Up to one in three of older patients who are hospitalised develop functional decline, which is associated with sustained disability, institutionalisation and death. This study developed and validated a clinical prediction model that identifies patients who are at risk for functional decline during hospitalisation. The predictive value of the model was compared against three models that were developed for patients admitted to a general medical ward. A prospective cohort study was performed on two cardiac care units between September 2016 and June 2017. Patients aged 75 years or older were recruited on admission if they were admitted for non-surgical treatment of an acute cardiovascular disease. Hospitalisation-associated functional decline was defined as any decrease on the Katz Index of Activities of Daily Living between hospital admission and discharge. Predictors were selected based on a review of the literature and a prediction score chart was developed based on a multivariate logistic regression model. A total of 189 patients were recruited and 33% developed functional decline during hospitalisation. A score chart was developed with five predictors that were measured on hospital admission: mobility impairment = 9 points, cognitive impairment = 7 points, loss of appetite = 6 points, depressive symptoms = 5 points, use of physical restraints or having an indwelling urinary catheter = 5 points. The score chart of the developed model demonstrated good calibration and discriminated adequately (C-index = 0.75, 95% CI (0.68–0.83) and better between patients with and without functional decline (chi2 = 12.8, p = 0.005) than the three previously developed models (range of C-index = 0.65–0.68). Functional decline is a prevalent complication and can be adequately predicted on hospital admission. A score chart can be used in clinical practice to identify patients who could benefit from preventive interventions. Independent external validation is needed.

中文翻译：

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预测患有心血管疾病的心脏护理病房老年患者的住院相关功能下降：一项前瞻性队列研究

住院的老年患者中，多达三分之一的患者会出现功能下降，这与持续的残疾，机构化和死亡有关。这项研究开发并验证了一种临床预测模型，该模型可识别出住院期间存在功能下降风险的患者。该模型的预测价值与针对普通病房住院患者开发的三种模型进行了比较。在2016年9月至2017年6月之间，对两个心脏护理单元进行了一项前瞻性队列研究。如果年龄75岁或以上的患者因非手术治疗急性心血管疾病而入院，则应招募他们。与住院相关的功能下降定义为住院和出院之间日常生活活动的卡茨指数的任何下降。根据文献回顾选择预测变量，并基于多元逻辑回归模型开发预测得分表。总共招募了189例患者，其中33％的患者在住院期间出现了功能下降。制定了一个评分表，其中包括在入院时测量的五种预测指标：活动障碍= 9分，认知障碍= 7分，食欲不振= 6分，抑郁症状= 5分，使用身体约束或有导尿管留置= 5分。所开发模型的评分表显示出良好的校准效果，并且可以充分区分（C指数= 0.75，95％CI（0.68–0）。83），有无功能下降的患者之间的差异（chi2 = 12.8，p = 0.005）比以前建立的三个模型（C-指数范围= 0.65-0.68）更好。功能下降是一种普遍的并发症，可以在入院时充分预测。评分表可用于临床实践，以识别可以从预防性干预中受益的患者。需要独立的外部验证。