The Predictive Value of Preendoscopic Risk Scores to Predict Adverse Outcomes in Emergency Department Patients With Upper Gastrointestinal Bleeding: A Systematic Review
Bibliographic record
Abstract
OBJECTIVES: Risk stratification of emergency department (ED) patients with upper gastrointestinal bleeding (UGIB) using preendoscopic risk scores can aid ED physicians in disposition decision-making. We conducted a systematic review to assess the predictive value of preendoscopic risk scores for 30-day serious adverse events. METHODS: We searched MEDLINE, PubMed, Embase, and the Cochrane Database of Systematic Reviews from inception to March 2015. We included studies involving adult ED UGIB patients evaluating preendoscopic risk scores and excluded reviews, case reports, and animal studies. The composite outcome included 30-day mortality, recurrent bleeding, and need for intervention. In two phases (screening and full review), two reviewers independently screened articles for inclusion and extracted patient-level data. The consensus data were used for analysis. We reported sensitivity, specificity, positive and negative predictive value, and positive and negative likelihood ratios with 95% confidence intervals. RESULTS: We identified 3,173 articles, of which 16 were included: three studied Glasgow Blatchford score (GBS); one studied clinical Rockall score (cRockall); two studied AIMS65; six compared GBS and cRockall; three compared GBS, a modification of the GBS, and cRockall; and one compared the GBS and AIMS65. Overall, the sensitivity and specificity of the GBS were 0.98 and 0.16, respectively; for the cRockall they were 0.93 and 0.24, respectively; and for the AIMS65 they were 0.79 and 0.61, respectively. The GBS with a cutoff point of 0 had a sensitivity of 0.99 and a specificity of 0.08. CONCLUSION: The GBS with a cutoff point of 0 was superior over other cutoff points and risk scores for identifying low-risk patients but had a very low specificity. None of the risk scores identified by our systematic review were robust and, hence, cannot be recommended for use in clinical practice. Future prospective studies are needed to develop robust new scores for use in ED patients with UGIB.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.010 | 0.056 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.009 | 0.009 |
| Bibliometrics | 0.010 | 0.010 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".