The effects of supported shared‐care and hemodialysis self‐care on patient psychological well‐being, interdialytic weight gain, and blood pressure control
Bibliographic record
Abstract
INTRODUCTION: Traditionally hemodialysis (HD) treatments are undertaken by dialysis staff. Self-care has been reported to improve psychological well-being and treatment compliance for patients with chronic diseases. We evaluated our shared-care HD program to determine whether shared-care benefits patients. METHODS: We reviewed the electronic health care and HD sessional records and psychological distress thermometer (DT) scores of patients in our HD centers. HD shared care was classified as grade 0-none, grade 1 patients weighing themselves and measuring blood pressure (BP), grade 2 performs HD, and grade 3 additionally troubleshoots problems. FINDINGS: We reviewed 675 HD patients; mean age 64.1 ± 16.3 years, 62.3% male, 45.9% diabetic, Stoke-Davies co-morbidity grade 1 (1-1), frailty score 4 (3-5), DT 3 (0-5). 60.3% performed no shared care, 19% grade 1, 14.8% grade 2, and 6% grade 3. Patients performing more shared care were younger, less frail, less co-morbid, and physically stronger. We then propensity matched 113 patients with grade ≥ 2 shared care for age and frailty with 113 no shared-care patients. Fewer shared-care patients were prescribed antihypertensives (50.7 vs. 70.7%, P < 0.01), and had lower serum N terminal probrain natriuretic peptide 3033 (1083-8502) vs. 4814(1514-135821) pg/mL), phosphate (1.62 ± 0.49 vs. 1.78 ± 0.62 mmol/L), and higher albumin (40.7 ± 4.3 vs. 38.0 ± 4.3 g/L), all P < 0.05 but no differences in psychological DT scores. DISCUSSION: Although there was no significant benefit in psychological well-being, as measured by the self-reported DT, patients performing more shared care demonstrated other benefits in terms of blood pressure and volume control.
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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 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".