Severe Acute Respiratory Syndrome Coronavirus‐2 Infection in Children With Liver Transplant and Native Liver Disease
Bibliographic record
Abstract
OBJECTIVE: Increased mortality risk because of severe acute respiratory syndrome coronavirus-2 (SARS-CoV2) infection in adults with native liver disease (LD) and liver transplant (LT) is associated with advanced age and comorbid conditions. We aim to report outcomes for children with LD and LT enrolled in the NASPGHAN/SPLIT SARS-CoV2 registry. METHODS: In this multicenter observational cohort study, we collected data from 91 patients <21 years (LD 44, LT 47) with laboratory-confirmed SARS-CoV2 infection between April 21 and September 17, 2020. RESULTS: Patients with LD were more likely to require admission (70% vs 43% LT, P = 0.007) and pediatric intensive care unit (PICU) management (32% vs 4% LT, P = 0.001). Seven LD patients required mechanical ventilation (MV) and 2 patients died; no patients in the LT cohort died or required MV. Four LD patients presented in pediatric acute liver failure (PALF), 2 with concurrent multisystem inflammatory syndrome in children (MIS-C); all recovered without LT. Two LD patients had MIS-C alone and 1 patient died. Bivariable logistic-regression analysis found that patients with nonalcoholic fatty LD (NAFLD) (odds ratio [OR] 5.6, P = 0.02) and LD (OR 6.1, P = 0.01, vs LT) had higher odds of severe disease (PICU, vasopressor support, MV, renal replacement therapy or death). CONCLUSIONS: Although not directly comparable, LT recipients had lower odds of severe SARS-CoV2 infection (vs LD), despite immunosuppression burden. NAFLD patients reported to the registry had higher odds of severe SARS-CoV2 disease. Future controlled studies are needed to evaluate effective treatments and further stratify LD and LT patients with SARS-CoV2 infection.
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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 | 0.001 | 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 | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".