MELD score and antibiotics use are predictors of length of stay in patients hospitalized with hepatic encephalopathy
Bibliographic record
Abstract
BACKGROUND: Hepatic encephalopathy (HE) represents a significant burden to the healthcare system. The aim of this study was to determine factors influencing the hospital length of stay among patients hospitalized with HE. METHODS: A data warehouse query was performed to identify 316 patients with a first hospitalization during which HE occurred, between April 2010 and February 2012. Baseline and hospitalization characteristics were collected with IRB approval. A negative binomial multivariable model was used to control for potential confounders on the length of hospitalization. RESULTS: Median age was 59 years, and 60.4% of admitted patients were male. The median MELD score was 22 (IQR: 17-28). Median length of stay was 8 days (IQR: 3.25-14.25). After controlling for MELD score, female gender (2.2 days; p = 0.04), being initially admitted for a reason other than HE (liver-related: 7.6 days; p < 0.01 and non liver-related 10.7 days; p < 0.01) and receiving antibiotics other than rifaximin (10.5 days; p < 0.01) were associated with longer length of stay whereas hepatitis C (-3.1 days; p < 0.01) was associated with a shorter length of stay. CONCLUSIONS: MELD score, gender, use of antibiotics other than rifaximin, reason for admission and hepatitis C are predictors readily available in clinic that can help identify patients at risk for longer length of stay.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".