Outcomes of Acute Gastrointestinal Bleeding in Patients With COVID-19: A Case-Control Study
Bibliographic record
Abstract
Background: Coronavirus disease 2019 (COVID-19) patients are at higher risk of acute gastrointestinal bleeding (AGIB) due to higher use of steroids, mechanical ventilation, and use of anticoagulation. We performed this study to compare outcomes of AGIB in COVID-19-positive patients and those without COVID-19 and AGIB. Methods: This was a case-control study including patients admitted from March 2020 to February 2021 with the diagnosis of AGIB. Patients were divided into two groups: COVID-19-positive and non-COVID-19 patients. Our primary outcomes were in-hospital or 30 days mortality and length of stay. Secondary outcomes were the rate of rebleeding, the need for intensive care unit (ICU) level of care, and the need for blood transfusion. Results: Eighteen COVID-19-positive patients and 54 matched non-COVID-19 patients were included. The COVID-19-positive patients less frequently had endoscopies performed (33.3% vs. 74.1%, P = 0.0059) and had greater steroid use (83.3% vs. 14.8%, P < 0.0001) compared to non-COVID-19 patients. ICU stays were more likely in the COVID-positive patients (odds ratio (OR): 20.41; 95% confidence interval (CI): 2.59 - 160.69; P = 0.004) as was longer hospital length of stay (OR: 1.08; 95% CI: 1.03 - 1.13; P = 0.002). Mortality, readmission within 30 days, need for blood transfusion, and having rebleeding during the admission did not differ for COVID-19 and non-COVID-19 patients. Conclusion: COVID-19 patients with AGIB are more likely to require ICU admission and had a longer length of stay. Despite the significantly lower rate of endoscopic procedures performed in patients with COVID-19, need for blood transfusion, mortality and rebleeding were not significantly different.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".