Clinical Risk Characteristics of Upper Gastrointestinal Hemorrhage Severity: A Multivariable Risk Analysis
Bibliographic record
Abstract
BACKGROUND: Upper gastrointestinal hemorrhage (UGIH) is one of the common clinical manifestations encountered in most emergency departments. Patient characteristics indicating UGIH severity in developing countries may be different from those in developed countries. The present study was designed to explore clinical prognostic indicators for UGIH severity. METHODS: A retrospective cohort study was conducted in a university affiliated tertiary hospital in Kamphaeng Phet, Thailand. Medical folders of patients with UGIH were reviewed. Patients were grouped into 3 severity levels, based on criteria proposed by The American College of Surgeon. Pre-defined prognostic indicators were compared. The prognostic indicators for UGIH severity were analyzed by a multivariable continuation ratio ordinal logistic regression and presented with odds ratios. RESULTS: From 1,043 eligible medical folders, 984 (94.3%) complete folders were used in analysis. There were 241, 631 and 112 patients in the mild, moderate and severe UGIH groups. Six independent indicators of severe UGIH were, hemoglobin < 100 g/dL (OR = 13.82, 95% CI = 9.40 to 20.33, P < 0.001), systolic blood pressure < 100 mmHg (OR = 11.01, 95% CI = 7.41 to 16.36, P < 0.001), presence of hepatic failure (OR = 5.50, 95% CI = 1.14 to26.64, P = 0.037), presence of cirrhosis (OR = 2.03, 95% CI = 1.32 to 3.11, P = 0.001), blood urea nitrogen ≥ 35 mmol/L (OR = 1.73, 95% CI = 1.25 to 2.40, P = 0.001), and pulse rate ≥ 100 per minute (OR = 1.72, 95% CI = 1.21 to 2.45, P = 0.003). CONCLUSIONS: Pulse rate ≥ 100 per minute, systolic blood pressure < 100 mmHg, hemoglobin < 10 g/dL, blood urea nitrogen ≥ 35 mmol/L, presence of cirrhosis and presence of hepatic failure are prognostic indicators for an increase in UGIH severity levels. They are potentially useful in UGIH risk stratification.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.005 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.002 |
| 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 teacher head, 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".