Frailty Assessment in Hospitalized Older Adults Using the Electronic Health Record.
Frailty Assessment in Hospitalized Older Adults Using the Electronic Health Record.
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DOI：
10.1177/1099800416679730
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发表时间：
2017-03
影响因子：
2.5
通讯作者：
Whitson HE
中科院分区：
文献类型：
--
作者：
Lekan DA;Wallace DC;McCoy TP;Hu J;Silva SG;Whitson HE
虚弱是一种生理储备减少和多个生理系统失调的临床综合征，与不良后果的风险增加相关。这项回顾性、横断面、相关性研究的目的是通过生物心理社会衰弱评估来描述三级甲等医院收治的老年人的衰弱特征，并确定衰弱与院内死亡率和 30 天再住院时间之间的关系。样本包括278名医疗单位收治的≥55岁患者。使用电子健康记录 (EHR) 中症状、综合征和状况的临床数据以及四种血清生物标志物的实验室数据来确定虚弱程度。根据 16 个风险因素创建了衰弱风险评分 (FRS)，并检查了 FRS 与结果之间的关系。样本的平均年龄为 70.2 岁，平均 FRS 为 9.4 (SD, 2.2)。 FRS 增加与死亡风险增加显着相关（3 天≤住院时间 (LOS) ≤ 7 天的风险比 = 1.77 –.27），但取决于 LOS (p < .001)。对于那些未在医院死亡的患者，虚弱与再住院有一定关系（调整后的比值比 = 1.18，p = 0.086，曲线下面积 [AUC] = 0.66，AUC 的 95% 置信区间 = [0.57, 0.76]）。 EHR 中的临床数据可用于衰弱评估。信息学可以促进数据聚合和决策支持。由于虚弱是可以预防和治疗的，因此早期检测对于提供量身定制的干预措施和最佳的患者治疗效果至关重要。
Frailty, a clinical syndrome of decreased physiologic reserve and dysregulation in multiple physiologic systems, is associated with increased risk for adverse outcomes. The aim of this retrospective, cross-sectional, correlational study was to characterize frailty in older adults admitted to a tertiary-care hospital using a biopsychosocial frailty assessment and to determine associations between frailty and time to in-hospital mortality and 30-day rehospitalization. The sample included 278 patients ≥ 55 years old admitted to medicine units. Frailty was determined using clinical data from the electronic health record (EHR) for symptoms, syndromes, and conditions and laboratory data for four serum biomarkers. A frailty risk score (FRS) was created from 16 risk factors, and relationships between the FRS and outcomes were examined. The mean age of the sample was 70.2 years and mean FRS was 9.4 (SD, 2.2). Increased FRS was significantly associated with increased risk of death (hazard ratio = 1.77 –.27 for 3 days ≤ length of stay (LOS) ≤ 7 days), but depended upon LOS (p < .001). Frailty was marginally associated with rehospitalization for those who did not die in hospital (adjusted odds ratio = 1.18, p = .086, area under the curve [AUC] = 0.66, 95% confidence interval for AUC = [0.57, 0.76]). Clinical data in the EHR can be used for frailty assessment. Informatics may facilitate data aggregation and decision support. Because frailty is potentially preventable and treatable, early detection is crucial to delivery of tailored interventions and optimal patient outcomes.
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影响因子：
2.9
作者：
Chamberlain, Alanna M.;St Sauver, Jennifer L.;Rutten, Lila J. Finney
通讯作者：
Rutten, Lila J. Finney
DOI：
10.1093/gerona/gln038
发表时间：
2009-04-01
影响因子：
5.1
作者：
Brinkley, Tina E.;Leng, Xiaoyan;Nicklas, Barbara J.
通讯作者：
Nicklas, Barbara J.
影响因子：
7.4
作者：
Blyth, Fiona M.;Rochat, Stephane;Waite, Louise M.
通讯作者：
Waite, Louise M.
DOI：
10.1002/jcsm.12051
发表时间：
2015-12
期刊：
Journal of cachexia, sarcopenia and muscle
影响因子：
--
作者：
Calvani R;Marini F;Cesari M;Tosato M;Anker SD;von Haehling S;Miller RR;Bernabei R;Landi F;Marzetti E;SPRINTT consortium
通讯作者：
SPRINTT consortium
影响因子：
3.6
作者：
Artz, Andrew S.
通讯作者：
Artz, Andrew S.