Knowledge of Home Dialysis Among Inner‐City Satellite Hemodialysis Patients
Bibliographic record
Abstract
There is limited use of home renal replacement therapies in the U.S.A. One percent of dialysis patients are on home hemodialysis (HHD) and only 9% undergo peritoneal dialysis (PD). In an effort to better understand this, 161 satellite hemodialysis patients in 6 units in Brooklyn were surveyed. Forty-eight percent of patients were women, 86% were black, 5% white, 8% Hispanic, and 1% other. Mean age was 49.4 years (range 22 - 69 years). Etiology of renal disease was hypertension (41%), diabetes mellitus (31%), polycystic kidney disease (3%), systemic lupus erythematosus (4%), and other or unknown (21%). Patients were queried about knowledge of and attitudes toward home therapies. Seventy-nine percent of patients knew of home dialysis. The source of this information was the nephrologist (59%), the social worker (14%), a nurse (8%), other patients (4%), and other sources (15%). Only 10% of patients had ever considered HHD. Fifty-four percent were afraid to do self-care at home and 35% were not interested. Surprisingly, only 3% felt they had no reliable helper and 8% felt that their housing was not suitable. Similarly, 78% of patients had been spoken to about PD, but only 11% had considered it. Forty-one percent were afraid of doing self-care on PD, and 45% were not interested. We conclude that, although the majority of patients in six inner-city dialysis units had heard of home dialysis, only a small number ever considered it. As many patients were afraid of doing home therapy, better education about the risks and benefits needs to be disseminated.
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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 | 0.002 |
| 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 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 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".