Neonatal Herpes Simplex Virus Infection Among Medicaid-Enrolled Children: 2009–2015
Bibliographic record
Abstract
OBJECTIVES: To examine the incidence, mortality, and health care use related to neonatal herpes simplex virus (HSV) infection. METHODS: A retrospective longitudinal cohort study using a multistate Medicaid claims database. We identified neonates hospitalized with HSV infection from 2009 to 2015 by using discharge diagnosis codes and managed them for 6 months after discharge. Incidence rates were corrected for the imperfect sensitivity and specificity of thediagnosis codes for identifying HSV infection. RESULTS: Of 2 107 124 births from 2009 to 2015, 900 neonates were identified with HSV infection, with a corrected incidence rate of 4.5 (95% confidence interval [CI]: 4.2–4.8) per 10 000 births. The yearly disease incidence increased by 56%, from 3.4 (95% CI: 2.8–4.2) per 10 000 births (or 1 in 2941 births) in 2009 to 5.3 (95% CI: 4.6–6.1) per 10 000 births (or 1 in 1886 births) in 2015 (P < .001). Of the 900 neonates with HSV infection, 54 (6.0% [95% CI: 4.4%–7.6%]) died during the index hospitalization; there was no increase in the yearly mortality rate. Of the 692 (81.2%) infants with follow-up data, 316 (45.7%) had an emergency department visit, and 112 (16.2%) had a hospital readmission. Total payments at 6 months amounted to $60 620 431, a median of $87 602 per case of neonatal HSV infection. CONCLUSIONS: We observed an increase in neonatal HSV infection incidence over a recent 7-year period in a Medicaid population. Associated health care use and payments were substantial. Public health interventions targeting disease prevention and early diagnosis are needed.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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) | 0.001 | 0.002 |
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; both teacher heads agree on what is shown here.
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".