He Yuxin, Yuan Yuan, Tan Qingzhu, Zhang Xiao, Liu Yunyu, Xiao Minglun
Department of Medical Administration, Affiliated Banan Hospital of Chongqing Medical University, Chongqing, China.
Medical Recorods Department, Women and Children's Hospital of Chongqing Medical University, Chongqing Health Center for Women and Children, Chongqing, China.
Front Endocrinol (Lausanne). 2025 Feb 27;16:1534516. doi: 10.3389/fendo.2025.1534516. eCollection 2025.
Elderly type 2 diabetes mellitus (T2DM) patients complicated with heart failure (HF) exhibit a high rate of 30-day readmission. Predictive models have been suggested as tools for identifying high-risk patients. Thus, we aimed to develop and validate a predictive model using multicenter electronic medical records (EMRs) data to estimate the risk of 30-day readmission in elderly T2DM patients complicated with HF.
EMRs data of elderly T2DM patients complicated with HF from five tertiary hospitals, spanning 2012 to 2023, were utilized to develop and validate the 30-day readmission model. The model were evaluated using holdout data with the area under the receiver operating characteristic curve (AUROC), calibration curves, decision curve analysis (DCA), and clinical impact curves (CIC).
A total of 1899 patients were included, with 955, 409, and 535 in the derivation, internal validation, and external validation cohorts, respectively. Pulmonary infections (odds ratio [OR]: 3.816, 95% confidence interval [CI]: 2.377-6.128, < 0.001), anti-hypertensive drug use (OR: 5.536, 95% CI: 1.658-18.486, = 0.005), and neutrophil percentage-to-albumin ratio (NPAR) (OR: 1.144, 95% CI: 1.093-1.197, < 0.001) were independent predictors of 30-day readmission risk. AUROC in the derivation, internal validation, and external validation cohorts were 0.782 (95% CI: 0.737-0.826), 0.746 (95% CI: 0.654-0.838), and 0.753 (95% CI: 0.684-0.813), respectively. The calibration curve, DCA results, and CIC results indicated that the model also possessed good predictive power. Additionally, an operation interface on a web page (https://cqykdxtjt.shinyapps.io/readmission/) was created for clinical practitioners to apply.
A 30-day readmission risk prediction model was developed and externally validated. This model facilitates the targeting of interventions for elderly T2DM patients complicated with HF who are at high risk of an early readmission.
老年2型糖尿病（T2DM）合并心力衰竭（HF）患者30天再入院率较高。预测模型已被建议作为识别高危患者的工具。因此，我们旨在利用多中心电子病历（EMR）数据开发并验证一个预测模型，以估计老年T2DM合并HF患者30天再入院风险。
利用2012年至2023年期间五家三级医院的老年T2DM合并HF患者的EMR数据来开发和验证30天再入院模型。使用保留数据通过受试者操作特征曲线下面积（AUROC）、校准曲线、决策曲线分析（DCA）和临床影响曲线（CIC）对模型进行评估。
共纳入1899例患者，分别有955例、409例和535例纳入推导队列、内部验证队列和外部验证队列。肺部感染（比值比[OR]：3.816，95%置信区间[CI]：2.377 - 6.128，P < 0.001）、使用抗高血压药物（OR：5.536，95% CI：1.658 - 18.486，P = 0.005）和中性粒细胞百分比与白蛋白比值（NPAR）（OR：1.144，95% CI：1.093 - 1.197，P < 0.001）是30天再入院风险的独立预测因素。推导队列、内部验证队列和外部验证队列的AUROC分别为0.782（95% CI：0.737 - 0.826）、0.746（95% CI：0.654 - 0.838）和0.753（95% CI：0.684 - 0.813）。校准曲线、DCA结果和CIC结果表明该模型也具有良好的预测能力。此外，还创建了一个网页操作界面（https://cqykdxtjt.shinyapps.io/readmission/）供临床医生应用。
开发并外部验证了一个30天再入院风险预测模型。该模型有助于针对有早期再入院高风险的老年T2DM合并HF患者进行干预。
