We are currently updating our website, and will have our new version online soon. Please check back later this fall.

Mailing List

Subscribe to the KT Canada mailing list

Login

Welcome

Signup

Once you have signed up, you will receive a confirmation email with your username and password. To activate your account, follow the instructions in the email.

 

Centre for Evidence-
Based Medicine

Completed Prognosis Worksheet for Evidence-Based Geriatric Medicine

Citation

Burn J, Dennis M, Bamford J et al. Epileptic seizures after a first stroke: the Oxfordshire community stroke project. BMJ 1997;315:1582-7

Are the results of this prognosis study valid?

  1. Was a defined, representative sample of patients assembled at a common (usually early) point in the course of their disease?
    Yes - from a common point but unsure how GPs decided which stroke patients should be admitted to hospital
  2. Was patient follow-up sufficiently long and complete?
    Yes-minimum of 2 years and up to 6.5 years
  3. Were objective outcome criteria applied in a "blind" fashion?
    Patients were asked at follow-up if they had a seizure and were then assessed by a study neurologist (unsure if neurologist was blinded)
  4. If subgroups with different prognoses are identified, was there adjustment for important prognostic factors?
    Looked at different stroke types, previous history of stroke
  5. Was there validation in an independent group ("test-set") of patients?
    No

Are the valid results of this prognosis study important?

  1. How likely are the outcomes over time?
    5.7% over one year
  2. How precise are the prognostic estimates?
    95% confidence interval - 3.5 to 7.9%

If you want to calculate a Confidence Interval around the measure of Prognosis

Clinical Measure Standard Error (SE) Typical calculation of CI
Proportion (as in the rate of some prognostic event, etc) where:

the number of patients = n

the proportion of these patients who experience the event = p
sqrt((px(1-p))/n)
where p is proportion and n is number of patients
If p = 24/60 = 0.4 (or 40%) and n=60
sqrt((0.4x(1-0.4))/60)
= 0.063 (or 6.3%)

95% CI is 40% +/- 1.96 x 6.3% or 27.6% to 52.4%
n from your evidence: 675

p from your evidence: 0.057
sqrt((px(1-p))/n)
where p is proportion and n is number of patients
Your calculation:
SE = 0.009
95% CI: 5.7% ± 1.7% = 4% to 7.4%

Can you apply this valid, important evidence about prognosis in caring for your patient?

  1. Were the study patients similar to your own?
    Yes
  2. Will this evidence make a clinically important impact on your conclusions about what to offer or tell your patient?
    Yes

Additional Notes

-

Continue to CAT