Pan Huiqing, Liu Xinran, Wang Bing, Hang Hua, Ye Sheng
Emergency Department, The Second Affiliated Hospital of Wannan Medical College, Wuhu, Anhui, People's Republic of China.
Graduate School, Wannan Medical College, Wuhu, Anhui, People's Republic of China.
Int J Gen Med. 2025 Apr 23;18:2225-2235. doi: 10.2147/IJGM.S515677. eCollection 2025.
Prolonged hospital length of stay (PLOS) is associated with adverse outcomes, including increased healthcare costs, higher risk of complications, and increased mortality. This study aimed to investigate the relationship between PLOS and mortality among patients hospitalized in internal medicine wards and to develop a nomogram to predict the risk of death in this patient population.
This retrospective study included patients hospitalized for more than 30 days in internal medicine wards between January 1, 2022, and December 31, 2022. Multivariate logistic regression analysis was used to identify independent risk factors for in-hospital mortality. The nomogram was constructed based on the independent factors. Calibration curves and receiver operating characteristic (ROC) curves were used to evaluate the predictive performance of the nomogram, and decision curve analysis (DCA) was conducted to assess its clinical utility.
A total of 1042 patients were included in this study, resulting in a mortality rate of 10.17%. Multivariate logistic regression analysis showed that age (=1.043, 95% CI: 1.026-1.061, <0.001), tumor (=2.274, 95% CI: 1.441-3.589, <0.001), blood transfusion (=4.667, 95% CI: 2.932-7.427, <0.001), ADL score (=0.966, 95% CI: 0.952-0.981, <0.001) and MNA-SF score (=0.825, 95% CI: 0.760-0.895, <0.001) as independent risk factors for mortality among patients hospitalized in internal medicine wards. The nomogram constructed using these factors demonstrated well discriminatory ability, with an AUC of 0.803 (95% CI: 0.761-0.846). Decision curve analysis further validated the clinical utility of the nomogram, highlighting its potential to improve risk assessment and guide clinical decision-making.
This nomogram effectively evaluates the risk of death for prolonged hospitalization of patients in internal medicine wards and holds significant potential for promotion in clinical practice.
住院时间延长（PLOS）与不良结局相关，包括医疗费用增加、并发症风险升高和死亡率增加。本研究旨在调查内科病房住院患者的PLOS与死亡率之间的关系，并开发一种列线图以预测该患者群体的死亡风险。
这项回顾性研究纳入了2022年1月1日至2022年12月31日期间在内科病房住院超过30天的患者。采用多因素logistic回归分析确定院内死亡的独立危险因素。基于这些独立因素构建列线图。使用校准曲线和受试者工作特征（ROC）曲线评估列线图的预测性能，并进行决策曲线分析（DCA）以评估其临床实用性。
本研究共纳入1042例患者，死亡率为10.17%。多因素logistic回归分析显示，年龄（=1.043，95%CI：1.026 - 1.061，<0.001）、肿瘤（=2.274，95%CI：1.441 - 3.589，<0.001）、输血（=4.667，95%CI：2.932 - 7.427，<0.001）、日常生活活动能力（ADL）评分（=0.966，95%CI：0.952 - 0.981，<0.001）和微型营养评定简表（MNA - SF）评分（=0.825，95%CI：0.760 - 0.895，<0.001）是内科病房住院患者死亡的独立危险因素。使用这些因素构建的列线图显示出良好的区分能力，曲线下面积（AUC）为0.803（95%CI：0.761 - 0.846）。决策曲线分析进一步验证了列线图的临床实用性，突出了其在改善风险评估和指导临床决策方面的潜力。
该列线图有效地评估内科病房长期住院患者的死亡风险，在临床实践中具有显著的推广潜力。
