Effect of Comorbidity on Mortality in Patients With Peptic Ulcer Bleeding: Systematic Review and Meta-Analysis
Bibliographic record
Abstract
OBJECTIVES: By systematic review and meta-analysis, we sought to assess the impact of comorbidity on short-term mortality in patients with peptic ulcer bleeding (PUB). METHODS: We conducted systematic searches in PubMed and Embase (January 1989-January 2010). Relative risks (RRs) were pooled across selected studies and an analysis of diagnostic test accuracy was performed to validate the results further. RESULTS: Of 1,572 identified studies, 16 were eligible for inclusion. Only three had a low risk of bias and the overall quality of evidence was low. The risk of death (30-day or in-hospital mortality) was significantly greater in PUB patients with comorbidity than in those without (RR: 4.44; 95% confidence interval (CI): 2.45-8.04). The pooled sensitivity for comorbidity predicting death in patients with PUB was 0.86 (95% CI: 0.66-0.95) and the pooled specificity was 0.53 (95% CI: 0.40-0.65). PUB patients with three or more comorbidities had a greater risk of dying than those with one or two (RR: 3.46; 95% CI: 1.34-8.89). All individual comorbidities that we assessed significantly increased the risk of death associated with PUB. However, RRs were higher for hepatic, renal, and malignant disease (range: 4.04-6.33; no significant heterogeneity) than for cardiovascular and respiratory disease and diabetes (2.39, 2.45, and 1.63, respectively; no significant heterogeneity). CONCLUSIONS: Underlying comorbidity is consistently associated with increased mortality in patients with PUB. The number and type of comorbidities in patients with PUB should be carefully evaluated and factored into initial management strategies.
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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 | 0.015 | 0.046 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.021 | 0.043 |
| Bibliometrics | 0.008 | 0.008 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".