Department of Biomedical and Dental Sciences and Morphofunctional Imaging, Policlinico Universitario, University of Messina, 1, Via Consolare Valeria, 98125, Messina, Italy.
Department of Medical Informatics, Erasmus Medical Centre, s-Gravendijkwal 230, 3015 CE, Rotterdam, The Netherlands.
Drug Saf. 2019 Jun;42(6):713-719. doi: 10.1007/s40264-018-00785-z.
The role of frailty in postmarketing drug safety is increasingly acknowledged. Few European electronic medical records (EMRs) have been used to explore frailty in observational drug safety research.
The aim of this study was to identify data elements, beyond multimorbidity and polypharmacy, that could potentially contribute to measuring frailty among older adults in the Dutch nationwide Integrated Primary Care Information (IPCI) database.
Persons aged between 65 and 90 years in the IPCI database were identified from 2008 to 2013. Clinical non-disease, non-drug measurements that could potentially contribute to measuring frailty were identified and selected if they were recorded in > 0.005% of patients and could be included in at least one of three definitions of frailty: the frailty phenotype model, the cumulative deficit model, and direct evaluations of frailty through standardized frailty scores. The frequency of these measures was calculated.
Overall, 314,191 (17% of the source population) elderly persons were identified. Of these, 7948 (2.53%) had one or more of 12 clinical measurements identified that could potentially contribute to measuring frailty, such as clinical evaluations of cognition, mobility, and cachexia, as well as direct measures of frailty, such as the Groningen Frailty Index. Three of five measurements required for the frailty phenotype were identified in < 0.5% of the population: cachexia, reduced walking speed, and reduced physical activity; weakness and fatigue were not identified. The measurements outlined above may be appropriate for the cumulative deficit definition of frailty, provided that at least 30 deficits, including comorbidities and drug utilization, are evaluated in total. The most commonly recorded item identified that could potentially be used in a cumulative frailty model was the Mini-Mental State Examination score (N= 2850; 0.91%); the only recorded direct measurement of frailty was the Groningen Frailty Index (N = 2382; 0.76%).
Non-disease, non-drug clinical data that could potentially contribute to a frailty model was not commonly recorded in the IPCI; less than 3% of a cohort of elderly persons had these data recorded, suggesting that the use of these data in postmarketing drug safety evaluation may be limited.
衰弱在药物上市后安全性中的作用越来越受到认可。很少有欧洲电子病历(EMR)被用于探索观察性药物安全性研究中的衰弱问题。
本研究旨在确定除了多病种和多药物治疗之外,在荷兰全国综合初级保健信息(IPCI)数据库中,哪些数据元素可能有助于测量老年人的衰弱程度。
从 2008 年至 2013 年,在 IPCI 数据库中确定年龄在 65 至 90 岁之间的人群。确定可能有助于测量衰弱的非疾病、非药物临床测量值,如果这些测量值记录在超过 0.005%的患者中,并且可以至少包含以下三种衰弱定义之一:衰弱表型模型、累积缺陷模型和通过标准化衰弱评分直接评估衰弱,则选择这些测量值。计算这些测量值的频率。
总体而言,确定了 314191 名(源人群的 17%)老年人。其中,7948 人(2.53%)具有 12 种可能有助于测量衰弱的临床测量值之一或更多,例如认知、移动和恶病质的临床评估,以及直接测量衰弱的方法,如 Groningen 衰弱指数。五种衰弱表型所需的三种测量值中有三种(<0.5%的人群):恶病质、行走速度降低和体力活动减少;虚弱和疲劳未被识别。上述测量值可能适合于衰弱的累积缺陷定义,前提是总共评估至少 30 种缺陷,包括合并症和药物利用情况。确定的最常见的可能用于累积衰弱模型的记录项目是简易精神状态检查评分(N=2850;0.91%);记录的唯一直接衰弱测量值是 Groningen 衰弱指数(N=2382;0.76%)。
IPCI 中未常规记录可能有助于衰弱模型的非疾病、非药物临床数据;不到 3%的老年人群记录了这些数据,这表明在药物上市后安全性评估中使用这些数据可能受到限制。