The International Quotidian Hemodialysis Registry: Rationale and challenges
Bibliographic record
Abstract
Outcomes from conventional thrice-weekly hemodialysis (CHD) are disappointing for a life-saving therapy. The results of the HEMO Study show that the recommended minimum dose (Kt/V) for adequacy is also the optimum attainable with CHD. Interest is therefore turning to alternative therapies exploring the effects of increased frequency and time of hemodialysis (HD) treatment. The National Institutes of Health have sponsored 2 randomized prospective trials comparing short hours daily in-center HD and long hours slow nightly home HD with CHD. An International Registry has also been created to capture observational data on patients receiving short hours daily in-center HD, long hours slow nightly home HD, and other alternative therapies. Participation by individual centers, other registries and the major dialysis chains is growing and currently data from nearly 3000 patients have been collected. Pitfalls in data collection have been identified and are being corrected. A matched cohort (patients in other registries) study is planned to obtain information regarding hard outcomes expected from these therapies. The Registry may become the most important source of information required by governments, providers, and the nephrological community in assessing the utility of such therapies.
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 | 0.081 | 0.090 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.001 |
| Bibliometrics | 0.007 | 0.011 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.005 | 0.007 |
| Open science | 0.004 | 0.003 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.002 | 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".