Establishment and validation of an in-hospital mortality risk prediction model for coronary heart disease and chronic kidney disease

Abstract

Objective To explore the risk factors of in-hospital death in patients with coronary artery disease (CAD) complicated with chronic kidney disease (CKD), and establish a mortality risk prediction model and verify its predictive efficacy. Methods The data of CAD patients with CKD diagnosed by Medical Information Mart for Intensive Care Ⅳ (MIMIC-Ⅳ) from 2008 to 2019 were collected and retrospectively analyzed. The data of 1 609 patients were divided into the modeling group (1 126 cases) and the internal validation group (483 cases) in a ratio of 7 ∶3. The in-hospital death was used as the outcome event. The variables were screened by univariate and multivariate logistic regression analyses, and a nomogram for predicting the risk of in-hospital death was drawn. The model was then assessed with receiver operating characteristic (ROC) curve analysis for area under curve (AUC), sensitivity and specificity, Hosmer-Lemeshow test, and calibration curve analysis, and the model was internally validated. A total of 287 patients with CAD and CKD admitted in Chongqing General Hospital from January to October 2023 were recruited as the external validation group, and the model was externally validated. Results Multivariate logistic regression analysis showed that age (OR=1.031, 95%CI: 1.015~1.049), antiplatelet drugs (OR=0.520, 95%CI: 0.342~0.792), statins (OR=0.312, 95%CI: 0.212~0.460), WBC count (OR=1.035, 95%CI: 1.016~1.057), major adverse cardiovascular events (MACE) (OR=2.417, 95%CI: 1.330~4.643), eGFR (OR=0.986, 95%CI: 0.978~0.995), phosphate (OR=1.226, 95%CI: 1.104~1.362), bicarbonate (OR=0.938, 95%CI: 900~0.977), chloride (OR=0.969, 95%CI: 0.942~0.997), and PCI or CABG (OR=0.362, 95%CI: 0.174~0.685) were significantly associated with in-hospital mortality in patients with CAD and CKD. The established nomogram showed an AUC value of 0.800 (95%CI: 0.768~0.832), a sensitivity of 0.693, and a specificity of 0.760 in prediction of in-hospital death. In the internal validation, the AUC value was 0.724 (95%CI: 0.663~0.785), the sensitivity was 0.689, and the specificity was 0.682; and the above values were 0.858 (95%CI: 0.809~0.907), 0.800, and 0.787, respectively in the external validation, indicating that the model had good predictive ability. Hosmer-Lemeshow test of the modeling group and the external validation group showed that the model had good calibration ability (Chi-square=5.975, P=0.650; Chi-square=7.891, P=0.444). Conclusion The in-hospital mortality of CAD patients with CKD is related to age, antiplatelet drugs, statins, WBC count, MACE incidence, eGFR, phosphate, bicarbonate, PCI or CABG, and chloride. Our established nomogram has a good predictive value for the risk of death in CAD patients with CKD.

Keywords

• coronary artery disease
• chronic kidney disease
• nomogram
• prediction model