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哪种脆弱性评估方法可以更好地提高 SASA 对择期腹部手术患者术后并发症的预测能力?
Authors Yin Y, Jiang L , Xue L
Received 7 January 2022
Accepted for publication 4 April 2022
Published 5 May 2022 Volume 2022:18 Pages 541—550
DOI https://doi.org/10.2147/TCRM.S357285
Checked for plagiarism Yes
Review by Single anonymous peer review
Peer reviewer comments 2
Editor who approved publication: Dr De-Yun Wang
Purpose: To determine which frailty method can better improve the predictive ability of the Surgical Apgar Score combined with American Society of Anesthesiologists physical status classification (SASA).
Patients and Methods: A prospective cohort study was conducted. A total of 194 elderly patients undergoing elective abdominal surgery were included. Preoperative frailty using FRAIL questionnaire, frailty index (FI), Clinical Frailty Scale (CFS) and SASA scores was assessed. Primary outcome was in-hospital Clavien-Dindo ≥grade II complications. Multiple logistic regression was used to examine the association between frailty and complications. Receiver operating characteristic curves were used to explore the predictive ability of frailty.
Results: According to the FRAIL, FI and CFS criteria, the prevalence of frailty in the study population was 43.8%, 32.5%, and 36.6%, respectively. After adjusting for all covariates, frailty was significantly associated with postoperative complications in hospital by FRAIL [odds ratio: 5.11, 95% CI: 1.41– 18.44, P = 0.013], by FI [OR: 4.25, 95% CI: 1.21– 14.90, P = 0.024] and by CFS [OR: 5.10, 95% CI: 1.52– 17.17, P = 0.008]. The area under the curve (AUC) for SASA was 0.768 (95% CI: 0.702– 0.826). Addition of frailty assessment (FRAIL, FI and CFS) increased the AUC to 0.787 (95% CI: 0.722– 0.842), 0.798 (95% CI: 0.734– 0.852), and 0.815 (95% CI: 0.753– 0.867), respectively. Compared to SASA, only addition of CFS had a significant difference (P = 0.0478).
Conclusion: Frailty is an effective predictor of postoperative complications in elderly Chinese patients undergoing elective abdominal surgery. Frailty assessment of CFS can better improve the predictive ability of SASA.
Keywords: frailty assessment, risk assessment tool, postoperative complication