부산대학교 도서관

This cohort study evaluates the use of a frailty index to estimate risk of postoperative adverse outcomes in patients 55 years or older who are recovering from noncardiac surgery. Key Points: Question: What is the association between frailty status, as defined by a validated automated electronic frailty index (eFI), and postoperative adverse events in patients recovering from major noncardiac surgery? Findings: In this cohort study of 33 449 patients who underwent noncardiac surgery lasting at least 1 hour, patients who were classified as prefrail and frail vs those with fit status had a higher odds of postoperative adverse events in a fully adjusted model. Each increase of the eFI score by 0.03 units increased the odds of postoperative adverse events. Meaning: Findings of this study suggest that frailty status is associated with increased odds of postoperative adverse events in older adults recovering from noncardiac surgery; deployment of eFI tools could support screening and possible risk modification, especially in this population. Importance: Electronic frailty index (eFI) is an automated electronic health record (EHR)–based tool that uses a combination of clinical encounters, diagnosis codes, laboratory workups, medications, and Medicare annual wellness visit data as markers of frailty status. The association of eFI with postanesthesia adverse outcomes has not been evaluated. Objective: To examine the association of frailty, calculated as eFI at the time of the surgical procedure and categorized as fit, prefrail, or frail, with adverse events after elective noncardiac surgery. Design, Setting, and Participants: This cohort study was conducted at a tertiary care academic medical center in Winston-Salem, North Carolina. The cohort included patients 55 years or older who underwent noncardiac surgery of at least 1 hour in duration between October 1, 2017, and June 30, 2021. Exposure: Frailty calculated by the eFI tool. Preoperative eFI scores were calculated based on available data 1 day prior to the procedure and categorized as fit (eFI score: ≤0.10), prefrail (eFI score: >0.10 to ≤0.21), or frail (eFI score: >0.21). Main Outcomes and Measures: The primary outcome was a composite of the following 8 adverse component events: 90-item Patient Safety Indicators (PSI 90) score, hospital-acquired conditions, in-hospital mortality, 30-day mortality, 30-day readmission, 30-day emergency department visit after surgery, transfer to a skilled nursing facility after surgery, or unexpected intensive care unit admission after surgery. Secondary outcomes were each of the component events of the composite. Results: Of the 33 449 patients (median [IQR] age, 67 [61-74] years; 17 618 females [52.7%]) included, 11 563 (34.6%) were classified as fit, 15 928 (47.6%) as prefrail, and 5958 (17.8%) as frail. Using logistic regression models that were adjusted for age, sex, race and ethnicity, and comorbidity burden, patients with prefrail (odds ratio [OR], 1.24; 95% CI, 1.18-1.30; P <.001) and frail (OR, 1.71; 95% CI, 1.58-1.82; P <.001) statuses were more likely to experience postoperative adverse events compared with patients with a fit status. Subsequent adjustment for all other potential confounders or covariates did not alter this association. For every increase in eFI of 0.03 units, the odds of a composite of postoperative adverse events increased by 1.06 (95% CI, 1.03-1.13; P <.001). Conclusions and Relevance: This cohort study found that frailty, as measured by an automatically calculated index integrated within the EHR, was associated with increased risk of adverse events after noncardiac surgery. Deployment of eFI tools may support screening and possible risk modification, especially in patients who undergo high-risk surgery.