Acute severe hepatitis as a presenting symptom in clinically stable patients admitted with SARS-CoV-2 Omicron infection
Bibliographic record
Abstract
BACKGROUND: Suggested mechanisms for SARS-CoV-2 direct liver infection have been proposed by others to involve both cholangiocytes and hepatocytes. Early clinical studies have highlighted abnormal liver biochemistry with COVID-19 infection as often not being severe, with elevated liver enzymes <5X the upper limit of normal. METHODS: Liver enzymes were evaluated and compared in patients admitted with a diagnosis of COVID-19 in a deidentified Internal Medicine-Medical Teaching Unit/hospitalist admission laboratory database. Comparisons in the incidence of severe liver injury (alanine aminotransferase >10 times upper limit of normal) were made for patients with pre-Omicron SARS-CoV-2 (November 30, 2019, to December 15, 2021) and Omicron SARS-CoV-2 (December 15, 2021, to April 15, 2022). Comprehensive hospital health records were also reviewed for the 2 patient cases discussed. One patient had a liver biopsy that was evaluated with H&E and immunohistochemistry staining using an antibody against COVID-19 spike protein. RESULTS: The evaluation of a deidentified admissions laboratory database found the incidence of severe liver injury was 0.42% with Omicron versus 0.30% with pre-Omicron variants of COVID-19. In both patient cases discussed, abnormal liver biochemistry and a negative comprehensive workup strongly suggest COVID-19 as the cause of severe liver injury. In the one patient with liver biopsy, immunohistochemistry staining suggests SARS-CoV-2 presence in the portal and lobular spaces in association with immune cell infiltration. CONCLUSIONS: The Omicron variant of SARS-CoV-2 should be considered in the differential diagnosis of severe acute liver injury. Our observation suggests that this new variant, either through direct liver infection and/or mediating immune dysfunction, can result in severe liver injury.
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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 | 0.001 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 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 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".