RSV hospitalization in infants with neuromuscular disease in the Canadian registry of palivizumab after prophylaxis (2005-2012)
Bibliographic record
Abstract
OBJECTIVES: Infants with neuromuscular impairment (NMI) at high risk of severe respiratory syncytial virus (RSV) infection;may receive palivizumab.We compared respiratory illness (RIH) and RSV positive hospitalization (RSVH) rates in NMI infants with prophylaxis versus those prophylaxed for standard indications (SD), and other underlying medical disorders (MD) through the Canadian Registry of Synagis®.(CARESS) METHODS: CARESS is a prospective, observational study in 32 sites across Canada for infants with >1 dose of palivizumab prophylaxis in 2005-2012 seasons. Compliance, RI data collected monthly. RESULTS: 13,310 infants in database. 153 had NMI (1.1%), 11239 SD (84.4%), 1918 MD (14.4%). Enrolment age, gestational age, birth weight, proportions of Caucasians, daycare attendance, smoking exposure, siblings, multiple birth, >5 individuals in the household, history of atopy, significantly different (p<0.05) across the three groups. The NMI group received a smaller proportion of expected number of injections than SD or MD (58.8% versus 65.8% and 67.9%, p=0.032).RIH and RSVH prevalence higher in NMI than SD or MD (RIH; 18.3% versus 9.6% and 5.9%, p<0.0005) (RSVH; 5.23% versus 1.56% and 1.21%, p[<0.0005). Cox proportional hazard analysis showed increased risk of RSVH in NMI patients compared to SD (hazard ratio=4.33, 95%CI 1.9-9.7, p<0.0005), after adjusting for covariates (injection compliance, daycare attendance, having siblings, exposure to smoking and crowding). CONCLUSIONS: Infants with NMI were at higher risk of RIH and RSVH compared to SD or MD. These data support palivizumab prophylaxis in NMI, as recommended by international pediatric bodies.
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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 | 0.001 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.002 | 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".