Antidiabetic medication persistence and implementation in patients with chronic kidney disease
Bibliographic record
Abstract
Authors : Viet Thanh Truong, Jocelyne Moisan, Edeltraut Krou00ebger, Serge Langlois, Jean-Pierre Gru00e9goireTitle: Antidiabetic medication persistence and implementation in patients with chronic kidney diseaseBackgroundPersistence with and implementation of antidiabetic drug (AD) treatment are important for patients with chronic kidney disease to slow disease progression and prevent cardiovascular complications. AimsWe aimed to evaluate AD persistence and implementation and to identify factors associated with persistence and with implementation.MethodUsing Quebec (Canada) medico-administrative data, we conducted a cohort study among patients newly diagnosed with chronic kidney disease between 1 January 2000 and 31 December 2011 who initiated afterwards an AD. We considered as persistent patients who were still taking any AD one year after initiation of AD treatment. Among persistent patients, those who had at least 80% of days covered with any AD in the 365-day period following treatment initiation, were considered to have adequately implemented their treatment. Factors associated with persistence and implementation were identified using a multivariate modified Poisson regression. ResultsThe cohort consisted of 6,671 patients newly diagnosed with chronic kidney disease who initiated an AD. Of them, 5,128 (76.9%) were persistent with their AD one year after initiation. Patients with medium (vs. high) socio-economic status, those being treated with a multi-therapy (vs. metformin monotherapy), and those who had comorbidities including hypertension, dyslipidemia, stroke and coronary disease were more likely to be persistent, whereas those who had more than 10 physician visits or were hospitalized in the year prior to the initial AD were less likely to be persistent. Among persistent individuals, 4,506 (87.9%) had adequate implementation. Female patients, those aged 82 years or over and those who had more than 10 physician visits in the year prior to AD initiation were more likely to adequately implement their AD treatment.DiscussionOverall, about 32.4% of patients with chronic kidney disease who initiated an AD may not fully benefit from it as they were either non-persistent or had inadequate treatment implementation. The knowledge of factors associated with persistence and implementation could help to target patients who are likely to benefit from interventions aiming to optimize persistence and implementation.
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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 | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".