Orkaby Ariela R, Hshieh Tammy T, Gaziano John M, Djousse Luc, Driver Jane A
Division of Aging, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA; VA Boston Healthcare System, Geriatric Research, Education, and Clinical Center (GRECC), Massachusetts Veterans Epidemiology and Research Information Center (MAVERIC), Boston, MA, USA.
Division of Aging, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA.
Arch Gerontol Geriatr. 2017 Jul;71:21-27. doi: 10.1016/j.archger.2017.02.009. Epub 2017 Feb 20.
As the population ages it is important to identify frailty, a powerful predictor of morbidity and mortality, and often an important unmeasured confounder. We sought to develop a frailty index in the Physician's Health Study (PHS) and estimate the association with mortality.
Prospective cohort study. Annual questionnaire assessed mood, function and health status. Two frailty scores were compared - cumulative deficit frailty index (PHS FI) and modified Study of Osteoporotic Fracture (mSOF) frailty score. Endpoints committee confirmed mortality.
12,180 male physicians ≥60 years were analyzed. Mean(SD) follow-up was 10(3) years, 2168 deaths occurred. PHS FI identified 4412 (36%) physicians robust, 5305 (44%) pre-frail, and 2463 (20%) frail, while mSOF identified 7323 (61%) robust, 3505 (29%) pre-frail and 1215 (10%) frail. Age-standardized rate of death was lower among subjects identified as robust using the PHS FI, 11/1000 person-years (PY) (95% Confidence Interval (CI): 9.5-11.9) compared to 14/1000PY (95% CI: 13.5-15.4) using mSOF [P-difference <0.001]. In the prefrail group, death rates were 16/1000PY in PHS FI and 21/1000PY in mSOF, [P-difference <0.001]. There was no difference in age-adjusted mortality rates in the frail group according to each definition (35 vs 33/1000PY). Survival analysis showed an increased risk of mortality in each frailty category using either definition, (log-rank p<0.001).
The PHS FI outperformed mSOF in identifying risk of death particularly in robust and pre-frail categories. Similar indices can be created in existing datasets to identify frail individuals and where appropriate account for frailty, an often unmeasured confounder.
随着人口老龄化,识别衰弱这一发病率和死亡率的有力预测指标以及常常未被测量的重要混杂因素变得至关重要。我们试图在医师健康研究(PHS)中开发一种衰弱指数,并评估其与死亡率的关联。
前瞻性队列研究。通过年度问卷评估情绪、功能和健康状况。比较了两种衰弱评分——累积缺陷衰弱指数(PHS FI)和改良的骨质疏松性骨折研究(mSOF)衰弱评分。终点委员会确认死亡情况。
对12180名年龄≥60岁的男性医师进行了分析。平均(标准差)随访时间为10(3)年,发生了2168例死亡。PHS FI将4412名(36%)医师判定为健康,5305名(44%)为衰弱前期,2463名(20%)为衰弱;而mSOF将7323名(61%)医师判定为健康,3505名(29%)为衰弱前期,1215名(10%)为衰弱。使用PHS FI判定为健康的受试者的年龄标准化死亡率较低,为11/1000人年(PY)(95%置信区间(CI):9.5 - 11.9),而使用mSOF时为14/1000 PY(95% CI:13.5 - 15.4)[P差异<0.001]。在衰弱前期组中,PHS FI的死亡率为16/1000 PY,mSOF为21/1000 PY,[P差异<0.001]。根据每种定义,衰弱组的年龄调整死亡率没有差异(35对33/1000 PY)。生存分析表明,使用任何一种定义,每个衰弱类别中的死亡风险均增加(对数秩检验p<0.001)。
在识别死亡风险方面,尤其是在健康和衰弱前期类别中,PHS FI优于mSOF。可以在现有数据集中创建类似的指数,以识别衰弱个体,并在适当情况下考虑衰弱这一常常未被测量的混杂因素。