Medication burden in patients with dialysis-dependent CKD: a systematic review
Bibliographic record
Abstract
This systematic review aimed to statistically profile the medication burden and associated influencing factors, and outcomes in patients with dialysis-dependent chronic kidney disease (DD-CKD). Studies of medication burden in patients with DD-CKD in the last 10 years from 1 January 2013 to 31 March 2024 were searched from PubMed, Embase, and Cochrane databases. Newcastle-Ottawa Scale (NOS) or Agency for Healthcare Research and Quality (AHRQ) methodology checklist was used to evaluate quality and bias. Data extraction and combining from multiple groups of number (n), mean, and standard deviation (SD) were performed using R programming language (version4.3.1; R Core Team, Vienna, Austria). A total of 10 studies were included, and the results showed a higher drug burden in patients with DD-CKD. The combined pill burden was 14.57 ± 7.56 per day in hemodialysis (HD) patients and 14.63 ± 6.32 in peritoneal dialysis (PD) patients. The combined number of medications was 9.74 ± 3.37 in HD and 8 ± 3 in PD. Four studies described the various drug classes and their proportions, in general, antihypertensives and phosphate binders were the most commonly used drugs. Five studies mentioned factors associated with medication burden. A total of five studies mentioned medication burden-related outcomes, with one study finding that medication-related burden was associated with increased treatment burden, three studies finding that poor medication adherence was associated with medication burden, and another study finding that medication complexity was not associated with self-reported medication adherence. Limitations: meta-analysis was not possible due to the heterogeneity of studies.
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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 | 0.006 | 0.028 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.008 | 0.008 |
| Bibliometrics | 0.009 | 0.011 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".