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Record W3208650238 · doi:10.1093/pch/pxab061.047

61 Adherence to Daily Medication Regimens in Pediatric Asthma: Do Socioeconomic Status and Daily Dose Frequency have an Impact?

2021· article· en· W3208650238 on OpenAlexaffabout
Frédérique Armellin-Ducharme, Olivier Drouin

Bibliographic record

VenuePaediatrics & Child Health · 2021
Typearticle
Languageen
FieldHealth Professions
TopicChild and Adolescent Health
Canadian institutionsCentre Hospitalier Universitaire Sainte-Justine
Fundersnot available
KeywordsMedicineAsthmaSocioeconomic statusCohortPediatricsMedication adherenceRetrospective cohort studyPopulationInternal medicinePhysical therapyEnvironmental health

Abstract

fetched live from OpenAlex

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.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.006
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.073
Threshold uncertainty score0.146

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.002
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.000

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.

Opus teacher head0.033
GPT teacher head0.381
Teacher spread0.348 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2021
Admission routes2
Has abstractyes

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