Access to new drugs for dialysis patients: challenges for indigenous and non-indigenous populations
Bibliographic record
Abstract
Most dialysis patients are on 5 - 10 medications. The costs of these medications vary widely, ranging from pennies per day for water soluble multivitamins, to several thousand dollars per year for erythropoietin-stimulating agents. In Canada, public funding for drug therapies is undertaken by each province, with wide variability in coverage and on restriction criteria for expensive new drugs. For native Canadians and Inuit, access to drugs is superior to that of other Canadians through a federal program. The Canadian system for drug evaluation, where strict evidence-based medicine (EBM) and comparative effectiveness research (CER) is applied, is instructive and may provide clues to the future from an international perspective. Given the unique challenges in nephrology, it is predicted that access to new drugs and other therapies will be restricted by these evaluation methods. Indeed, it seems desirable for nephrology organizations to respond to this new threat in a pragmatic and balanced way. Part of that response might be a call for exceptional status for dialysis, with adjusted criteria of EBM and CER that would be more suitable, and stimulate innovation and research in nephrology.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".