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Physician Prediction Of 1-Year Mortality In The Cardiac Catheterization Laboratory: Comparison To A Validated Risk Score

CORONARY ARTERY DISEASE(2021)

Cited 2|Views60
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Abstract
Background Physician perception of procedural risk and clinical outcome can affect revascularization decision making. Public reporting of percutaneous coronary intervention outcomes accentuates the need for accuracy in risk prediction in order to avoid a treatment paradox of undertreating the highest risk patients. Our study compares a validated risk score to physician prediction (PP) of 1-year mortality based on clinical impression at the time of invasive angiography. Methods and results We performed a cohort study between August 2015 and May 2018 to determine the discriminative accuracy of interventional cardiologists on one-year mortality of the treated patient. PP of one-year mortality was compared to the New York State Percutaneous Coronary Intervention Reporting System (NYPCIRS) score in predicting mortality. Three thousand seven hundred ninety-two patients were followed with a median follow-up period of 14.4 months (interquartile range 12.4-18.1 months) and 165 patients (4.4%) died within one-year. PP of mortality was associated with one-year mortality with a hazard ratio of 8.78 (95% confidence interval 5.24-14.71, P < 0.0001). Clinical presentation in the form of cardiogenic shock, return of spontaneous circulation, and liver and renal dysfunction were associated with PP. Diagnostic accuracy and specificity were improved in PP compared to NYPCIRS. The combination of PP to NYPCIRS improved the overall c-statistic and diagnostic yield. Conclusion PP appears to be especially specific and accurate for prediction of mortality compared to NYPCIRS though it lacks sensitivity. Furthermore, the combination of PP with NYPCIRS improved the c-statistic and diagnostic yield. Overall, the utility of PP with an objective risk score improves the diagnostic accuracy of mortality prediction.
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Key words
percutaneous coronary intervention complications, risk stratification
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