Resource Utilization for Acute Lower Gastrointestinal Hemorrhage: The Ontario GI Bleed Study
Bibliographic record
Abstract
OBJECTIVES: Acute lower gastrointestinal hemorrhage (LGIH) is a common indication for hospitalization. However, there are few published studies of related health care resource utilization. Resource utilization, length of stay (LOS) and direct medical costs were characterized in a cohort of patients admitted for nonmalignant LGIH to centres in Ontario. METHODS: Consecutive admissions for LGIH were identified at four Ontario hospitals. Profiles of resource utilization, LOS and estimates of direct medical costs were compiled through detailed chart review and adaptation of an administrative database. All centres were participants in the Ontario Case Cost Project. Linear regression models of log-transformed data were constructed to identify demographic variables predictive of LOS and case cost. RESULTS: Among 124 patients enrolled (mean age 58.8 years) the average case cost was dollars 4832 (SD dollars 7187) for 7.5 days in hospital (SD 12.0). Diverticular disease was the bleeding source most often identified (34.6%), followed by hemorrhoids (13.7%) and ischemic colitis (9.7%). Older age and comorbid illness, specifically coronary artery disease (CAD), were associated with both increased LOS and higher case cost in univariate regression analyses. Age persisted as the lone independent predictor of LOS in the multivariate model (P<0.05, R2=0.076), and age and CAD were both independent predictors of cost (P<0.05, R2=0.109) in a stepwise multiple linear regression analysis. Neither sex nor nonsteroidal anti-inflammatory drug use predicted LOS or cost. CONCLUSIONS: Admissions for acute LGIH are associated with significant resource utilization, particularly among elderly patients with CAD.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".