Medication review interventions for adults living with advanced chronic kidney disease: A scoping review
Bibliographic record
Abstract
Structured medication reviews (SMRs) were introduced into the National Health Service (NHS) Primary Care to support the delivery of the NHS Long-Term Plan for medicines optimization. SMRs improve the quality of care, reduce harm and offer value for money. However, evidence to support SMRs for patients with chronic kidney disease (CKD) stage G4-5D with elevated risk of cardiovascular disease and premature mortality is unknown. This scoping review aimed to assess the extent and nature of SMR research in the population of patients with CKD stage G4-5D. Electronic databases were searched on 20 October 2023. Studies were eligible if they described an SMR in adults with CKD stage G4-5D, regardless of the study design. Data detailing the global patterns, population and intervention descriptions, professionals performing SMR, and reported areas for future research were extracted. The extracted outcome data were categorized as clinical, patient-important, medication-related and experience-related. A narrative synthesis was completed. Seventeen studies (81%) were conducted in nephrology outpatient settings, three (14%) during acute hospital admissions and one (5%) within the community pharmacy. Eighteen studies (86%) were quantitative, including five randomized controlled trials. Ten (48%) studies were undertaken in the United States and Canada, and two in Europe (France and Norway). No such studies have been conducted in the United Kingdom. Our review revealed that there is a lack of evidence for SMR as a strategy to reduce polypharmacy and harms from medication for adults with CKD stage G4-5D. Therefore, further research is required in this area.
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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 | 0.022 | 0.109 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.007 | 0.007 |
| Bibliometrics | 0.015 | 0.014 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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".