Coronary Heart Disease (CHD) with renal insufficiency is a significant global health issue. This study aimed to develop and validate a predictive model for in-hospital mortality to enable early risk identification in these patients. We analyzed data from 11,830 CHD patients with renal insufficiency treated at Tongji Hospital, Huazhong University of Science and Technology, Wuhan, Hubei Province, China (1994–2023). Among 113 clinical variables, five key features—age, high-sensitivity C-reactive protein (hs-CRP), estimated glomerular filtration rate (eGFR), creatine kinase (CK), and blood urea—were selected using Recursive Feature Elimination. Six machine learning models (Random Forest, XGBoost, Decision Tree, Neural Network, Logistic Regression, and Support Vector Machine) were developed and assessed for discrimination, calibration, and clinical utility. Temporal validation was performed using data from May 16, 2023 to October 31, 2024. SHapley Additive exPlanations (SHAP) were used for model interpretation. Of the 11,830 patients, 694 (5.9 %) died during hospitalization. Among the six models, XGBoost showed the best overall performance in the test set, achieving the highest AUC (0.926), lowest Brier score (0.034), highest accuracy (0.957), and balanced sensitivity (0.381) and F1 score (0.512). Decision curve analysis confirmed its superior clinical utility. In a temporally independent validation cohort of 5983 patients, XGBoost maintained strong predictive performance (AUC = 0.901), demonstrating excellent robustness and generalizability. The XGBoost-based model accurately predicts in-hospital mortality in CHD patients with renal insufficiency, supporting early risk stratification and clinical decision-making.

Background: Atrial fibrillation (AF) is a common cardiac arrhythmia strongly associated with an imbalance between T helper 17 (Th17) cells and regulatory T cells (Treg). Secreted phosphoprotein 1 (SPP1), an immune signaling molecule implicated in AF pathogenesis, may shift the Th17/Treg cell balance in non-valvular AF (NVAF). This study aimed to explore the regulatory effects of SPP1 on the balance of Th17 and Treg cells in NVAF. Methods: Venous blood samples were collected from 58 patients with NVAF (observation group) and 58 age- and sex- matched healthy controls (control group). The serum concentrations of SPP1, along with the percentages of Treg and Th17 cells, and the levels of their associated cytokines, were measured. Correlation analysis was employed to evaluate the association between serum SPP1 levels and the Treg/Th17 cell ratio. In parallel, an experimental rat model of AF was established to investigate the expression of SPP1, related inflammatory factors, and fibrin within the left atrial tissue. Results: NVAF patients showed significantly higher serum levels of SPP1 and certain inflammatory cytokines (interleukin (IL)-17A and IL-23) than the controls. NVAF patients exhibited increased Th17 cells and elevated collagen I levels. Meanwhile, Treg cell frequency and IL-10 levels were significantly reduced compared to controls. Consequently, the Treg/Th17 ratio was significantly lower in NVAF patients. Notably, a significant inverse correlation was identified between serum SPP1 concentrations and the Treg/Th17 ratio. Consistent results were also obtained in animal models of AF, further supporting these findings. Conclusion: Our findings suggest that elevated SPP1 levels disrupt the Treg/Th17 cell balance in NVAF patients, promoting inflammation and fibrosis. These findings indicate that SPP1 represents a promising therapeutic target for the prevention and management of NVAF.

Objective To compare the long-term prognosis of patients who experienced acute ST-segment elevation myocardial infarction and underwent either late percutaneous coronary intervention (PCI) within a period of 2 days to less than 1 week or more advanced PCI within 1 week to less than 1 month. Methods We enrolled 198 patients from Tongji Hospital of Tongji Medical College, Huazhong University of Science and Technology, between June 2019 and August 2022. These patients had experienced acute ST-segment elevation myocardial infarction and underwent either late PCI or more advanced PCI. Long-term follow-up was conducted through outpatient clinic visits or telephone interviews. The study endpoints included all-cause death, nonfatal myocardial infarction, and New York Heart Association class IV heart failure. We utilized the Kaplan-Meier method to illustrate the cumulative incidence of endpoint events in both patient groups. Statistical significance in survival differences was assessed using the log-rank test. Additionally, the Cox proportional risk model was employed to analyze whether the timing of late revascularization procedures had an impact on the long-term prognosis of the patients. Results Among the 198 patients included in the study, 108 underwent late PCI, while 90 underwent more advanced PCI. The majority were male (73.74%), with an average age of 62 ± 13 years. The follow-up period averaged 20 (15, 28) months, and all patients successfully completed the follow-up process. Analysis based on the Kaplan-Meier method revealed that the incidence of all-cause death [11.1% vs. 5.6%, P=0.165], nonfatal myocardial infarction [7.4% vs. 7.8%, P=0.922], New York Heart Association class IV heart failure [2.8% vs. 3.3%, P>0.999], and the composite endpoint [18.5% vs. 14.4%, P=0.444] were not statistically significant between the late PCI and more advanced PCI groups. After adjusting for factors like left ventricular ejection fraction, renin-angiotensin system inhibitors, β-blockers, and statins, the results still indicated no statistically significant differences between the two groups in terms of rates for all-cause death, recurrent myocardial infarction, New York Heart Association class IV heart failure, and composite endpoints (P=0.05). Conclusion This study’s 20 (15, 28) months follow-up suggests that patients experiencing acute ST-segment elevation myocardial infarction have a comparable prognosis regardless of whether they underwent late or more advanced PCI.

Acute kidney injury (AKI) represents a common and potentially fatal complication in patients with traumatic shock. Early and accurate prediction of AKI pla