Ruling out coronary artery disease in primary care: development and validation of a simple prediction rule.
BACKGROUND
Chest pain can be caused by various conditions, with life-threatening cardiac disease being of greatest concern. Prediction scores to rule out coronary artery disease have been developed for use in emergency settings. We developed and validated a simple prediction rule for use in primary care.


METHODS
We conducted a cross-sectional diagnostic study in 74 primary care practices in Germany. Primary care physicians recruited all consecutive patients who presented with chest pain (n = 1249) and recorded symptoms and findings for each patient (derivation cohort). An independent expert panel reviewed follow-up data obtained at six weeks and six months on symptoms, investigations, hospital admissions and medications to determine the presence or absence of coronary artery disease. Adjusted odds ratios of relevant variables were used to develop a prediction rule. We calculated measures of diagnostic accuracy for different cut-off values for the prediction scores using data derived from another prospective primary care study (validation cohort).


RESULTS
The prediction rule contained five determinants (age/sex, known vascular disease, patient assumes pain is of cardiac origin, pain is worse during exercise, and pain is not reproducible by palpation), with the score ranging from 0 to 5 points. The area under the curve (receiver operating characteristic curve) was 0.87 (95% confidence interval [CI] 0.83-0.91) for the derivation cohort and 0.90 (95% CI 0.87-0.93) for the validation cohort. The best overall discrimination was with a cut-off value of 3 (positive result 3-5 points; negative result <or= 2 points), which had a sensitivity of 87.1% (95% CI 79.9%-94.2%) and a specificity of 80.8% (77.6%-83.9%).


CONCLUSIONS
The prediction rule for coronary artery disease in primary care proved to be robust in the validation cohort. It can help to rule out coronary artery disease in patients presenting with chest pain in primary care.
Bösner
Stefan
S
Department of General Practice and Family Medicine, University of Marburg, D-35032 Marburg, Germany. boesner@staff.uni-marburg.de
Haasenritter
Jörg
J
Becker
Annette
A
Karatolios
Konstantinos
K
Vaucher
Paul
P
Gencer
Baris
B
Herzig
Lilli
L
Heinzel-Gutenbrunner
Monika
M
Schaefer
Juergen R
JR
Abu Hani
Maren
M
Keller
Heidi
H
Sönnichsen
Andreas C
AC
Baum
Erika
E
Donner-Banzhoff
Norbert
N
D000293:Adolescent; D000367:Age Factors; D000368:Aged; D000369:Aged, 80 and over; D002637:Chest Pain / Q000175:diagnosis / Q000209:etiology; D002648:Child; D016001:Confidence Intervals; D003324:Coronary Artery Disease / Q000150:complications / Q000175:diagnosis*; D003430:Cross-Sectional Studies; D005260:Female; D005858:Germany; D006801:Humans; D016015:Logistic Models; D008297:Male; D008875:Middle Aged; D016017:Odds Ratio; D011237:Predictive Value of Tests; D011320:Primary Health Care / Q000379:methods*; D012372:ROC Curve; D012307:Risk Factors; D012680:Sensitivity and Specificity; D012720:Severity of Illness Index; D012737:Sex Factors; D055815:Young Adult