Comorbidity Patterns in Older Patients Undergoing Hip Fracture Surgery: A Comorbidity Network Analysis Study.

IF 1.7 4区 医学 Q2 NURSING Clinical Nursing Research Pub Date : 2024-01-01 Epub Date: 2023-11-06 DOI:10.1177/10547738231209367
Chiyoung Lee, Sijia Wei, Eleanor S McConnell, Hideyo Tsumura, Tingzhong Michelle Xue, Wei Pan
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Abstract

Comorbidity network analysis (CNA) is a technique in which mathematical graphs encode correlations (edges) among diseases (nodes) inferred from the disease co-occurrence data of a patient group. The present study applied this network-based approach to identifying comorbidity patterns in older patients undergoing hip fracture surgery. This was a retrospective observational cohort study using electronic health records (EHR). EHR data were extracted from the one University Health System in the southeast United States. The cohort included patients aged 65 and above who had a first-time low-energy traumatic hip fracture treated surgically between October 1, 2015 and December 31, 2018 (n = 1,171). Comorbidity includes 17 diagnoses classified by the Charlson Comorbidity Index. The CNA investigated the comorbid associations among 17 diagnoses. The association strength was quantified using the observed-to-expected ratio (OER). Several network centrality measures were used to examine the importance of nodes, namely degree, strength, closeness, and betweenness centrality. A cluster detection algorithm was employed to determine specific clusters of comorbidities. Twelve diseases were significantly interconnected in the network (OER > 1, p-value < .05). The most robust associations were between metastatic carcinoma and mild liver disease, myocardial infarction and congestive heart failure, and hemi/paraplegia and cerebrovascular disease (OER > 2.5). Cerebrovascular disease, congestive heart failure, and myocardial infarction were identified as the central diseases that co-occurred with numerous other diseases. Two distinct clusters were noted, and the largest cluster comprised 10 diseases, primarily encompassing cardiometabolic and cognitive disorders. The results highlight specific patient comorbidities that could be used to guide clinical assessment, management, and targeted interventions that improve hip fracture outcomes in this patient group.

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接受髋部骨折手术的老年患者的共病模式:一项共病网络分析研究。
共病网络分析(CNA)是一种技术,其中数学图对从患者组的疾病共现数据推断出的疾病(节点)之间的相关性(边)进行编码。本研究应用这种基于网络的方法来识别接受髋部骨折手术的老年患者的共病模式。这是一项使用电子健康记录(EHR)的回顾性观察性队列研究。EHR数据来自美国东南部的一所大学卫生系统。该队列包括年龄在65岁及以上的患者,他们在2015年10月1日至2018年12月31日期间首次接受低能量创伤性髋部骨折手术治疗(n = 1171)。合并症包括根据Charlson合并症指数分类的17种诊断。CNA调查了17种诊断中的共病相关性。使用观察到的与预期的比率(OER)来量化关联强度。使用几种网络中心性度量来检验节点的重要性,即度、强度、接近度和介数中心性。采用聚类检测算法来确定合并症的特定聚类。12种疾病在网络中显著相互关联(OER > 1,p值  2.5)。脑血管病、充血性心力衰竭和心肌梗死被确定为与许多其他疾病同时发生的中心疾病。注意到两个不同的集群,最大的集群包括10种疾病,主要包括心脏代谢和认知障碍。研究结果强调了特定的患者合并症,可用于指导临床评估、管理和有针对性的干预措施,以改善该患者组的髋部骨折结果。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
CiteScore
3.40
自引率
5.90%
发文量
107
审稿时长
>12 weeks
期刊介绍: Clinical Nursing Research (CNR) is a peer-reviewed quarterly journal that addresses issues of clinical research that are meaningful to practicing nurses, providing an international forum to encourage discussion among clinical practitioners, enhance clinical practice by pinpointing potential clinical applications of the latest scholarly research, and disseminate research findings of particular interest to practicing nurses. This journal is a member of the Committee on Publication Ethics (COPE).
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