Systemic inflammatory response and serum lipopolysaccharide levels predict multiple organ failure and death in alcoholic hepatitis
Bibliographic record
Abstract
UNLABELLED: Alcoholic hepatitis (AH) frequently progresses to multiple organ failure (MOF) and death. However, the driving factors are largely unknown. At admission, patients with AH often show criteria of systemic inflammatory response syndrome (SIRS) even in the absence of an infection. We hypothesize that the presence of SIRS may predispose to MOF and death. To test this hypothesis, we studied a cohort including 162 patients with biopsy-proven AH. The presence of SIRS and infections was assessed in all patients, and multivariate analyses identified variables independently associated with MOF and 90-day mortality. At admission, 32 (19.8%) patients were diagnosed with a bacterial infection, while 75 (46.3%) fulfilled SIRS criteria; 58 patients (35.8%) developed MOF during hospitalization. Short-term mortality was significantly higher among patients who developed MOF (62.1% versus 3.8%, P < 0.001). The presence of SIRS was a major predictor of MOF (odds ratio = 2.69, P = 0.025) and strongly correlated with mortality. Importantly, the course of patients with SIRS with and without infection was similar in terms of MOF development and short-term mortality. Finally, we sought to identify serum markers that differentiate SIRS with and without infection. We studied serum levels of high-sensitivity C-reactive protein, procalcitonin, and lipopolysaccharide at admission. All of them predicted mortality. Procalcitonin, but not high-sensitivity C-reactive protein, serum levels identified those patients with SIRS and infection. Lipopolysaccharide serum levels predicted MOF and the response to prednisolone. CONCLUSION: In the presence or absence of infections, SIRS is a major determinant of MOF and mortality in AH, and the mechanisms involved in the development of SIRS should be investigated; procalcitonin serum levels can help to identify patients with infection, and lipopolysaccharide levels may help to predict mortality and the response to steroids.
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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 | 0.000 | 0.002 |
| 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) | 0.001 | 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".