Hospitalization for Respiratory Syncytial Virus Illness in Down Syndrome Following Prophylaxis With Palivizumab
Bibliographic record
Abstract
BACKGROUND: Down syndrome (DS) is a risk factor for respiratory syncytial virus (RSV) hospitalization, but little is known about prophylaxis in these children. METHODS: CARESS is a prospective registry of children who received ≥1 dose of palivizumab during the 2006-2012 RSV seasons across 32 sites in Canada. The objective was to compare respiratory illness hospitalization and RSV hospitalization (RSVH) hazard ratios in DS children aged <2 years who received palivizumab versus children who received prophylaxis for standard indications (SI) and for other medical illnesses (MI). RESULTS: 13,310 children were enrolled; DS (600; 4.5%), SI (11,081; 83.3%) and MI (1629, 12.2%), with DS children increasing over the duration from 0.1% (2006) to 4.5% (2012). Participants were significantly different in mean birth weight, gestational and enrollment age and risk factors. Children in each group received an average of 4.3 ± 1.4 (DS), 4.1 ± 1.6 (SI) and 4.5 ± 1.4 (MI) palivizumab injections per RSV season, with DS, differing significantly from SI [F(2, 13,307) = 43.6, P = 0.01] but not MI [F(2, 13 307) = 43.6, P = 0.07]. Compliance rates were similar across the groups. While a significantly greater proportion of SI children had RIHs compared with DS, [hazard ratio: 0.64 (0.48-0.84); P = 0.001] hazard ratios were similar for DS and MI. RSVH incidence rates were: 1.53%, 1.45% and 2.27% for DS, SI and MI, respectively. Neither group nor compliance affected time to RSVH. CONCLUSIONS: The proportion of DS children who received palivizumab in CARESS has increased almost 45-fold. RSVH rates were low in DS following prophylaxis and hazards were similar to those found in SI and MI.
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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 | 0.000 | 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) | 0.001 | 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".