Short and long nightly hemodialysis in the United States
Bibliographic record
Abstract
When hemodialysis first started in the United States in the 1960s, a large percentage of patients performed their treatments at home. However, because of reimbursement issues, home hemodialysis (HHD) gradually succumbed to an in-center approach and eventually a mindset. Since the introduction of nightly HHD by Uldall and Pierratos in 1993, there has been a resurgence of interest in HHD. This paper describes the different types of home hemodialysis being performed as of December 31, 2007 in this country. Because neither the United States Renal Data System (USRDS) nor the End Stage Renal Disease (ESRD) Networks break down home dialysis into the different modalities, a provider questionnaire was sent out to 2 major providers, a number of mid-level providers and other providers known to do HHD. In addition, a questionnaire was sent out to 3 machine providers to obtain the number of patients using their machine for HHD as of December 31, 2007. The results showed that 91.7% of patients are dialyzing in-center, 7.3% are doing peritoneal dialysis, and 0.7% are doing HHD. Currently about 1% of ESRD patients in the United States are doing home hemodialysis. NxStage, however, has started 1000 patients in the past year on short-daily home hemodialysis. Patients are beginning to understand that there are better options than 3 times a week in-center dialysis. And as a result of the "HEMO Study," nephrologists now believe that longer and more frequent dialysis is a better therapy for ESRD patients. Therefore, promotion of HHD should become a priority for the renal community in the future.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".