91 The impact of non-pharmaceutical public health interventions on hospital admissions and mortality from common causes of pediatric respiratory distress: a single center perspective
Notice bibliographique
Résumé
Abstract Background In response to the COVID-19 pandemic, jurisdictions around the world implemented policies to reduce COVID-19 transmission through public masking, travel restrictions, and closure of non-essential businesses. Collectively known as non-pharmaceutical interventions (NPI), these strategies reliably reduce the spread of COVID-19. International data suggests NPI also reduce hospitalizations for pediatric respiratory infections and their consequences, particularly asthma exacerbation. However, few Canadian studies have examined the impact of NPI on hospitalizations for common causes of pediatric respiratory distress. Objectives This study describes the impact of NPI on admissions for bronchiolitis, pneumonia, and asthma at a Canadian pediatric tertiary care centre. Design/Methods A retrospective chart review was conducted including all pediatric patients <18 years admitted to the general pediatric and pediatric intensive care units with bronchiolitis, pneumonia, or asthma. Data regarding diagnosis, length of hospitalization, and mortality were collected before (September 2016-March 2020) and in the 6 months after provincial NPI implementation (March 2020-September 2020). NPI were present throughout this period, however, specific measures varied due to evolving public health orders. Chi-squared testing was conducted to describe the impact of NPI on number of admissions, length of hospitalization, and mortality. Results Participants (n=1631) included 111 (6.8%) patients <1 month, 878 (53.8%) patients 1-23 months, 331 (20.3%) patients 24 months-4 years, and 311 (19.1%) patients ≥5 years. A mean of 205 patients were admitted every 6 months with respiratory distress (bronchiolitis, pneumonia, and/or asthma) prior to NPI implementation. During this timeframe, the 6-month mean admissions due to asthma, pneumonia, and bronchiolitis were 48, 56, and 101, respectively. In the 6 months following NPI implementation, there were 56 admissions for respiratory distress, including 15 for asthma, 19 for pneumonia, and 22 for bronchiolitis. Mean length of stay increased following the implementation of NPI from 8.49 to 11.68 days, whereas 6-month mean mortality decreased from two to zero deaths. Results did not attain statistical significance (p>0.05). Conclusion Results suggest NPI reduce hospitalizations and mortality from bronchiolitis, pneumonia, and asthma. Given the similar seasonality of these conditions, periodic use of NPI beyond the COVID-19 pandemic may reduce pediatric morbidity and mortality from common causes of respiratory distress. However, additional research is needed to describe the relationship between NPI and length of hospitalization. Future studies should also examine the impact of NPI on other pediatric infectious diseases to better characterize their utility.
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 | 0,002 | 0,007 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,002 |
| Bibliométrie | 0,002 | 0,002 |
| Études des sciences et des technologies | 0,001 | 0,001 |
| Communication savante | 0,002 | 0,001 |
| Science ouverte | 0,001 | 0,002 |
| Intégrité de la recherche | 0,001 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,005 | 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 ».