Comparative Analysis of Incidence and Outcomes of Acute Hepatitis A (HAV) and B Virus Infections (HBV) in Children Aged ≤ 20 years in the United States (US)
Bibliographic record
Abstract
HAV and HBV are amongst the most common vaccine preventable diseases and may be associated with morbidity and health care costs. The epidemiology and impact of acute HAV and HBV infection in pediatric hospitalizations is poorly defined relative to other populations. A cohort study was undertaken with the 2012 Kids’ Inpatient Database that encompasses a stratified random sample of community and non-rehabilitation based hospitalizations across the US of pediatric patients aged ≤ 20 years. The primary outcome was incidence of acute HAV and HBV-related hospitalizations. Risk factors of age, sex, and race, and outcomes of length of stay (LOS), and costs were compared between persons with HAV and HBV infection. ICD-9 codes of 070.0–070.31 were utilized to capture acute HAV and HBV cases. Continuous and discrete outcomes between HAV and HBV were calculated with linear and logistic regression (with weighting), respectively. A total of 424 cases of acute viral hepatitis A (48.3%), B (50.5%), and co-infection (1.2%) occurred, corresponding to a national overall incidence rate of 8.9 cases per 100,000 persons (aged ≤ 20 years). HBV acquisition was associated with a higher mean age than HAV (15.4 vs. 13.1 years, P < 0.001). A greater proportion of patients with HBV compared with HAV were female (70.1% vs. 41.2%, P < 0.001). The distribution of race was significantly different with disproportionate numbers of HBV compared with HAV cases in Blacks and Asians (P < 0.001). LOS (6.93 vs. 4.38 days, P = 0.02) and hospitalization costs ($58,211 vs. $30,758, P = 0.03) were both significantly greater in HBV than HAV cases. We demonstrated that acute HAV and HBV cases differed in demographic factors of sex, age, and race, and that HBV was associated with greater LOS and costs. Although the incidence was low, enhanced vaccine efforts are indicated for further prevention of these infections in children. All authors: No reported disclosures.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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".