Patient-important upper gastrointestinal bleeding in the ICU: A mixed-methods study of patient and family perspectives
Bibliographic record
Abstract
INTRODUCTION: The objective of this study was to create a definition of patient-important upper gastrointestinal bleeding during critical illness as an outcome for a randomized trial. DESIGN: This was a sequential mixed-methods qualitative-dominant multi-center study with an instrument-building aim. In semi-structured individual interviews or focus groups we elicited views from survivors of critical illness and family members of patients in the intensive care unit (ICU) regarding which features indicate important gastrointestinal bleeding. Quantitative demographic characteristics were collected. We analyzed qualitative data using inductive content analysis to develop a definition for patient-important upper gastrointestinal bleeding. SETTING: Canada and the United States. PARTICIPANTS: 51 ICU survivors and family members of ICU patients. RESULTS: Participants considered gastrointestinal bleeding to be important if it resulted in death, disability, or prolonged hospitalization. The following also signaled patient-important upper gastrointestinal bleeding: blood transfusion, vasopressors, endoscopy, CT-angiography, or surgery. Whether an intervention evinced concern depended on its effectiveness, side-effects, invasiveness and accessibility; contextual influences included participant familiarity and knowledge of interventions and trust in the clinical team. CONCLUSIONS: Survivors of critical illness and family members described patient-important upper gastrointestinal bleeding differently than current definitions of clinically-important upper gastrointestinal bleeding.
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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 | 0.039 | 0.036 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.004 | 0.002 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.001 | 0.002 |
| 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".