To establish a prediction model of coronary heart disease (CHD) in elderly patients with diabetes mellitus (DM) based on machine learning (ML) algorithms.

Based on the Medical Big Data Research Centre of Chinese PLA General Hospital in Beijing, China, we identified a cohort of elderly inpatients (≥ 60 years), including 10,533 patients with DM complicated with CHD and 12,634 patients with DM without CHD, from January 2008 to December 2017. We collected demographic characteristics and clinical data. After selecting the important features, we established five ML models, including extreme gradient boosting (XGBoost), random forest (RF), decision tree (DT), adaptive boosting (Adaboost) and logistic regression (LR). We compared the receiver operating characteristic curves, area under the curve (AUC) and other relevant parameters of different models and determined the optimal classification model. The model was then applied to 7447 elderly patients with DM admitted from January 2018 to December 2019 to further validate the performance of the model.

Fifteen features were selected and included in the ML model. The classification precision in the test set of the XGBoost, RF, DT, Adaboost and LR models was 0.778, 0.789, 0.753, 0.750 and 0.689, respectively; and the AUCs of the subjects were 0.851, 0.845, 0.823, 0.833 and 0.731, respectively. Applying the XGBoost model with optimal performance to a newly recruited dataset for validation, the diagnostic sensitivity, specificity, precision, and AUC were 0.792, 0.808, 0.748 and 0.880, respectively.

The XGBoost model established in the present study had certain predictive value for elderly patients with DM complicated with CHD.

To investigate the effects of sodium-glucose cotransporter 2 inhibitors (SGLT2i) on cardiovascular outcomes in elderly Chinese patients with comorbid coronary heart disease (CHD) and type 2 diabetes mellitus (T2DM).

A retrospective cohort study was conducted on 501 elderly inpatients (≥ 60 years) with comorbid CHD/T2DM in Department of Cardiovascular Medicine and Endocrinology, Chinese PLA General Hospital from January 2018 to December 2019. These patients were divided into two groups according to the administration of SGLT2i. All the demographic characteristics and clinical data were collected. Cardiovascular outcomes, including all-cause mortality, major adverse cardiovascular events (MACE), and hospitalization for heart failure (HHF), were followed up.

In the cohort, there were 167 patients in the SGLT2i group and 334 patients in the control group. In the efficacy analyses, the incidence of MACE was lower in the SGLT2i group than in the control group: 3.6% vs. 9.3% (P = 0.022). A lower risk of MACE was observed in the SGLT2i group [hazard ratio (HR) = 0.40, 95% CI: 0.17–0.95]. There was no significant difference in the incidence of all-cause mortality or HHF between the two groups. No significant difference of HR was observed for all-cause mortality (HR = 0.41, 95% CI: 0.12–1.41) or HHF (HR = 0.58, 95% CI: 0.12–2.81).

SGLT2i treatment exhibited benefits for elderly patients with comorbid CHD/T2DM with a lower risk for MACE.