Is more frequent hemodialysis beneficial and what is the evidence?
Bibliographic record
Abstract
PURPOSE OF REVIEW: The HEMO study results have shown that increasing dialysis dose in conventional thrice weekly hemodialysis does not improve patient outcomes. Interest has therefore turned to more frequent (daily) hemodialysis treatments. This review covers the rationale for such an approach together with a current review of the published study data. RECENT FINDINGS: Recent studies have suggested improvements in a number of intermediate patient outcomes such as cardiovascular (blood pressure control, left ventricular hypertrophy), anemia, phosphate control, nutritional status and quality of life. Some of these outcomes are associated with increased survival in the dialysis population. SUMMARY: The inference from these studies is that more frequent hemodialysis will indeed reduce mortality and morbidity. To date, however, the studies have all been small and underpowered to detect such primary outcomes. No randomized controlled trials are yet reported. The US National Institutes of Health have sponsored larger scale North American based studies and an International Registry of Daily Dialysis patients has been created to attain further information of the possible benefits of such therapy. In spite of the paucity of hard evidence the studies to date have been enough to convince some jurisdictions to recognize and fund daily hemodialysis treatments.
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 | 0.004 | 0.017 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.009 | 0.002 |
| Bibliometrics | 0.003 | 0.005 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.007 | 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".