracotomy*

*Require post-procedure thoracostomy tube


No consensus on optimal initial drainage strategy Technique? Timing?

Why use administrative data to study complicated pneumonia?

Sonnappa et al. Kurt et al. Avansino et al. Li et al. Shah et al.

Sonnappa et al.

1st randomized study of VATS vs. thoracostomy tube drainage

60 patients enrolled from January 2002 to February 2005

Groups similar in Age & Sex Preadmission symptoms Effusion stage Causative bacteria (mostly S. pneumoniae)

Sonnappa S. Am J Respir Crit Care Med 20006;174:221-227

Sonnappa et al.

Variable Thoracostomy VATS P

(N=30) (N=30)

Median LOS (days) 7 8 0.645

Tube drainage (days) +1 compared to VATS 0.055

Repeat Procedures 17% 13% ?

Kurt BA, et al. Pediatrics 2006;118:e547-e553

Kurt et al.

1st randomized study of VATS vs. thoracostomy tube drainage in U.S.

18 patients enrolled from November 2003-May 2005

Groups similar in Age & sex Preadmission symptoms & antibiotics Effusion size Presence of loculation


Kurt et al.

Variable Thoracostomy VATS P

(N=8) (N=10)

Mean LOS (days) 13.3 5.8 0.004

Tube drainage (days) 9.6 2.8 <0.001

Oxygen (days) 3.6 1.6 0.965

Narcotic use (days) 7.6 2.2 0.043

Procedures (no.) 2.25 1.0 0.002


Key Differences

Differences Kurt et al. used substantially larger chest tubes

(16-24 Fr vs. 8-10 Fr) Sonnappa et al. used more aggressive fibrinolysis LOS presented as mean (Kurt) or median

(Sonnappa) Limitations

Single centers Few patients

Can a meta-analysis more address this issue more

definitively?

Avansino et al. Systematic review of therapy for empyema (outcome data

from 3781 children)

Outcome PrimaryOperative

Primary Non-operative

Mortality 0% 3.3%Re-intervention 2.5% 23.5%Duration of hospitalization 10.8 d 20.0 dDuration of TT 4.4 d 10.6 dDuration of antibiotics 12.8 d 21.3 d

Avansino JR. Pediatrics 2005;115:1652-1659

Avansino et al.

In the pooled analysis, primary operative therapy reduced LOS by 45% (199 patients, 4 studies) Repeat procedures by 90% (492 patients, 9 studies) Results biased towards favoring operative therapy

Non-operative group= needle thoracentesis or chest tube drainage

Avansino JR, et al. Pediatrics 2005;115:1652-9

Avansino et al. - Limitations Poor study quality

No randomized studies performed at time of review Inclusion only of small (all <70 patients) observational studies

with heterogeneous study designs

Primary outcome of interest “therapeutic failure” not chosen a priori

Failure to adjust for confounding variables Timing of intervention Chemical fibrinolysis Empiric antibiotic therapy

Where do things stand?

Randomized studies Small & single center Multicenter studies difficult to conduct because

prevailing personal & institutional dogmas Pooled analyses

Few high quality studies Administrative data

Seriously?

Li et al.

2003 Kids’ Inpatient Database Inclusions

Age 0-18 years ICD-9 codes for “empyema” (510.0 & 510.9)

Exclusions Co-morbid illness Transfer from another hospital

Li ST. Arch Pediatr Adolesc Med 2008;162:44-48

Li et al.

1173 patients Primary operative management (POM) vs.

Non-operative management (NM) POM= decortication within 2 days of admission NM= everything else, including decortication 3 or

more days after admission


Li et al.

Procedure LOS Adjusted Change

Overall (n=1173)

NM 13.6 days Reference

POM 9.8 days -4.3 (-6.4 to -2.3)

Empyema as primary diagnosis (n=362)

NM 10.3 days Reference

POM 8.9 days -1.7 (-0.4 to -3.0)


Li et al. - Limitations

ICD-9 codes incomplete Other codes that suggest effusion were not included

511.1 – effusion, with mention of bacterial cause other than tuberculosis

513.0 – abscess of lung Diagnosis of pneumonia not required

Potential for inclusion of effusions not related to pneumonia (e.g., post-op)

NM group heterogeneous For example, those drained early by chest tube may be

different than those drained late by VATS and those never drained

Shah et al.

Pediatric Health Information System (PHIS) Inpatient data from 27 not-for-profit, tertiary care, U.S.

children’s hospitals Inclusions

Age 12 months to 18 years of age Discharged between 2001-2005 ICD-9 codes 510.0, 510,9, 511.1, or 513.0 as primary

diagnosis plus pneumonia (480-486) Pleural fluid drainage within 48 h of hospitalization

Exclusion Co-morbid illness

Shah SS. Arch Pediatr Adolesc Med 2008;162:675-681

Shah et al. - PHIS Study Population

Pneumonia(N=49,574)

Complicated Pneumonia

(N=2,862)

Early Drainage34% (N=961)

Late Drainage29% (N=829)

No Drainage37% (N=1,072)


Shah et al. - Initial Procedure

Procedure No. (%)

Chest tube 714 (74.3)

VATS 50 (5.2)

Thoracotomy 197 (20.5)


Shah et al. - Procedure Variation by Hospital

0%

20%

40%

60%

80%

100%

Hospital

%

OF

PROCEDURES

ChestTube

VATS

Thoracotomy

Shah et al. - Variation in LOS by Hospital*

Hospital

MEDIAN

LOS

0

2

4

6

8

10

12

14

16

*7% of patients had a LOS >28 days

Shah et al. - Change in LOS

Variable Adjusted Change in LOS*

P-value

Procedure (baseline=13.29 d)

Chest tube Reference …

VATS -2.66 d 0.006Thoracotomy -1.26 d 0.439

*Also adjusted for race, asthma diagnosis, receipt of systemic corticosteroids, empiric vancomycin therapy, and fibrinolysis


Shah et al. - Repeat Procedure

Repeat procedure 298 (31%) overall required a repeat procedure Percent requiring repeat procedure

34% with primary chest tube 8% with primary VATS 24% with primary thoracotomy


Shah et al. - Variation in Repeat Procedures by Hospital

0%

10%

20%

30%

40%

50%

60%

70%

80%

Hospital

REPEAT PROCEDURE


Shah et al. - Repeat Procedure

Variable Adjusted Odds Ratio (95% CI)*

P-value

Procedure

Chest tube Reference …

VATS 0.16 (0.06- 0.42) <0.001Thoracotomy 0.60 (0.31- 1.16) 0.133

*Also adjusted for race, asthma diagnosis, receipt of systemic corticosteriods, empiric vancomycin therapy, and fibrinolysis


Shah et al. - Summary

Among the subset of children with complicated pneumonia who undergo early pleural drainage, VATS is associated with 20% shorter LOS Fewer repeat procedural interventions


But which strategy is more cost-effective?

Background

VATS is more expensive than primary chest tube placement in terms of physician and procedural costs

Are these additional costs are offset by associated reductions in length of stay and repeat procedures?

A recent decision analysis concluded that chest tube with fibrinolysis was the preferred strategy

Shah et al.

Pediatric Health Information System (PHIS) Inpatient data from 27 not-for-profit, tertiary care, U.S.

children’s hospitals Inclusions

Age 12 months to 18 years of age Discharged between 2001-2005 ICD-9 codes 510.0, 510,9, 511.1, or 513.0 as primary

diagnosis plus pneumonia (480-486) Pleural fluid drainage within 48 h of hospitalization

Exclusion Co-morbid illness


Shah et al. – Resource Utilization (Unadjusted data)

Procedure Total Charges

Pharmacy Charges

Imaging Charges

LOS

Early chest tube $36,618 $5,978 $2,939 10 days

Early VATS $32,136 $4,385 $1,779 7 days

Any late procedure

$48,324 $7,465 $3,634 13 days

Analytic approaches

Children undergoing VATS vs. chest tube likely differ in many respects

How can one handle confounding in an observational study? Restriction Matching Adjustment in a regression model Propensity scores

Propensity Score

Represents the probability of treatment Estimated using logistic regression

Outcome = Treatment (i.e., VATS vs. chest tube) Exposures = Measured characteristics of the

study patients In theory, patients with similar propensity

scores should have a similar distribution of measured covariates

1.) Indications for Propensity Scores

Theoretical advantages Confounding by indication may cause treatment

groups to differ dramatically Comparison of propensity scores in exposed and

unexposed subjects can identify these areas of non-overlap


Useful for matching subjects Matching on propensity score outperforms other

matching strategies with many covariates Balance achieved will mimic randomization (for

measured variables)


Improved estimation with few outcomes Reliable estimates not possible with multivariable

modeling when there are many covariates and few outcomes


Propensity score by treatment interactions Can address possibility that the effectiveness of a

drug may vary according to the strength of the indication for its use


Propensity score calibration to correct for measurement errors A specific (and complicated) method that allows

one to account for multiple unobserved confounders Propensity score 1st created in a subgroup of patients

that have detailed information available This gold-standard propensity score is used to correct

the main study effect of the drug on outcome

Rationale for Analytic Approach

#1 Theoretical advantages Confounding by indication may cause treatment groups to

differ dramatically Comparison of propensity scores in exposed and

unexposed subjects can identify these areas of non-overlap

#2 Useful for matching subjects Matching on propensity score outperforms other matching

strategies with many covariates Balance achieved will mimic randomization (for measured

variables)

Approaches to Propensity Score Analysis Restriction

Restrict analysis to participants with sufficient overlap in scores

Matching A science unto itself

Stratified analysis Stratify analysis by score categories (e.g., quintiles)

Weighting Case weight=score; control weight=inverse of 1 minus their

score then apply sample weights in regression model Regression

Treat propensity score as model covariate with treatment

Approaches to Propensity Score Analysis

All methods should produce similar results What if there are differences?

Figure out why Present the best analysis (i.e., the one perceived

to be most accurate)

Practical Considerations

Determine area under the ROC curve for propensity score Rough rule of thumb, perhaps 0.7-0.9 is ok Very high values suggest non-overlap of

distribution of propensity scores between subjects Visually compare propensity score

distributions

Distribution of Propensity Scores

Propensity Score

Quintile

Chest tube

VATS

1 23% 6%

2 21% 16%

3 27% 24%

4 12% 16%

5 17% 38%

AUC = 0.70

Distribution of Propensity Scores

Propensity Score

Quintile

Chest tube

VATS

1 23% 6%

2 21% 16%

3 27% 24%

4 12% 16%

5 17% 38%

Poor overlap of propensity scores between the 2 groups at the extreme quintiles Restriction Matching Stratified analysis Weighting Regression

Matched vs. Unmatched Example

Covariate All VATS

(N=50)

All TT (N=714)

Matched TT

(N=345)

Winter 42% 38%* 44%**

Spring 36% 22% 35%

Summer 2% 14% 2%

Fall 20% 26% 19%

P-value - 0.02 0.99

Total Hospital Charges: VATS vs. Chest Tube

Method* Coefficient 95% CI P-value

Multivariable -0.14 -0.36 to 0.08 0.225

Restriction -0.18 -0.46 to 0.11 0.217

Matching** 0.004 -0.23 to 0.23 0.972

Regression -0.15 -0.39 to 0.08 0.191

*Multivariable model included age, race, sex, season, asthma, steroids, fibrinolysis, and empiric vancomycin receipt. Propensity score created using all of these variables.

**48 VATS patients matched with 7 patients, 1 matched with 5, 1 matched with 4

Propensity Analysis

Bottom line: VATS does not cost more than chest tube placement despite higher physician charges and additional operating room charges

Can We Simplify the Management of Complicated

Pneumonia in Children?

What we think we know

Early intervention reduces duration of hospitalization

Compared with chest tube placement, VATS Modestly decreases LOS Substantially decreases repeat procedures Does not cost more

Chemical fibrinolysis does not affect key outcomes

What we don’t know

Short-term outcomes Affect of various procedures on frequency of local,

systemic and metastatic complications

Long-term outcomes Correlation with short-term outcomes Impact of Impact of early vs. late intervention Impact of early VATS vs. tube thoracostomy

Impact of changing epidemiology on short- and long-term outcomes

Thank You

can we simplify the management of complicated pneumonia in children? samir s. shah, md, msce...

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