Lower Respiratory Tract Infections Following Respiratory Syncytial Virus Monoclonal Antibody Nirsevimab Immunization Versus Placebo: Analysis From a Phase 3 Randomized Clinical Trial (MELODY)
Bibliographic record
Abstract
BACKGROUND: Nirsevimab is an extended half-life, highly potent, anti-respiratory syncytial virus (RSV) fusion protein neutralizing monoclonal antibody with efficacy against RSV-associated medically attended (MA) lower respiratory tract infection (LRTI) in infants and medically vulnerable children (aged ≤24 months). This post hoc exploratory analysis examined the incidence of LRTI from RSV and other respiratory pathogens during MELODY: a 2:1 randomized, double-blind, placebo-controlled, phase 3 study of nirsevimab in healthy term and late preterm (ie, gestational age ≥35 weeks) infants entering their first RSV season. METHODS: A total of 3012 participants were randomized to nirsevimab (n = 2009) or placebo (n = 1003). Nasopharyngeal swabs were collected from infants who presented with an LRTI and tested for 22 different respiratory pathogens using the BioFire® Respiratory 2.1 Panel. Incidence of RSV and non-RSV MA-LRTIs through day 511 and LRTI severity were assessed. RESULTS: A total of 852 nasopharyngeal swabs were collected from 561 participants through day 511: 519 swabs from 337 nirsevimab participants and 333 swabs from 224 placebo participants. RSV and non-RSV infections were detected in 193 of 852 (22.7%) and 55 of 852 (64.7%) swabs, respectively. RSV infection rates were lower with nirsevimab compared with placebo, including RSV-rhinovirus/enterovirus coinfections. Rates of other viral infections were similar between study arms. Approximately 70% of single RSV infections and RSV coinfections were adjudicated as mild, and 26.2% of single RSV infections and 24.5% of RSV coinfections required hospitalization. CONCLUSIONS: Nirsevimab protected against RSV single and coinfections, with no evidence of replacement of RSV with other respiratory viruses. Clinical Trials Registration. NCT03979313.
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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 | 0.004 | 0.003 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.003 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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".