Prescribing patterns and medication costs in patients on maintenance haemodialysis and peritoneal dialysis
Bibliographic record
Abstract
BACKGROUND: Polypharmacy is a significant clinical issue for patients on dialysis but has been incompletely studied. We investigated the prevalence and costs of polypharmacy in a population-based cohort of participants treated with haemodialysis (HD) or peritoneal dialysis (PD). METHODS: We studied adults ≥20 years of age in Alberta, Canada receiving maintenance HD or PD as of 31 March 2019. We characterized participants as users of 0-29 drug categories of interest and those ≥65 years of age as users/non-users of potentially inappropriate medications (PIMs). We calculated the number of drug categories, daily pill burden, total annual cost and annual cost per participant and compared this to an age- and sex-matched cohort from the general Alberta population. RESULTS: Among 2248 participants (mean age 63 years; 39% female) on HD (n = 1781) or PD (n = 467), the median number of prescribed drug categories was 6 [interquartile range (IQR) 4-8] and the median daily pill burden was 8.0 (IQR 4.6-12.6), with 5% prescribed ≥21.7 pills/day and 16.5% prescribed ≥15 pills/day. Twelve percent were prescribed at least one drug that is contraindicated in kidney failure. The median annual per-participant cost was ${\$}$3831, totalling ≈${\$}$11.6 million annually for all participants. When restricting to the 1063 participants ≥65 years of age, the median number of PIM categories was 2 (IQR 1-2), with a median PIM pill burden of 1.2 pills/day (IQR 0.5-2.4). Compared with PD participants, HD participants had a similar daily pill burden, higher use of PIMs and higher annual per-participant cost. Pill burden and associated costs for participants on dialysis were >3-fold and 10-fold higher, respectively, compared with the matched participants from the general population. CONCLUSION: Participants on dialysis have markedly higher use of prescription medications and associated costs than the general population. Effective methods to de-prescribe in the dialysis population are needed.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| 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".