背景:急性心肌梗死患者的虚弱表现越来越多。电子虚弱指数(eFI)是一种经过验证的方法,可从常规初级保健数据中识别社区中的脆弱老年患者。我们的目的是评估eFI与老年急性心肌梗死住院患者预后之间的关系。
方法:使用DataLoch心脏病登记处进行的回顾性队列研究包括2013年10月至2021年3月期间因心肌梗死住院的65岁或以上的连续患者。
方法:患者被分类为适合,温和,中度,或者根据他们的eFI分数严重虚弱。Cox回归分析用于确定虚弱类别与全因死亡率之间的关联。
结果:在4670名患者中(中位年龄77岁[71-84],43%女性),1865年(40%)被归类为适合,1699(36%),798(17%)和308(7%)分类为轻度,中度和严重虚弱,分别。总的来说,1142例患者在12个月内死亡,其中248例(13%)和147例(48%)被归类为健康和严重虚弱。分别。调整后,任何程度的虚弱都与全因死亡风险增加相关,其中严重虚弱的风险最大(参考=fit,调整后的风险比2.87[95%置信区间2.24至3.66])。
结论:eFI确定心肌梗死后死亡风险高的患者。管理数据中的自动计算是可行的,并且可以提供一种低成本的方法来识别医院就诊的脆弱老年患者。
BACKGROUND: Frailty is increasingly present in patients with acute myocardial infarction. The electronic Frailty Index (eFI) is a validated method of identifying vulnerable older patients in the community from routine primary care data. Our aim was to assess the relationship between the eFI and outcomes in older patients hospitalised with acute myocardial infarction.
METHODS: Retrospective cohort study using the DataLoch Heart Disease Registry comprising consecutive patients aged 65 years or over hospitalised with a myocardial infarction between October 2013 and March 2021.
METHODS: Patients were classified as fit, mild, moderate, or severely frail based on their eFI score. Cox-regression analysis was used to determine the association between frailty category and all-cause mortality.
RESULTS: In 4670 patients (median age 77 years [71-84], 43% female), 1865 (40%) were classified as fit, with 1699 (36%), 798 (17%) and 308 (7%) classified as mild, moderate and severely frail, respectively. In total, 1142 patients died within 12 months of which 248 (13%) and 147 (48%) were classified as fit and severely frail, respectively. After adjustment, any degree of frailty was associated with an increased risk of all-cause death with the risk greatest in the severely frail (reference = fit, adjusted hazard ratio 2.87 [95% confidence intervals 2.24 to 3.66]).
CONCLUSIONS: The eFI identified patients at high risk of death following myocardial infarction. Automatic calculation within administrative data is feasible and could provide a low-cost method of identifying vulnerable older patients on hospital presentation.