Clinical Frailty Scale as a predictor of short‐term mortality: A systematic review and meta‐analysis of studies on diagnostic test accuracy

摘要

Abstract Background The Clinical Frailty Scale (CFS) is a representative frailty assessment tool in medicine. This systematic review and meta‐analysis aimed to examine whether frailty defined based on the CFS could adequately predict short‐term mortality in emergency department (ED) patients. Methods The PubMed, EMBASE, and Cochrane libraries were searched for eligible studies until December 23, 2021. We included studies in which frailty was measured by the CFS and short‐term mortality was reported for ED patients. All studies were screened by two independent researchers. Sensitivity, specificity, positive likelihood ratio (PLR), and negative likelihood ratio (NLR) values were calculated based on the data extracted from each study. Additionally, the diagnostic odds ratio (DOR) was calculated for effect size analysis, and the area under the curve (AUC) of summary receiver operating characteristics was calculated. Outcomes were in‐hospital and 1‐month mortality rate for patients with the CFS scores of ≥5, ≥6, and ≥7. Results Overall, 17 studies (n?=?45,022) were included. Although there was no evidence of publication bias, a high degree of heterogeneity was observed. For the CFS score of ≥5, the PLR, NLR, and DOR values for in‐hospital mortality were 1.446 (95% confidence interval [CI] 1.325–1.578), 0.563 (95% CI 0.355–0.893), and 2.728 (95% CI 1.872–3.976), respectively. In addition, the pooled statistics for 1‐month mortality were 1.566 (95% CI 1.241–1.976), 0.582 (95% CI 0.430–0.789), and 2.696 (95% CI 1.673–4.345), respectively. Subgroup analysis of trauma patients revealed that the CFS score of ≥5 could adequately predict in‐hospital mortality (PLR?1.641, 95% CI 1.242–2.170; NLR?0.580, 95% CI 0.461–0.729; DOR?2.883, 95% CI 1.994–4.168). The AUC values represented sufficient to good diagnostic accuracy. Conclusions Evidence that is published to date suggests that the CFS is an accurate and reliable tool for predicting short‐term mortality in emergency patients.