Current Opinions on Stress-Related Mucosal Disease Prevention in Canadian Pediatric Intensive Care Units
Bibliographic record
Abstract
OBJECTIVE: To describe current opinions about stress-related mucosal disease (SRMD) prevention in Canadian pediatric intensive care units (PICUs). METHODS: A 22-question survey covering several aspects of SRMD was sent to all identified PICU attendings in Canada. RESULTS: Sixty-eight percent of identified attendings completed the questionnaire. Thirty-eight percent were based in Quebec, 31% in Alberta, and 31% from other provinces. Most attendings (78%) had worked in a PICU for 6 years or more. When asked about risk factors for prescribing SRMD prevention drugs (more than 1 answer was accepted), the most popular answers were prior history of gastric ulceration/bleeding (33 respondents), coagulopathy (28 respondents), and major neurologic insult (18 respondents). Almost half of the attendings (48%) mentioned that they prescribe SRMD prophylaxis directly upon PICU admission to more than 25% of their patients. Forty-nine percent of respondents subjectively estimated that clinically significant upper gastrointestinal bleeding (UGIB; defined as UGIB associated with either hypotension, transfusion within 24 hours of the event, or death) occurred in less than 1% of their patients. Fifty-seven respondents (93%) used ranitidine as first-line therapy (average dose: 4.1 mg/kg/day, mainly intravenously). As second-line therapy, 32 attendings (52%) used pantoprazole and 13 (21%) used omeprazole. CONCLUSIONS: Despite the paucity of guidelines on SRMD prevention and the low reported incidence of clinically significant UGIB, SRMD prevention is frequently used in Canadian PICUs. Ranitidine is the first-line drug used by most attendings.
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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 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.003 | 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) | 0.003 | 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".