Predictive value of reverse shock index multiplied by Glasgow coma scale score for mortality of trauma patients: a Meta analysis
10.3760/cma.j.cn501098-20250615-00337
- VernacularTitle:反向休克指数与格拉斯哥昏迷评分乘积指数预测创伤患者死亡价值的Meta分析
- Author:
Bing LIU
1
;
Guohong JIA
1
;
Xiaopei BU
1
;
Chuangye SONG
1
;
Jianghua ZHANG
1
;
Zhifang JIA
1
;
Xiaowu LI
1
;
Jianjun MIAO
1
Author Information
1. 中国人民解放军陆军第八十一集团军医院普通外科，张家口 075000
- Publication Type:Journal Article
- Keywords:
Wounds and injuries;
Shock;
Glasgow coma scale;
Prognosis;
Meta analysis
- From:
Chinese Journal of Trauma
2025;41(11):1094-1102
- CountryChina
- Language:Chinese
-
Abstract:
Objective:To systematically evaluate the predictive value of the reverse shock index multiplied by the Glasgow coma scale score (rSIG) for mortality of trauma patients.Methods:A comprehensive literature search was conducted to identify studies on the predictive value of rSIG for mortality of trauma patients in the following databases from inception to April 2025, including CNKI, Wanfang Data, SinoMed, PubMed, Cochrane Library, Web of Science, and Embase. Two investigators independently screened the literature, extracted data, and assessed study quality according to predefined inclusion and exclusion criteria. The Quality assessment of diagnostic accuracy studies-2 (QUADAS-2) tool was used to evaluate the risk of bias in the included studies. Meta analysis was performed using Stata 17.0 software with a bivariate mixed-effects model. The following metrics were used to assess the predictive value of rSIG for mortality in trauma patients, including sensitivity, specificity, positive likelihood ratio (PLR), negative likelihood ratio (NLR), diagnostic odds ratio (DOR), and area under the summary receiver operating characteristic (SROC) curve (AUC). The influence of various factors on the predictive performance of rSIG was examined, including injury type, study design, region, sample size, cut-off value, rSIG measurement time, and outcome measures. Additionally, sensitivity analysis, Fagan′s nomogram, and Deeks′ funnel plot were employed to assess the robustness of the findings, clinical applicability, and publication bias.Results:A total of 15 studies involving 710 612 trauma patients were included, 26 105 of whom were deceased. Meta analysis results showed that rSIG had a pooled sensitivity of 0.78(95% CI 0.71, 0.84), a pooled specificity of 0.78(95% CI 0.68, 0.86), a pooled PLR of 3.60(95% CI 2.46, 5.27), a pooled NLR of 0.28(95% CI 0.22, 0.36), a pooled DOR of 12.70(95% CI 8.10, 19.91), and an AUC of 0.85(95% CI 0.81, 0.87) for predicting mortality of trauma patients. Subgroup analysis identified injury type as one of the major sources of heterogeneity, and the predictive specificity of rSIG was significantly higher in patients with multiple trauma (0.82) than in those with isolated traumatic brain injury (0.65) ( P<0.05). Sensitivity analysis indicated that the findings were robust and stable. Fagan′s nomogram showed that when the pre-test probability was 7%, the post-test probability of death increased to 21% in patients with low rSIG and decreased to 2% in those with high rSIG. Deeks′ funnel plots suggested no significant publication bias among the included studies ( P>0.05). Conclusion:Low rSIG has good predictive performance for mortality of trauma patients and can serve as an effective tool for early and rapid prognosis assessment with superior predictive performance in patients with multiple trauma compared to those with traumatic brain injury.
