ArticleThe Journal of international medical research2022
Prediction of in-hospital mortality after acute upper gastrointestinal bleeding: cross-validation of several risk scoring systems.
Article in The Journal of international medical research, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
What it found
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Who cites it
4 citing papers in PubMed, 15 citations in OpenAlex.
- Inflammatory indices as independent predictors of in-hospital mortality in acute upper gastrointestinal bleeding.BMC gastroenterology · 2026Observational
- The future of critical care: AI-powered mortality prediction for acute variceal gastrointestinal bleeding and acute non-variceal gastrointestinal bleeding patients.Frontiers in medicine · 2025Article
- Lactate level as a predictor of outcomes in patients with acute upper gastrointestinal bleeding: A systematic review and meta‑analysis.Experimental and therapeutic medicine · 2024Article
- The Accuracy of Pre-Endoscopic Scores for Mortality Prediction in Patients with Upper GI Bleeding and No Endoscopy Performed.Diagnostics (Basel, Switzerland) · 2023Article
Corrections and comments
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Authors and funding
4 authors at 2 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
objectiveWe aimed to identify the clinical, biochemical, and endoscopic features associated with in-hospital mortality after acute upper gastrointestinal bleeding (AUGIB), focusing on cross-validation of the Glasgow-Blatchford score (GBS), full Rockall score (RS), and Cedars-Sinai Medical Center Predictive Index (CSMCPI) scoring systems.
methodsOur prospective cross-sectional study included 156 patients with AUGIB. Several statistical approaches were used to assess the predictive accuracy of the scoring systems.
resultsAll three scoring systems were able to accurately predict in-hospital mortality (area under the receiver operating characteristic curve [AUC] > 0.9); however, the multiple logistic model separated the presence of hemodynamic instability (state of shock) and the CSMCPI as the only significant predictive risk factors. In compliance with the overall results, the CSMCPI was consistently found to be superior to the other two systems (highest AUC, highest sensitivity and specificity, highest positive and negative predictive values, highest positive likelihood ratio, lowest negative likelihood ratio, and 1-unit increase in CSMCPI associated with 6.3 times higher odds of mortality), outperforming the GBS and full RS.
conclusionsWe suggest consideration of the CSMCPI as a readily available and reliable tool for accurately predicting in-hospital mortality after AUGIB, thus providing an essential backbone in clinical decision-making.
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