Comparison of Risk Scores for Lower Gastrointestinal Bleeding A Systematic Review and Meta-analysis

被引:24
作者
Almaghrabi, Majed [1 ]
Gandhi, Mandark [2 ]
Guizzetti, Leonardo
Iansavichene, Alla [3 ]
Yan, Brian [1 ]
Wilson, Aze [1 ]
Oakland, Kathryn [4 ]
Jairath, Vipul [1 ,5 ,6 ]
Sey, Michael [1 ,5 ]
机构
[1] Western Univ, Div Gastroenterol, London, ON, Canada
[2] Grand River Hosp, Dept Med, Kitchener, ON, Canada
[3] London Hlth Sci Ctr, Lib Serv, London, ON, Canada
[4] HCA Healthcare UK, Digest Dis Dept, London, England
[5] London Hlth Sci Ctr, Lawson Hlth Res Inst, 800 Commissioners Rd E, London, ON N6A 5W9, Canada
[6] Western Univ, Dept Epidemiol & Biostat, London, ON, Canada
关键词
PREDICTION MODEL; NEURAL-NETWORK; VALIDATION; OUTCOMES; MANAGEMENT; HEMORRHAGE; TOOL; NEED;
D O I
10.1001/jamanetworkopen.2022.14253
中图分类号
R5 [内科学];
学科分类号
1002 ; 100201 ;
摘要
IMPORTANCE Clinical prediction models, or risk scores, can be used to risk stratify patients with lower gastrointestinal bleeding (LGIB), although the most discriminative score is unknown. OBJECTIVE To identify all LGIB risk scores available and compare their prognostic performance. DATA SOURCES A systematic search of Ovid MEDLINE, Embase, and the Cochrane Central Register of Controlled Trials from January 1, 1990, through August 31, 2021, was conducted. Non-English-language articles were excluded. STUDY SELECTION Observational and interventional studies deriving or validating an LGIB risk score for the prediction of a clinical outcome were included. Studies including patients younger than 16 years or limited to a specific patient population or a specific cause of bleeding were excluded. Two investigators independently screened the studies, and disagreements were resolved by consensus. DATA EXTRACTION AND SYNTHESIS Data were abstracted according to the Preferred Reporting Items for Systematic Reviews and Meta-analyses (PRISMA) guideline independently by 2 investigators and pooled using random-effects models. MAIN OUTCOMES AND MEASURES Summary diagnostic performance measures (sensitivity, specificity, and area under the receiver operating characteristic curve [AUROC]) determined a priori were calculated for each risk score and outcome combination. RESULTS A total of 3268 citations were identified, of which 9 studies encompassing 12 independent cohorts and 4 risk scores (Oakland, Strate, NOBLADS [nonsteroidal anti-inflammatory drug use, no diarrhea, no abdominal tenderness, blood pressure <= 100 mm Hg, antiplatelet drug use (nonaspirin), albumin <3.0 g/dL, disease score >= 2 (according to the Charlson Comorbidity Index), and syncope], and BLEED [ongoing bleeding, low systolic blood pressure, elevated prothrombin time, erratic mental status, and unstable comorbid disease]) were included in the meta-analysis. For the prediction of safe discharge, the AUROC for the Oakland score was 0.86 (95% CI, 0.82-0.88). For major bleeding, the AUROC was 0.93 (95% CI, 0.90-0.95) for the Oakland score, 0.73 (95% CI, 0.69-0.77) for the Strate score, 0.58 (95% CI, 0.53-0.62) for the NOBLADS score, and 0.65 (95% CI, 0.61-0.69) for the BLEED score. For transfusion, the AUROC was 0.99 (95% CI, 0.98-1.00) for the Oakland score and 0.88 (95% CI, 0.85-0.90) for the NOBLADS score. For hemostasis, the AUROC was 0.36 (95% CI, 0.32-0.40) for the Oakland score, 0.82 (95% CI, 0.79-0.85) for the Strate score, and 0.24 (95% CI, 0.20-0.28)for the NOBLADS score. CONCLUSIONS AND RELEVANCE The Oakland score was the most discriminative LGIB risk score for predicting safe discharge, major bleeding, and need for transfusion, whereas the Strate score was best for predicting need for hemostasis. This study suggests that these scores can be used to predict outcomes from LGIB and guide clinical care accordingly.
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页数:14
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