Acute Fulminant Hepatic Failure, Encephalopathy and Early CT Changes
Bibliographic record
Abstract
BACKGROUND: Acute fulminant hepatic failure (AFHF) is common in tertiary care centres with transplant facilities. Cerebral edema frequently threatens the lives of such patients. We reviewed our cases of AFHF, noting the incidence of cerebral edema with serial CT scans and factors associated with mortality. METHODS: Patients were captured through HmRI classification of acute liver/hepatic failure. Chart review included tabulation of: demographics, INR; serum bilirubin, creatinine, albumin; in-hospital mortality. Computed tomogram (Ct) scans were re-read with blinding to clinical information and catalogued for changes in sulcal markings, ventricular size and grey-white differentiation (GWD). INCLUSION CRITERIA: age equal to or greater than 16 years, encephalopathy, hepatic failure within eight weeks of onset of liver disease, CT scans of head performed. RESULTS: Of our 25 cases with AFHF, acetaminophen toxicity was the most common etiology (nine cases). Twelve of the 25 patients (48%) had cerebral edema on CT, including eight of the nine (89%) with acetaminophen toxicity. Decrease in sulcal markings and ventricular size preceded conspicuous alterations in GWD. Fourteen died, including all 12 with cerebral edema, although death was due to herniation in only one patient. None of the hematological or biochemical variables correlated significantly with mortality. CONCLUSIONS: Acetaminophen toxicity is a common cause of AFHF; this combination has a strong association with cerebral edema. Cerebral edema can be detected in its early stages and followed by baseline and serial CT scans. This facilitates management to prevent fatal brain herniation.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".