Distinct Patterns of Liver Chemistry Changes in Pediatric Acute Hepatitis of Unknown Origin and COVID-19 Patients: A Systematic Review
Bibliographic record
Abstract
In 2021 and 2022, there were noted to be clusters of pediatric acute hepatitis of unknown origin (AHUO) occurring across the globe. While there was not necessarily a global increase in cases, understanding the pattern of liver injury in AHUO is crucial to properly identify cases of this unexplained phenomenon, especially since it occurred simultaneously with a global resurgence of COVID-19. The objective of this study was to contrast the patterns in liver-relevant biochemical data from COVID-19 patients and AHUO. Studies reporting liver chemistries for cases of AHUO and COVID-19 were identified by a systematic review and search of the literature. For each case, alanine aminotransferase (ALT), aspartate aminotransferase (AST), total bilirubin, direct bilirubin, and international normalized ratio (INR) levels were extracted as available. These were normalized to multiples of the upper limit of normal by patient age. There were statistically significant greater elevations of ALT and AST in patients with AHUO than in those with COVID-19. Only a subset of patients with COVID-19 had an AST or ALT greater than the normal range. INR elevation could be substantial for both conditions but was also statistically higher in the AHUO group. Liver chemistry changes were not statistically correlated with age. The pattern of liver chemistry changes between AHUO and COVID-19 have some distinctions, which suggests that AHUO is not a phenomenon driven primarily by SARS-CoV-2 infection alone. Differentiating AHUO and COVID-19 would be challenging based on patterns of liver chemistry changes alone.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 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".