Association between disease severity and co-detection of respiratory pathogens in infants with RSV infection
Notice bibliographique
Résumé
Abstract BACKGROUND Respiratory syncytial virus (RSV) is the leading cause of hospitalisation associated with acute respiratory infection in infants and young children, with substantial disease burden globally. The impact of additional respiratory pathogens on RSV disease severity is not completely understood. OBJECTIVES The objective of this study was to explore the associations between RSV disease severity and the presence of other respiratory pathogens. METHODS Nasopharyngeal swabs were prospectively collected from two infant cohorts: a prospective longitudinal birth cohort study and an infant cross-sectional study recruiting infants <1 year of age with RSV infection in Spain, the UK, and the Netherlands during 2017–20 [part of the REspiratory Syncytial virus Consortium in EUrope (RESCEU) project]. The samples were sequenced using targeted metagenomic sequencing with a probe set optimised for high-resolution capture of sequences of over 100 pathogens, including all common respiratory viruses and bacteria. Viral genomes and bacterial genetic sequences were reconstructed. Associations between clinical severity and presence of other pathogens were evaluated after adjusting for potential confounders, including age, gestational age, RSV viral load, and presence of comorbidities. RESULTS RSV was detected in 433 infants. Nearly one in four of the infants (24%) harboured at least one additional non-RSV respiratory virus, with human rhinovirus being the most frequently detected (15% of the infants), followed by seasonal coronaviruses (4%). In this cohort, RSV-infected infants harbouring any other virus tended to be older (median age: 4.3 vs. 3.7 months) and were more likely to require intensive care and mechanical ventilation than those who did not. Moraxella, Streptococcus , and Haemophilus species were the most frequently identified target bacteria, together found in 392 (91%) of the 433 infants ( S. pneumoniae in 51% of the infants and H. influenzae in 38%). The strongest contributors to severity of presentation were younger age and the co-detection of Haemophilus species alongside RSV. Across all age groups in both cohorts, detection of Haemophilus species was associated with higher overall severity, as captured by ReSVinet scores, and specifically with increased rates of hospitalisation and respiratory distress. In contrast, presence of Moraxella species was associated with lower ReSVinet scores and reduced need for intensive care and mechanical ventilation. Infants with and without Streptococcus species (or S. pneumoniae in particular) had similar clinical outcomes. No specific RSV strain was associated with co-detection of other pathogens. CONCLUSION Our findings provide strong evidence for associations between RSV disease severity and the presence of additional respiratory viruses and bacteria. The associations, while not indicating causation, are of potential clinical relevance. Awareness of coexisting microorganisms could inform therapeutic and preventive measures to improve the management and outcome of RSV-infected infants.
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,001 | 0,003 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,001 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,001 | 0,000 |
| Science ouverte | 0,000 | 0,001 |
| Intégrité de la recherche | 0,001 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,002 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».