Evidence map›Paper›PMID 41798300›Full record

ArticleInternational journal of general medicine2026

Cholesterol-to-Lymphocyte Ratio as a Predictor of 1-Year Unplanned Readmission in Patients with Coronary Artery Disease and Type 2 Diabetes Mellitus: A Retrospective Cohort Study.

Yumin Wu, Chaozhong Luo, Juan Du, Changjiang Zhang

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Article in International journal of general medicine, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

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4 · The record

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5 · Who and what money

Authors and funding

4 authors.

Yumin WuDepartment of Cardiology, Minda Hospital of Hubei Minzu University, Enshi, Hubei, People's Republic of China.
Chaozhong LuoDepartment of Cardiology, Minda Hospital of Hubei Minzu University, Enshi, Hubei, People's Republic of China.
Juan DuDepartment of Cardiology, Minda Hospital of Hubei Minzu University, Enshi, Hubei, People's Republic of China.
Changjiang ZhangDepartment of Cardiology, Minda Hospital of Hubei Minzu University, Enshi, Hubei, People's Republic of China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Patients with coronary artery disease (CAD) and type 2 diabetes mellitus (T2DM) face a markedly increased risk of unplanned readmission due to metabolic disturbances and chronic inflammation. The cholesterol-to-lymphocyte ratio (CLR), reflecting both dyslipidemia and inflammatory status, may serve as a useful marker for risk stratification. This study aimed to evaluate the predictive value of CLR for 1-year unplanned readmission in CAD patients with T2DM. Methods: We conducted a single-center retrospective cohort study of patients hospitalized from January to December 2023 who were diagnosed with CAD and T2DM by coronary angiography. Demographic characteristics, comorbidities, medication use, and laboratory findings were collected, and CLR was calculated. Least absolute shrinkage and selection operator (LASSO) regression was applied to identify key predictors. Logistic regression, multilayer perceptron (MLP), and extreme gradient boosting (XGBoost) models were developed to assess predictive performance. Model discrimination and calibration were evaluated using AUC, accuracy, sensitivity, specificity, and calibration curves. Variable importance was further explored with SHAP value analysis. Results: A total of 973 patients were included, comprising 769 without readmission (NRG) and 204 with readmission (RG). CLR was significantly higher in the RG group (3.63 vs 3.07, P < 0.001). Six predictors were selected by LASSO: sex, age, atrial fibrillation, β-blocker use, oral anticoagulant use, and CLR. Among the models, XGBoost achieved the best performance in the test set (AUC = 0.81, accuracy = 0.72) with good calibration. SHAP analysis identified CLR as the most influential variable (mean absolute SHAP = 0.42), contributing most strongly to readmission risk. Regular outpatient use of β-blockers and oral anticoagulants was protective, while atrial fibrillation, younger age, and female sex were associated with increased risk. Conclusion: CLR showed a moderate ability to assist risk prediction of 1-year unplanned readmission in patients with CAD and T2DM in this exploratory single-center study. Further external validation is warranted.

Indexed as

cholesterol-to-lymphocyte ratiocoronary artery diseasereadmissiontype 2 diabetes mellitusXGBoost

Identifiers

PMID41798300
PMCPMC12967091

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.