Maggie McNally, James Curtain, Kirsty O’Brien, Borislav D Dimitrov, and Tom Fahey

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 O’Brien, Borislav D Dimitrov, and Tom Fahey

2. 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

3. 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

4. Ottawa Ankle Rule: an example of a CPR

5. 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 DBP≤60) 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

7. Studies included in meta-analysis (n=13)

8. 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

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

10. Results

11. CRB-65 Confusion Respiratory rate ≥ 30/min Blood pressure (SBP≤ 90 or DBP≤60) Age ≥ 65 0 1 or 2 3 or 4 Low Risk mortality 1.2% Intermediate Risk mortality 8.13% High Risk mortality 31%

12. 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)

13. CRB-65 Confusion Respiratory rate ≥ 30/min Blood pressure (SBP≤ 90 or DBP≤60) 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)

15. CRB-65 Confusion Respiratory rate ≥ 30/min Blood pressure (SBP≤ 90 or DBP≤60) Age ≥ 65 0 1 or 2 3 or 4 Low Risk mortality 1.2% Intermediate Risk mortality 8.13% High Risk mortality 31%

16. 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)

17. Conclusions

18. Hospital Based Patients Confusion Respiratory rate ≥ 30/min Blood pressure (SBP≤ 90 or DBP≤60) Age ≥ 65 0 1 or 2 3 or 4 Low Risk mortality 1.2% Intermediate Risk mortality 8.13% High Risk mortality 31%

19. Community Based Patients • General trend towards over-prediction • However, • Low cohort numbers • Low event numbers

20. 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