Comparison of Staff‐Assisted Home Hemodialysis with In‐Center Hemodialysis and In‐Hospital Hemodialysis
Bibliographic record
Abstract
Home hemodialysis (HHD) is superior to in-center hemodialysis (ICHD) in terms of survival, quality of life, and cost-effectiveness. However, assistance from family members in performing HHD is not always available to patients, and professional assistance for HHD can be cost prohibitive. For certain patients, ICHD can be impractical due to difficulties in transportation, which may necessitate ambulance transportation or hospitalization for in-hospital hemodialysis (IHHD). We describe 4 patients that have had problems receiving ICHD for various reasons. Two of these patients had problems with transportation, while the other two could not remain on dialysis for the prescribed duration of time and, therefore, received inadequate dialysis. These patients had difficulty while receiving ICHD in meeting the adequacy criteria set by Dialysis Outcomes Quality Initiative. One of these patients had a neuropsychiatric disorder and displayed disruptive behavior. When these 4 patients were switched to staff-assisted home hemodialysis (SAHD), the dialysis core indicators improved compared with ICHD, and the patients needed significantly fewer hospitalization days. In this paper, we demonstrate that, in patients that cannot be easily transferred, and in patients with neuropsychiatric disorders, SAHD can be a less expensive and more efficacious modality of dialysis.
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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 | 0.002 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".