Comparison of Mayo Clinic risk score and American College of Cardiology/American Heart Association lesion classification in the prediction of adverse cardiovascular outcome following percutaneous coronary interventions.
OBJECTIVE
We compared American College of Cardiology/American Heart Association (ACC/AHA) lesion classification with the recently proposed Mayo Clinic risk score to predict complications following percutaneous coronary intervention (PCI).


BACKGROUND
The ability of the ACC/AHA classification system to predict complications following PCI has been modest. With the inclusion of patient demographics, acuity of presentation, and measure of left ventricular function, models with better discriminatory accuracy are presently available.


METHODS
The Mayo Clinic risk score is constructed by adding integer scores for the presence of eight variables. We mapped the lesion-specific risk levels to a patient level by counting the number of lesions in each class (A, B1, B2, C, and unknown).


RESULTS
In 5,064 PCIs, 183 patients (4%) had the primary end point (death, Q-wave myocardial infarction, stroke, emergency coronary artery bypass graft). Of the 7,632 treated lesions, 891 (12%) were unsuccessfully treated with PCI (residual stenosis >20%). The discriminatory ability of the Mayo Clinic risk score model for prediction of the primary end point, as measured by the c-statistic, was 0.78 (95% confidence interval [CI] 0.74 to 0.81). The Mayo Clinic risk score offered significantly better risk stratification than the ACC/AHA lesion classification counts (95% CI for c-statistic difference: 0.05 to 0.15). Regarding angiographic success, the ACC/AHA lesion classification was a better system (95% CI for c-statistic difference: -0.08 to -0.03 favoring ACC/AHA classification), although its absolute ability was modest (c = 0.58).


CONCLUSIONS
Mayo Clinic risk score offers significantly better prediction for cardiovascular complications than the ACC/AHA classification. However, lesion classification by ACC/AHA classification is a better predictor for angiographic success.
Singh
Mandeep
M
Division of Cardiovascular Diseases and Internal Medicine, Rochester, Minnesota, USA. singh.mandeep@mayo.edu
Rihal
Charanjit S
CS
Lennon
Ryan J
RJ
Garratt
Kirk N
KN
Holmes
David R
DR
D000368:Aged; D015906:Angioplasty, Balloon, Coronary / Q000009:adverse effects; D017023:Coronary Angiography; D001026:Coronary Artery Bypass; D003327:Coronary Disease / Q000145:classification* / Q000000981:diagnostic imaging / Q000473:pathology / Q000628:therapy; D003331:Coronary Vessels / Q000473:pathology*; D004630:Emergencies; D005260:Female; D006801:Humans; D008297:Male; D009203:Myocardial Infarction / Q000209:etiology; D011379:Prognosis; D012307:Risk Factors; D015607:Stents; D020521:Stroke / Q000209:etiology; D017211:Treatment Failure