Transcript Factors Associated with Prolonged Length of Stay and

Can We Simplify the
Management of Complicated
Pneumonia in Children?
Samir S. Shah, MD, MSCE
Divisions of Infectious Diseases and General Pediatrics
The Children’s Hospital of Philadelphia
Departments of Pediatrics and Biostatistics and Epidemiology
University 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 PenicillinSusceptible 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


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


Does our definition exclude the sickest patients?
May limit accuracy of data for subpopulations
Insufficient data in publicly available dataset to
calculate standard errors for some subpopulations
Regional Variation in Pediatric
CAP Hospitalizations (Pennsylvania)
Gorton CP, et al. Pediatrics 2006;117:176-180
The epidemiology of
pneumonia and complicated
pneumonia is complex and
changing
Evolution of Empyema

Exudative


Fibrinopurulent



Neutrophil migration into pleural space
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
Management of Empyema

Surgical options

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
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Thoracentesis (needle aspiration)
Tube thoracostomy (+ fibrinolysis)
Video-assisted thoracoscopy*
Thoracotomy*
*Require post-procedure thoracostomy tube
Management of Empyema

No consensus on optimal initial drainage
strategy


Technique?
Timing?
Why use administrative data to
study complicated pneumonia?
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
Sonnappa et al.
Kurt et al.
Avansino et al.
Li et al.
Shah et al.
Sonnappa et al.


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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
Median LOS (days)
Tube drainage (days)
Repeat Procedures
Thoracostomy
VATS
(N=30)
(N=30)
7
8
+1 compared to VATS
17%
Kurt BA, et al. Pediatrics 2006;118:e547-e553
13%
P
0.645
0.055
?
Kurt et al.



1st randomized study of VATS vs.
thoracostomy tube drainage in U.S.
18 patients enrolled from November 2003May 2005
Groups similar in




Age & sex
Preadmission symptoms & antibiotics
Effusion size
Presence of loculation
Kurt BA, et al. Pediatrics 2006;118:e547-e553
Kurt et al.
Thoracostomy
VATS
(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
Variable
Kurt BA, et al. Pediatrics 2006;118:e547-e553
P
Key Differences

Differences



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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
Mortality
Re-intervention
Duration of hospitalization
Primary
Primary
Operative Non-operative
0%
2.5%
10.8 d
3.3%
23.5%
20.0 d
4.4 d
10.6 d
12.8 d
21.3 d
Duration of TT
Duration of antibiotics
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

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Timing of intervention
Chemical fibrinolysis
Empiric antibiotic therapy
Where do things stand?

Randomized studies
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Pooled analyses

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Small & single center
Multicenter studies difficult to conduct because
prevailing personal & institutional dogmas
Few high quality studies
Administrative data

Seriously?
Li et al.
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
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 ST. Arch Pediatr Adolesc Med 2008;162:44-48
Li et al.
Procedure
LOS
Adjusted Change
NM
13.6 days
Reference
POM
9.8 days
-4.3 (-6.4 to -2.3)
Overall (n=1173)
Empyema as primary diagnosis (n=362)
NM
10.3 days
Reference
POM
8.9 days
-1.7 (-0.4 to -3.0)
Li ST. Arch Pediatr Adolesc Med 2008;162:44-48
Li et al. - Limitations

ICD-9 codes incomplete


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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)


Inclusions





Inpatient data from 27 not-for-profit, tertiary care, U.S.
children’s hospitals
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 Drainage
Late Drainage
No Drainage
34% (N=961)
29% (N=829)
37% (N=1,072)
Shah SS. Arch Pediatr Adolesc Med 2008;162:675-681
Shah et al. - Initial Procedure
Procedure
Chest tube
VATS
Thoracotomy
No. (%)
714 (74.3)
50 (5.2)
197 (20.5)
Shah SS. Arch Pediatr Adolesc Med 2008;162:675-681
Shah et al. - Procedure
Variation by Hospital
Thoracotomy
100%
%
O 80%
F
VATS
P 60%
R
O
C 40%
E
D
U 20%
R
E
S 0%
Chest
Tube
Hospital
Shah et al. - Variation in LOS
by Hospital*
16
M
E
D
I
A
N
L
O
S
14
12
10
8
6
4
2
0
Hospital
*7% of patients had a LOS >28 days
Shah et al. - Change in LOS
Variable
Procedure
Chest tube
VATS
Thoracotomy
Adjusted Change
in LOS*
(baseline=13.29 d)
P-value
Reference
…
-2.66 d
-1.26 d
0.006
0.439
*Also adjusted for race, asthma diagnosis, receipt of systemic
corticosteroids, empiric vancomycin therapy, and fibrinolysis
Shah SS. Arch Pediatr Adolesc Med 2008;162:675-681
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 SS. Arch Pediatr Adolesc Med 2008;162:675-681
Shah et al. - Variation in
Repeat Procedures by Hospital
R
E
P
E
A
T
80%
P
R
O
C
E
D
U
R
E
40%
70%
60%
50%
30%
20%
10%
0%
Hospital
Shah SS. Arch Pediatr Adolesc Med 2008;162:675-681
Shah et al. - Repeat Procedure
Variable
Adjusted Odds Ratio
(95% CI)*
P-value
Reference
…
0.16 (0.06- 0.42)
0.60 (0.31- 1.16)
<0.001
0.133
Procedure
Chest tube
VATS
Thoracotomy
*Also adjusted for race, asthma diagnosis, receipt of systemic corticosteriods,
empiric vancomycin therapy, and fibrinolysis
Shah SS. Arch Pediatr Adolesc Med 2008;162:675-681
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
Shah SS. Arch Pediatr Adolesc Med 2008;162:675-681
But which strategy is more costeffective?
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)


Inclusions





Inpatient data from 27 not-for-profit, tertiary care, U.S.
children’s hospitals
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. – Resource
Utilization (Unadjusted data)
Procedure
Total
Charges
Pharmacy Imaging
Charges 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
2.) Indications for Propensity
Scores

Useful for matching subjects


Matching on propensity score outperforms other
matching strategies with many covariates
Balance achieved will mimic randomization (for
measured variables)
3.) Indications for Propensity
Scores

Improved estimation with few outcomes

Reliable estimates not possible with multivariable
modeling when there are many covariates and
few outcomes
4.) Indications for Propensity
Scores

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
5.) Indications for Propensity
Scores

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 nonoverlap
#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


Matching


Stratify analysis by score categories (e.g., quintiles)
Weighting


A science unto itself
Stratified analysis


Restrict analysis to participants with sufficient overlap in
scores
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
Spring
Summer
Fall
42%
36%
2%
20%
38%*
22%
14%
26%
44%**
35%
2%
19%
P-value
-
0.02
0.99
Total Hospital Charges: VATS
vs. Chest Tube
Method*
Coefficient
95% CI
P-value
Multivariable
Restriction
-0.14
-0.18
-0.36 to 0.08
-0.46 to 0.11
0.225
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


Long-term outcomes




Affect of various procedures on frequency of local,
systemic and metastatic complications
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