Devising a management algorithm for stable angina
I read this article with interest. I am currently involved in a pilot RCT of a management algorithm for stable angina, along with my colleagues, Dr. David White, Dr. Neil Drummond, and Jason Weshler. We have programmed the ACC/AHA clinical practice guideline <_1/> for the Palm Handheld computer, and are evaluating this in primary care practices.
According to Bayes'theorem, a test's usefulness is maximal when the pre-test probability of a condition is intermediate. Steurer et al found that family physicians had difficulty estimating the pre-test probability using clinical criteria (such as age), and over-estimated post-test probability in a low prevalence condition. We present the pre-test probability of angina to the clinician at the bedside, using palm-based software, and the program suggests further investigations using a Bayesian approach.
Perhaps some of our difficulties with EBM can be overcome by having easy to use software at the bedside to help us with probability calculations and evidence-based management. I hope that this trial will give us some indication as to whether this approach makes sense.
Michelle Greiver, MD, CCFP
1. Gibbons RJ, Chatterjee K, Daley J, Douglas JS, Fihn SD, Gardin JM, Grunwald MA, Levy D, Lytle BW, O'Rourke RA, Schafer WP, Williams SV. ACC/AHA/ACP-ASIM guidelines for the management of patients with chronic stable angina: executive summary and recommendations: a report of the American College of Cardiology/American Heart Association Task Force on practice guidelines (Committee on management of patients with chronic stable angina). Circulation 1999;99:2829-48
Competing interests: No competing interests