Liver transaminase concentrations in children with acute SARS-CoV-2 infection
Bibliographic record
Abstract
OBJECTIVE: To evaluate the relationship between SARS-CoV-2 infection and liver injury by comparing transaminase concentrations among children tested for SARS-CoV-2 and other respiratory viruses in pediatric emergency departments. DESIGN & METHODS: Eligible children were <18 years with suspected SARS-CoV-2, tested using molecular approaches in emergency departments between March 7, 2020, and June 15, 2021 (Pediatric Emergency Research Network), and between August 6, 2020, and February 22, 2022 (Pediatric Emergency Research Canada). We compared aspartate (AST) and alanine aminotransferase (ALT) concentrations at presentation for SARS-CoV-2 and other respiratory viruses through a multivariate linear regression model, with the natural log of serum transaminase concentrations as dependent variables. RESULTS: Of 16,892 enrolled children, 2,462 (14.6%) had transaminase concentrations measured; 4318 (25.6%) were SARS-CoV-2 positive, and 3932 (23.3%) were tested for additional respiratory viruses. Among study participants who had additional respiratory virus testing performed, the most frequently identified viruses were enterovirus/rhinovirus [8.7% (343/3,932)], respiratory syncytial virus [4.6% (181/3,932)], and adenovirus [2.6% (103/3,932)]. Transaminase concentrations were elevated in 25.6% (54/211) of children with isolated SARS-CoV-2 detection and 21.6% (117/541) of those with no virus isolated; P = 0.25. In the multivariable model, isolated SARS-CoV-2 detection was not associated with elevated ALT (adjusted geometric mean ratio (IU/L): 0.96; 95%Confidence Interval (CI): 0.84, 1.08) or AST (adjusted geometric mean ratio (IU/L): 1.03; 95%CI: 0.92, 1.16) concentrations, with negative respiratory panel as the referent group. Ninety-day follow-up was completed in 82.2% (3,550/4,318) of SARS-CoV-2 positive children; no cases of new-onset liver disease were reported. CONCLUSION: Among those tested, transaminase concentrations did not vary between SARS-CoV-2-positive children and those with a negative respiratory viral panel. In multivariate analysis, SARS-CoV-2 infection was not associated with increased initial transaminase concentrations compared to other respiratory viruses.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.004 |
| 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 | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".