Maternal outcomes in pregnancies affected by varicella zoster virus infections: Population‐based study on 7.7 million pregnancy admissions
Bibliographic record
Abstract
AIM: Previous estimates of the incidence of varicella zoster virus (VZV) pneumonia and maternal death associated with VZV infection among the pregnant population have varied considerably and been based predominantly on reports from case series. We sought to measure the incidence of VZV-related morbidity and mortality to provide more representative population estimates. METHODS: We carried out a large cohort study on all births using the United States Healthcare Cost and Utilization Project-Nationwide Inpatient Sample database between 2003 and 2010. Descriptive statistics were used to measure baseline characteristics and outcomes of women with VZV infection. Multivariate logistic regression analyses were used to identify risk factors for the development of VZV-related morbidity and mortality. RESULTS: We identified 935 patients admitted for VZV infection among 7.7 million pregnancy admissions, representing an incidence of 1.21 cases/10 000 pregnancies (95% confidence interval [CI], 1.13-1.29). The incidence of VZV pneumonia was 2.5% (95% CI, 1.6-3.7). No maternal deaths were recorded during the 8-year study period. There were no significant risk factors identified for those who developed VZV pneumonia compared to those who had an uncomplicated VZV infection during pregnancy. CONCLUSION: The incidence of VZV pneumonia and VZV infection associated with maternal death is significantly lower than previously estimated and may reflect better immunization and earlier interventions.
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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 | 0.003 |
| 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 | 0.001 | 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".