Effectiveness of Palivizumab in High-risk Infants and Children
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
BACKGROUND: Infants with premature birth ≤35 weeks gestational age, chronic lung disease of prematurity and congenital heart disease are at an increased risk for lower respiratory tract infections and hospitalization from respiratory syncytial virus (RSV), which has been shown in randomized trials to be prevented by palivizumab. However, palivizumab effectiveness (PE) has not been studied in a large clinical setting. METHODS: A multicenter study among high-risk US and Canadian children younger than 24 months hospitalized with lower respiratory tract infection and whose nasopharyngeal aspirates were tested for human metapneumovirus (HMPV) and RSV were the subjects of the trial. We conducted a test-negative case-control study in these subjects to determine PE. We used an inverse propensity score weighted (IPSW) multiple logistic regression model to adjust PE. RESULTS: Palivizumab was used in 434 (51%) of 849 eligible children. RSV was identified in 403 (47%) children. The unadjusted PE was 43% [95% confidence interval (CI), 34%-51%)]. After IPSW adjustment, the adjusted PE was 58% (95% CI, 43%-69%). Palivizumab prevented intensive care unit admissions (PE, 62%; 95% CI, 35%-78%). PE for 29-35 weeks gestational age and ≤6 months of chronologic age without chronic lung disease of prematurity or congenital heart disease was 74% (95% CI, 56%-85%). CONCLUSIONS: Using a test-negative case-control design with RSV molecular detection, palivizumab is shown to prevent RSV hospitalizations and intensive care unit admissions in high-risk infants.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it