Predicting severity of pneumonia in general practice: a meta-analysis of the CRB-65 criteria.

1
HRB Centre for Primary Care Research Department
of General Practice
Royal College of Surgeons in Ireland
Predicting severity of pneumonia in general
practice a meta-analysis of the CRB-65 criteria
Maggie McNally, James Curtain, Kirsty OBrien,
Borislav D Dimitrov, and Tom Fahey
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Outline

• What is a clinical prediction rule?
• Assessment of clinical prediction rules
• CRB-65 a clinical prediction rule
• Statistical methods in meta-analysis
• Results
• Conclusions
• Future work

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Clinical Prediction Rule

• Clinical tool that quantifies contribution of
• History
• Examination
• Diagnostic tests
• Stratify patients according to probability of
  having target disorder
• Outcome can be in terms of diagnosis, prognosis,
  referral or treatment

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Ottawa Ankle Rule an example of a CPR
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Stages of assessment of a Clinical Prediction
Rule
Step 1 Derivation identification of factors with
predictive power
Step 2 Validation evidence of reproducible
accuracy Narrow Broad
Step 3 Impact Analysis evidence of rule changing
behaviour and improving outcome
Level of Evidence
4
3
2
1
6
CRB-65 a clinical prediction rule
Confusion Respiratory rate 30/min Blood
pressure (SBP 90 or DBP60) Age 65
1 or 2
0
3 or 4
Low Risk mortality 1.2
Intermediate Risk mortality 8.13
High Risk mortality 31
Likely suitable for home treatment
Consider hospital referral
Urgent hospital admission
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Studies included in meta-analysis (n13)
study setting participants
Barlow et al 2007 inpatients 419
Bauer et al 2006 outpatients inpatients 1959
Bont et al 2008 outpatients 314
Buising et al 2007 emergency department 740
Capelastegui et al 2006 outpatients inpatients 1776
Chalmers et al 2008 inpatients 1007
Kruger et al 2008 inpatients 1404
Man et al 2007 inpatients 1016
Menendez et al 2009 inpatients 447
Myint et al 2006 inpatients 192
Schaaf et al 2007 inpatients 105
Schuetz et al 2008 emergency department 373
Zuberi et al 2008 inpatients 137
TOTAL TOTAL 9889
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Level of evidence for CRB-65
Step 1 Derivation identification of factors with
predictive power
Step 2 Validation evidence of reproducible
accuracy Narrow Broad
Step 3 Impact Analysis evidence of rule changing
behaviour and improving outcome
Level of Evidence
4
3
2
1
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Statistical Methods

• Derivation study used as predictive model
• Results presented as ratio measurement
• predicted deaths by CRB-65 rule
• observed deaths in validation study

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Results
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CRB-65
Confusion Respiratory rate 30/min Blood
pressure (SBP 90 or DBP60) Age 65
0
1 or 2
3 or 4
Low Risk mortality 1.2
Intermediate Risk mortality 8.13
High Risk mortality 31
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n 799 events 0 (0)
RR 9.63 (CI 1.23 75.63)
n 1887 events 14 (0.74)
RR 1.25 (CI 0.60 2.59)
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CRB-65
Confusion Respiratory rate 30/min Blood
pressure (SBP 90 or DBP60) Age 65
0
1 or 2
3 or 4
Low Risk mortality 1.2
Intermediate Risk mortality 8.13
High Risk mortality 31
14
n 647 events 10 (1.5)
RR 4.92 (CI 2.39 10.11)
n 5674 events 455 (8.0)
RR 0.99 (CI 0.80 1.23)
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CRB-65
Confusion Respiratory rate 30/min Blood
pressure (SBP 90 or DBP60) Age 65
0
1 or 2
3 or 4
Low Risk mortality 1.2
Intermediate Risk mortality 8.13
High Risk mortality 31
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n 26 events 5 (19.2)
RR 1.58 (CI 0.59 4.19)
n 869 events 257 (29.6)
RR 1.04 (CI 0.88 1.23)
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Conclusions
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Hospital Based Patients
Confusion Respiratory rate 30/min Blood
pressure (SBP 90 or DBP60) Age 65
0
1 or 2
3 or 4
Low Risk mortality 1.2
Intermediate Risk mortality 8.13
High Risk mortality 31
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Community Based Patients

• General trend towards over-prediction
• However,
• Low cohort numbers
• Low event numbers

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Future Work
Step 1 Derivation identification of factors with
predictive power
Step 2 Validation evidence of reproducible
accuracy Narrow Broad
Step 3 Impact Analysis evidence of rule changing
behaviour and improving outcome
Level of Evidence
4
3
2
1
21
Acknowledgements

• RCSI Research Institute
• Grainne McCabe, RCSI Library