Antibiotic Treatment of Wheezing in Children With Asthma: What Is the Practice?
Notice bibliographique
Résumé
Kozyrskyj AL, Dahl ME, Ungar WJ, Becker AB, Law BJ. Pediatrics. 2006;117(6). Available at: www.pediatrics.org/cgi/content/full/117/6/e1104 PURPOSE OF THE STUDY. To evaluate time trends and determinants of antibiotic use in children with wheezing episodes. STUDY POPULATION. Children with asthma were identified from population-based health care and prescription databases in Manitoba, Canada, during fiscal years 1995–2001. Asthma was defined as at least 1 physician or hospital visit for asthma or at least 1 prescription for an asthma drug. METHODS. In this descriptive study, using general estimating equations, annual population-based rates of antibiotic prescriptions for wheezing episodes were modeled by age and antibiotic class. Population-based rates for antibiotic use for wheezing were defined as the annual number of antibiotic prescriptions dispensed per 1000 children with asthma. Linear hierarchical rankings were used to calculate odds ratios for receiving an antibiotic prescription according to child demographics and physician factors. RESULTS. Antibiotic prescription rates for wheezing decreased 28% from 708 prescriptions per 1000 children with asthma in 1995 to 511 prescriptions per 1000 children with asthma in 2001. However, an increase in prescriptions was observed for broader-spectrum macrolides (azithromycin and clarithromycin) in preschool-aged children (a 15-fold increase) and in all children (an eightfold increase). Immediate prescriptions (defined as within 2 days of the visit) were given in 23% of physician encounters for wheezing. Sixty-four percent of the visits resulted in an antibiotic prescription within 7 days of the visit. General practitioners prescribed antibiotics for wheezing more often than pediatricians, as did older compared with younger physicians. Physicians trained outside Canada and the United States were 40% more likely to prescribe antibiotics. Visits for younger children and visits during winter months more frequently resulted in antibiotic prescriptions. CONCLUSIONS. Antibiotic prescription rates for wheezing episodes declined in the late 1990s, but broader-spectrum antibiotic prescription rates increased. REVIEWER COMMENTS. Antibiotic use in asthma has gained renewed interest because of the antiinflammatory properties of certain antibiotic classes such as the macrolides. Coupled with the better-tolerated and more-convenient dosing of newer antibiotics (primarily azithromycin), they may provide a future therapeutic option in the treatment of asthma. Nonetheless, little is published about the prescribing patterns of antibiotics for wheezing and asthma. Coexisting maladies such as otitis or pneumonia are not specifically addressed in this publication but may account for the increase in prescription rates at 7 days postvisit. In addition, the possible contribution of antibiotics in the inception of asthma by participating in the “hygiene hypothesis” provides additional interest in these data. Finally, the perceived dangers of resistance with antibiotic use continue to make their use controversial in the treatment of asthma exacerbations.
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 | 0,006 | 0,032 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,001 |
| Bibliométrie | 0,001 | 0,003 |
| Études des sciences et des technologies | 0,001 | 0,001 |
| Communication savante | 0,002 | 0,003 |
| Science ouverte | 0,001 | 0,001 |
| Intégrité de la recherche | 0,002 | 0,002 |
| 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 ».