Hepatitis C is a predictor of acute liver injury among hospitalizations for acetaminophen overdose in the United States
Why this work is in the frame
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Bibliographic record
Abstract
UNLABELLED: Acute liver injury (ALI) following acetaminophen overdose (AO) occurs in less than 10% of cases, but that risk is increased among alcoholics and those with chronic alcoholic liver disease. We sought to assess whether coexistent hepatitis C virus (HCV) infection potentiated the hepatotoxic effects of acetaminophen. We queried the Nationwide Inpatient Sample (1998-2005), a 20% sample of U.S. hospitals, to identify admissions for AO using International Classification of Diseases, Ninth Revision, Clinical Modification (ICD-9-CM) codes. Outcomes were development of ALI (ICD-9-CM: 570.0, 572.2, 573.3), in-hospital mortality, severe liver failure, and resource utilization. There were 42,781 admissions for AO in the sample, yielding a national estimate of 210,436 AO hospitalizations. HCV prevalence increased from 0.5% to 1.5% between 1998 and 2005 (P < 0.0001). The rate of ALI was 7.2%. After adjusting for confounders and excluding patients with cirrhosis, the risk of ALI increased with HCV (adjusted odds ratio [aOR] 1.80; 95% confidence interval [CI]: 1.30-2.48), nonalcoholic fatty liver disease (aOR 7.43; 95% CI: 3.30-16.7), alcoholic liver disease (aOR 6.46; 95% CI: 4.53-9.21), and malnutrition (aOR 3.84; 95% CI: 2.61-5.65). HCV was associated with greater risk of progression to severe liver failure (aOR 3.55; 95% CI: 1.88-6.70). Crude mortality was higher in patients with HCV compared to those without HCV (2.1% versus 0.9%, P = 0.01); patients with ALI had an overall mortality of 8.6%. Length of stay was longer in patients with HCV (4.0 versus 2.6 days, P < 0.0001). Admissions with coexistent HCV also incurred two-fold higher hospital charges than those that did not ($21,400 versus $11,400, P < 0.0001). CONCLUSION: Our retrospective analysis suggests that patients with HCV may be at increased risk of ALI following AO. These findings warrant further confirmation in prospective studies.
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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 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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 it