61 Adherence to Daily Medication Regimens in Pediatric Asthma: Do Socioeconomic Status and Daily Dose Frequency have an Impact?
Notice bibliographique
Résumé
Abstract Primary Subject area Respirology Background Children with asthma from lower socioeconomic status (SES), and those with poor adherence to controller medications have worse health outcomes, including higher rates of exacerbations and hospitalizations. Simpler medication regimens could potentially improve medication adherence and asthma control. Objectives We aimed to determine if: (1) medication adherence (proportion of prescribed days covered [PPDC]) and primary non-adherence (PPDC = 0%) varied by SES; and if (2) there was an interaction between SES and daily dose frequency on adherence. Design/Methods This retrospective cohort study included children 2-17 years old followed at the asthma clinic of a large Canadian pediatric hospital between 2011 and 2020. Patients were prescribed one of five medication regimens that included one or more of the following medication classes: inhaled corticosteroids (ICS), long-acting beta-agonists (LABA) and leukotriene receptor antagonists (LTRA). Primary outcome was medication adherence, using the PPDC: the number of days for which a medication was dispensed divided by the number of days for which it was prescribed. For regimens with two different medications, total PPDC was the average of the PPDCs for each medication. The main predictor was SES, measured by the Pampalon’s material deprivation index, a compounded index of income, employment, and education, based on postal codes. It is divided in quintiles, with quintile 1 being the least materially deprived. Comparison of PPDC between quintiles of SES was achieved by a Kruskal-Wallis test. Chi-square testing was used to assess the relationship between the proportion of patients with primary non-adherence (PPDC=0) and quintiles of SES. In the subset of patients who did not have primary non-adherence (n = 462), interaction between SES and daily dose frequency on log transformed PPDC was examined using linear regression models. Results Among 551 patients, mean age was 7.1 years (SD 3.8) (Table1), and there was a similar number of patients in each quintile of SES based on a chi-square goodness of fit test (p=0.61). For the overall sample, mean PPDC was 38.1% (SD 27.6). PPDC was not statistically different between quintiles of SES (p=0.57) (Figure 1). Distribution of primary non-adherence (PPDC = 0) in the cohort was independent of the quintiles of SES (p=0.57). Keeping SES constant, twice-daily dose frequency was associated with a 1.1% decrease in PPDC (p=0.85). The interaction between daily dose frequency and SES was not statistically significant (p=0.66). Conclusion Medication adherence (PPDC) and primary non-adherence (PPDC = 0) did not vary significantly by SES, but twice-daily dose frequency was associated with a small decrease in mean PPDC. Quebec’s mandatory medication insurance could potentially explain the absence of difference in medication adherence across SES quintiles.
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 | 0,006 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,001 |
| Bibliométrie | 0,001 | 0,002 |
| Études des sciences et des technologies | 0,001 | 0,000 |
| Communication savante | 0,001 | 0,001 |
| Science ouverte | 0,001 | 0,001 |
| Intégrité de la recherche | 0,001 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,003 | 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 ».