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成年糖尿病患者 1 年再入院频率的预测因素。

Predictors of frequency of 1-year readmission in adult patients with diabetes.

机构信息

Saw Swee Hock School of Public Health, National University of Singapore, Singapore, Singapore.

Health and Social Sciences, Singapore Institute of Technology, Singapore, Singapore.

出版信息

Sci Rep. 2023 Dec 16;13(1):22389. doi: 10.1038/s41598-023-47339-7.

Abstract

Diabetes mellitus (DM) is the third most common chronic condition associated with frequent hospital readmissions. Predictors of the number of readmissions within 1 year among patients with DM are less often studied compared with those of 30-day readmission. This study aims to identify predictors of number of readmissions within 1 year amongst adult patients with DM and compare different count regression models with respect to model fit. Data from 2008 to 2015 were extracted from the electronic medical records of the National University Hospital, Singapore. Inpatients aged ≥ 18 years at the time of index admission with a hospital stay > 24 h and survived until discharge were included. The zero-inflated negative binomial (ZINB) model was fitted and compared with three other count models (Poisson, zero-inflated Poisson and negative binomial) in terms of predicted probabilities, misclassification proportions and model fit. Adjusted for other variables in the model, the expected number of readmissions was 1.42 (95% confidence interval [CI] 1.07 to 1.90) for peripheral vascular disease, 1.60 (95% CI 1.34 to 1.92) for renal disease and 2.37 (95% CI 1.67 to 3.35) for Singapore residency. Number of emergency visits, number of drugs and age were other significant predictors, with length of stay fitted as a zero-inflated component. Model comparisons suggested that ZINB provides better prediction than the other three count models. The ZINB model identified five patient characteristics and two comorbidities associated with number of readmissions. It outperformed other count regression models but should be validated before clinical adoption.

摘要

糖尿病(DM)是与频繁住院再入院相关的第三大常见慢性疾病。与 30 天再入院相比,预测 DM 患者一年内再入院次数的预测因素研究较少。本研究旨在确定成年糖尿病患者一年内再入院次数的预测因素,并比较不同计数回归模型的拟合优度。数据来自新加坡国立大学医院的电子病历,时间为 2008 年至 2015 年。纳入标准为索引入院时年龄≥18 岁、住院时间>24 小时且存活至出院的住院患者。拟合零膨胀负二项式(ZINB)模型,并与其他三种计数模型(泊松、零膨胀泊松和负二项式)在预测概率、分类错误比例和模型拟合方面进行比较。在模型中调整其他变量后,外周血管疾病的预期再入院次数为 1.42(95%置信区间 [CI] 1.07 至 1.90),肾脏疾病为 1.60(95% CI 1.34 至 1.92),新加坡居民为 2.37(95% CI 1.67 至 3.35)。急诊次数、药物种类和年龄也是其他重要的预测因素,住院时间作为零膨胀部分拟合。模型比较表明,ZINB 提供了比其他三种计数模型更好的预测。ZINB 模型确定了与再入院次数相关的五个患者特征和两种合并症。它优于其他计数回归模型,但在临床应用前应进行验证。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e5e2/10725424/38a917010f13/41598_2023_47339_Fig1_HTML.jpg

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