Respiratory syncytial virus (RSV) prophylaxis in special populations
Bibliographic record
Abstract
Objective: To compare palivizumab utilization and compliance, and respiratory infection (RI) outcomes in subgroups of infants at high risk for RSV within the Canadian Registry Database. Methods: A prospective, observational, registry of infants at 29 sites who received ≥1 dose of palivizumab during the 2006-2010 RSV seasons. Utilization and RI outcomes were collected monthly over the full course of palivizumab. Infants ≤35 completed weeks gestational age without medical conditions who met standard approval criteria (Group 1) were compared to those at high risk of RI due to underlying medical illnesses (Group 2). Results: There were more infants in Group 1 (n=4880, 84%) than Group 2 (n=952, 16%). Group 2 included Down syndrome (20.2%), upper airway anomalies (18.5%), pulmonary disorders (13.3%), cystic fibrosis (12.3%), neuromuscular impairment (8.2%), multiple system disorders (6.1%), cardiac disorders (2.7%), immunocompromise (1.8%), and miscellaneous disorders (16.9%). From 2006-2010, the proportion of Group 2 infants increased 4-fold from 5.6% (69/1224) to 19.1% (462/2413). Group 2 was older at enrollment (10.2±9.2 vs 3.5±3.1 months, p<0.005), had more advanced gestational age (35.9±6.0 vs. 30.9±5.4 weeks, p<0.005) and had higher RI (9.0% vs. 4.2%, p<0.0005) and RSV hospitalization (2.35% vs 1.32%, p=0.003) rates. Group 2 infants tended to be less compliant with treatment (69.4% vs. 72.8%, p=0.048). Group (p=0.015) was an independent predictor of RSV hospitalization over compliance (p=0.951; model: χ2=5.273, df=1, p=0.022). Conclusion: Results imply that infants with underlying medical disorders, though not currently approved for prophylaxis, are at an elevated risk for both RI and RSV hospitalization.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".