The role of frailty risk for fracture-related hospital readmission and mortality after a hip fracture

医学 髋部骨折 危险系数 回顾性队列研究 置信区间 队列研究 比例危险模型 急诊医学 内科学 骨质疏松症
作者
Seigo Mitsutake,Zhisheng Sa,Janet C. Long,Jeffrey Braithwaite,Jean‐Frédéric Lévesque,Diane Watson,Jacqueline Close,Rebecca Mitchell
出处
期刊:Archives of Gerontology and Geriatrics [Elsevier BV]
卷期号:117: 105264-105264 被引量:4
标识
DOI:10.1016/j.archger.2023.105264
摘要

Frailty risk estimated using hospital administrative data may provide a useful clinical tool to identify older hip fracture patients at-risk of fracture-related readmissions and mortality. This study examined hip fracture hospitalisation temporal trends and explore the role of frailty risk in fracture-related readmission and mortality. This retrospective cohort study was conducted using linked hospital admission and mortality data in New South Wales, Australia. Patients aged ≥65 years were admitted after a hip fracture between 2014 and 2021 for temporal trends and those admitted and discharged after a hip fracture in 2014–2018 for fracture-related readmission. The Hospital Frailty Risk Score was estimated, and patients were followed for at least 36 months after discharge. A semi-competing risk analysis was used to examine the associations of frailty with fracture-related readmission and/or mortality. Hip fracture hospitalisation rate was 472 per 100,000 and declined by 2.9 % (95 % confidence intervals (CI): −3.7 to −2.1) annually. Amongst 28,567 patients, 9.8 % were identified with low frailty risk, 39.4 %, intermediate frailty risk, and 50.6 % with high frailty risk. Patients with intermediate or high frailty risk had a higher chance of fracture-related readmission (Hazard ratios (HR): 1.33, 95 %CI: 1.21–1.47, HR: 1.65, 95 %CI: 1.49–1.83), death (HR: 1.50, 95 %CI: 1.38–1.63, HR: 1.80, 95 %CI: 1.65–1.96) and death post fracture-related readmission (HR: 1.32, 95 %CI: 1.12–1.56, HR: 1.56, 95 %CI: 1.32–1.84) than those with low frailty risk. It appears that frailty risk estimated using hospital administrative data can contribute to identify patients who could benefit from targeted interventions to prevent further fractures.
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