slide1 n.
Download
Skip this Video
Download Presentation
Maggie McNally, James Curtain, Kirsty O’Brien, Borislav D Dimitrov, and Tom Fahey

Loading in 2 Seconds...

play fullscreen
1 / 21

Maggie McNally, James Curtain, Kirsty O’Brien, Borislav D Dimitrov, and Tom Fahey - PowerPoint PPT Presentation


  • 71 Views
  • Uploaded on

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. Outline.

loader
I am the owner, or an agent authorized to act on behalf of the owner, of the copyrighted work described.
capcha
Download Presentation

PowerPoint Slideshow about 'Maggie McNally, James Curtain, Kirsty O’Brien, Borislav D Dimitrov, and Tom Fahey' - rene


Download Now An Image/Link below is provided (as is) to download presentation

Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author.While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server.


- - - - - - - - - - - - - - - - - - - - - - - - - - E N D - - - - - - - - - - - - - - - - - - - - - - - - - -
Presentation Transcript
slide1

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

outline
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
clinical prediction rule
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
stages of assessment of a clinical prediction rule
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

crb 65 a clinical prediction rule
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

level of evidence for crb 65
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

statistical methods
Statistical Methods
  • Derivation study used as predictive model
  • Results presented as ratio measurement:

predicted deaths by CRB-65 rule

observed deaths in validation study

crb 65
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%

slide12

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)

crb 651
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%

slide14

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)

crb 652
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%

slide16

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)

hospital based patients
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%

community based patients
Community Based Patients
  • General trend towards over-prediction
  • However,
    • Low cohort numbers
    • Low event numbers
future work
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

acknowledgements
Acknowledgements
  • RCSI Research Institute
  • Grainne McCabe, RCSI Library