Department of Medicine, University of Alabama at Birmingham, Nashville, Tennessee.
Department of Biostatistics, Vanderbilt University Medical Center, Nashville, Tennessee.
J Gerontol A Biol Sci Med Sci. 2019 Jul 12;74(8):1282-1288. doi: 10.1093/gerona/gly224.
It is unknown whether observational studies evaluating the association between antidiabetic medications and mortality adequately account for frailty. Our objectives were to evaluate if frailty was a potential confounder in the relationship between antidiabetic medication regimen and mortality and how well administrative and clinical electronic health record (EHR) data account for frailty.
We conducted a retrospective cohort study in a single Veterans Health Administration (VHA) healthcare system of 500 hospitalizations-the majority due to heart failure-of Veterans who received regular VHA care and initiated type 2 diabetes treatment from 2001 to 2008. We measured frailty using a modified frailty index (FI, >0.21 frail). We obtained antidiabetic medication regimen and time-to-death from administrative sources. We compared FI among patients on different antidiabetic regimens. Stepwise Cox proportional hazards regression estimated time-to-death by demographic, administrative, clinical EHR, and FI data.
Median FI was 0.22 (interquartile range 0.18, 0.27). Frailty differed across antidiabetic regimens (p < .001). An FI increase of 0.05 was associated with an increased risk of death (hazard ratio 1.45, 95% confidence interval 1.32, 1.60). Cox proportional hazards model for time-to-death including demographic, administrative, and clinical EHR data had a c-statistic of 0.70; adding FI showed marginal improvement (c-statistic 0.72).
Frailty was associated with antidiabetic regimen and death, and may confound that relationship. Demographic, administrative, and clinical EHR data, commonly used to balance differences among exposure groups, performed moderately well in assessing risk of death, with minimal gain from adding frailty. Study design and analytic techniques can help minimize potential confounding by frailty in observational studies.
目前尚不清楚评估抗糖尿病药物与死亡率之间关联的观察性研究是否充分考虑了衰弱问题。我们的目的是评估衰弱是否是抗糖尿病药物治疗方案与死亡率之间关系的一个潜在混杂因素,以及行政和临床电子健康记录(EHR)数据对衰弱的评估程度。
我们在一个退伍军人医疗保健系统(VHA)中进行了一项回顾性队列研究,该系统中共有 500 例住院患者,其中大多数是由于心力衰竭住院的退伍军人,他们在 2001 年至 2008 年期间接受了常规 VHA 护理,并开始接受 2 型糖尿病治疗。我们使用改良的衰弱指数(FI,>0.21 为衰弱)来测量衰弱。我们从行政数据中获得抗糖尿病药物治疗方案和死亡时间。我们比较了不同抗糖尿病治疗方案患者的 FI。逐步 Cox 比例风险回归分析根据人口统计学、行政、临床 EHR 和 FI 数据估计死亡时间。
FI 的中位数为 0.22(四分位距 0.18,0.27)。不同抗糖尿病治疗方案的衰弱程度不同(p<0.001)。FI 增加 0.05 与死亡风险增加相关(风险比 1.45,95%置信区间 1.32,1.60)。包括人口统计学、行政和临床 EHR 数据的 Cox 比例风险模型用于评估死亡时间,其 C 统计量为 0.70;加入 FI 仅略有改善(C 统计量为 0.72)。
衰弱与抗糖尿病药物治疗方案和死亡相关,可能会混杂这种关系。人口统计学、行政和临床 EHR 数据常用于平衡暴露组之间的差异,在评估死亡风险方面表现良好,加入衰弱后略有改善。研究设计和分析技术可以帮助最大限度地减少观察性研究中衰弱的潜在混杂。