Derivation and Validation of Risk Prediction Models for Cardiovascular and Kidney Outcomes of Non‐ST‐Segment–Elevation Acute Coronary Syndrome in Patients With Chronic Kidney Disease

BACKGROUND: Patients with chronic kidney disease are at high risk of adverse outcomes after acute coronary syndrome (ACS) and need optimized treatment decisions. We derived and validated a series of risk models for predicting 1-year mortality, readmission for myocardial infarction, and progression to kidney failure following ACS. METHODS: The development cohort included adults with chronic kidney disease who had an admission for non-ST-segment-elevation ACS, in Alberta, Canada between April 1, 2004 and March 31, 2017. Cox proportional hazard and Fine and Gray competing risk models were externally validated and updated in a temporally distinct cohort of patients in Alberta and a geographically distinct cohort of patients with chronic kidney disease and ACS in British Columbia, Canada. RESULTS: The derivation cohort included 11 980 patients, the temporal validation cohort 4204, and the geographic validation cohort 1787. All models showed comparable discrimination and calibration in the temporal validation cohort; comparable model performance was achieved in the geographic validation cohort after updating. In the temporal and geographic validation cohorts, respectively, discrimination was very good for kidney failure (C-indexes, 0.93 [95% CI, 0.89-0.97] and 0.80 [95% CI, 0.78-0.82]), and modest for mortality (0.77 [95% CI, 0.75-0.78] and 0.71 [95% CI, 0.69-0.73]), and readmission for myocardial infarction (0.65 [95% CI, 0.62-0.67] and 0.57 [95% CI, 0.53-0.62]). All models were well calibrated after updating. CONCLUSIONS: We have developed, validated, and updated risk models for cardiac and renal outcomes in patients with chronic kidney disease and ACS, which can help facilitate shared decision-making surrounding diagnostic testing, treatment, and monitoring of these patients.