Longitudinal medication adherence in children with nephrotic syndrome and association with disease outcomes
Bibliographic record
Abstract
BACKGROUND: Children with nephrotic syndrome have a high medication burden and treatment-related side effects, which can contribute to non-adherence. Optimal medication adherence may reduce symptom burden, improve disease control and prevent complications. However, longitudinal patterns of medication adherence and associations with disease outcomes among children with nephrotic syndrome remain uncertain. METHODS: We analysed data from Insight into Nephrotic Syndrome: Investigating Genes, Health, and Therapeutics, a prospective observational childhood nephrotic syndrome cohort. We included all children (1-18 years of age) with nephrotic syndrome diagnosed from 1996 to 2023 from the Greater Toronto and Hamilton Area, Canada, excluding congenital or secondary causes of nephrotic syndrome. Participants were followed annually with questionnaires for up to 5 years since study initiation. Medication adherence was self-reported by participants or parents using the Medication Adherence Questionnaire (MAQ). We evaluated the association between longitudinal medication non-adherence (MAQ score ≥1) and subsequent relapse rates, steroid-sparing medication initiation and hospitalizations using generalized linear mixed models. RESULTS: We included 1905 study visits among 735 children diagnosed with nephrotic syndrome [mean age at visit 8.7 years (standard deviation 4.3), 65% male, 30% frequently relapsing or steroid dependent, median 1 (interquartile range 0-3) prescribed medications]. Medication non-adherence (MAQ score ≥1) was reported at 367 (19%) study visits and 228 (31%) participants reported non-adherence at least once. Rates of non-adherence remained stable over 5 years of follow-up. Worse medication adherence was not significantly associated with subsequent relapse rates {adjusted relative rate 1.14 [95% confidence interval (CI) 0.97-1.34]}, use of steroid-sparing medication [adjusted odds ratio (OR) 0.90 (95% CI 0.61-1.32] or rituximab [adjusted OR 0.77 (95% CI 0.36-1.66)] or hospitalizations [adjusted OR 1.17 (95% CI 0.59-2.32)]. CONCLUSIONS: Self-reported medication non-adherence occurs in one-third of children with nephrotic syndrome yet does not adversely affect subsequent relapses, steroid-sparing medication use or hospitalizations.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".