Persistence and compliance with newly initiated antihypertensive drug treatment in patients with chronic kidney disease
Bibliographic record
Abstract
BACKGROUND: Patients with chronic kidney disease initiating an antihypertensive drug (AH) treatment must persist and comply with it to slow disease progression and benefit from the reduction of cardiovascular morbidity and mortality. OBJECTIVES: This study evaluates the persistence and compliance with AH treatment and identifies the associated factors among chronic kidney disease patients who initiated AH treatment. METHODS: A population-based cohort study using Quebec administrative data was conducted. Patients who still take any AH 1 year after initiation were considered persistent. Of these patients, those who had ≥80% of days covered with an AH in the year after initiation were considered compliant. Factors associated with persistence and compliance were identified using a modified Poisson regression. RESULTS: Of the 7,119 eligible patients, 78.8% were persistent, 87.7% of whom were compliant with their AH treatment. Compared with patients on diuretic monotherapy, those who initially used angiotensin-converting enzyme inhibitor monotherapy, angiotensin II receptor blocker monotherapy, calcium channel blocker monotherapy, β-blocker monotherapy, or multidrug therapy were more likely to be persistent. In contrast, individuals who visited their physicians ≥17 times were less likely to be persistent than those who visited between 0 and 8 times. The patients who were more likely to be compliant had initially used an angiotensin-converting enzyme inhibitor, β-blocker, calcium channel blocker, or multitherapy as opposed to a diuretic. CONCLUSION: A year after initiating AH treatment, nearly a third of chronic kidney disease patients were either not taking an AH or had not been compliant. Factors associated with persistence and compliance could help identify patients who need help in managing their AH treatment.
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 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 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| 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".