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Sarcopenia, frailty and cachexia patients detected in a multisystem electronic health record database

机译:在多系统电子健康记录数据库中检测到SARCOPENIA,FRAIRTY和CACHEXIA患者

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BACKGROUND:Sarcopenia, cachexia and frailty have overlapping features and clinical consequences, but often go unrecognized. The objective was to detect patients described by clinicians as having sarcopenia, cachexia or frailty within electronic health records (EHR) and compare clinical variables between cases and matched controls.METHODS:We conducted a case-control study using retrospective data from the Indiana Network for Patient Care multi-health system database from 2016 to 2017. The computable phenotype combined ICD codes for sarcopenia, cachexia and frailty, with clinical note text terms for sarcopenia, cachexia and frailty detected using natural language processing. Cases with these codes or text terms were matched to controls without these codes or text terms matched on birth year, sex and race. Two physicians reviewed EHR for all cases and a subset of controls. Comorbidity codes, laboratory values, and other coded clinical variables were compared between groups using Wilcoxon matched-pair sign-rank test for continuous variables and conditional logistic regression for binary variables.RESULTS:Cohorts of 9594 cases and 9594 matched controls were generated. Cases were 59% female, 69% white, and a median (1st, 3rd quartiles) age 74.9 (62.2, 84.8) years. Most cases were detected by text terms without ICD codes n?=?8285 (86.4%). All cases detected by ICD codes (total n?=?1309) also had supportive text terms. Overall 1496 (15.6%) had concurrent terms or codes for two or more of the three conditions (sarcopenia, cachexia or frailty). Of text term occurrence, 97% were used positively for sarcopenia, 90% for cachexia, and 95% for frailty. The remaining occurrences were negative uses of the terms or applied to someone other than the patient. Cases had lower body mass index, albumin and prealbumin, and significantly higher odds ratios for diabetes, hypertension, cardiovascular and peripheral vascular diseases, chronic kidney disease, liver disease, malignancy, osteoporosis and fractures (all p??0.05). Cases were more likely to be prescribed appetite stimulants and caloric supplements.CONCLUSIONS:Patients detected with a computable phenotype for sarcopenia, cachexia and frailty differed from controls in several important clinical variables. Potential uses include detection among clinical cohorts for targeting recruitment for research and interventions.
机译:背景:Sarcopenia,Cachexia和Freailty具有重叠的特征和临床后果,但经常无法识别。该目的是检测临床医生描述的患者,以在电子健康记录(EHR)内具有患者,并在案件和匹配控制之间比较临床变量。方法:我们使用来自印第安纳网络的回顾数据进行了案例控制研究从2016到2017年患者提供多卫生系统数据库。可计算表型组合肌肉脑,恶病虫和脆弱的ICD代码,使用自然语言处理检测到SARCOPENIA,恶病毒和脆弱的临床票据文本术语。具有这些代码或文本术语的案件与没有这些代码或出生年份,性和种族匹配的文本术语的控制。两个医生审查了所有案例的EHR和一个控制的子集。在使用Wilcoxon匹配的对符号测试与二元变量的连续变量和条件逻辑回归的组中,在组之间比较了合并码,实验室值和其他编码的临床变量。结果:9594例和9594个匹配对照的群组。病例为59%的雌性,69%白色,和中位数(1st,第3四分位数)74.9岁(62.2,84.8)年。大多数情况是通过没有ICD代码的文本术语来检测到的案例n?=?8285(86.4%)。 ICD代码检测的所有病例(总N?=?1309)也有支持性文本。总体而言,1496(15.6%)在三种条件(Sarcopenia,Cachexia或Freailty)中有两种或更多种同时术语或代码。文本术语发生,97%用于SARCOPENIA,90%的恶棍,95%的脆弱。剩余的出现是术语的负面用途或应用于除患者以外的人。病例具有较低的身体质量指数,白蛋白和预级白蛋白,对糖尿病,高血压,心血管和外周血血管疾病,慢性肾病,肝脏病,恶性肿瘤,骨质疏松症和骨折(所有P <-0.05)显着较高。病例更容易处方食欲兴奋剂和热源补充剂。结论:用可计算表型检测的患者,用于SARCOPENIA,恶病症和脆弱在几个重要的临床变量中的控制不同。潜在用途包括临床队列中的检测,用于针对研究和干预的招聘。

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