Rationale for a home dialysis virtual ward: design and implementation
Bibliographic record
Abstract
BACKGROUND: Home-based renal replacement therapy (RRT) [peritoneal dialysis (PD) and home hemodialysis (HHD)] offers independent quality of life and clinical advantages compared to conventional in-center hemodialysis. However, follow-up may be less complete for home dialysis patients following a change in care settings such as post hospitalization. We aim to implement a Home Dialysis Virtual Ward (HDVW) strategy, which is targeted to minimize gaps of care. METHODS/DESIGN: The HDVW Pilot Study will enroll consecutive PD and HHD patients who fulfilled any one of our inclusion criteria: 1. following discharge from hospital, 2. after interventional procedure(s), 3. prescription of anti-microbial agents, or 4. following completion of home dialysis training. Clinician-led telephone interviews are performed weekly for 2 weeks until VW discharge. Case-mix (modified Charlson Comorbidity Index), symptoms (the modified Edmonton Symptom Assessment Scale) and patient satisfaction are assessed serially. The number of VW interventions relating to eight pre-specified domains will be measured. Adverse events such as re-hospitalization and health-services utilization will be ascertained through telephone follow-up after discharge from the VW at 2, 4, 12 weeks. The VW re-hospitalization rate will be compared with a contemporary cohort (matched for age, gender, renal replacement therapy and co-morbidities). Our protocol has been approved by research ethics board (UHN: 12-5397-AE). Written informed consent for participation in the study will be obtained from participants. DISCUSSION: This report serves as a blueprint for the design and implementation of a novel health service delivery model for home dialysis patients. The major goal of the HDVW initiative is to provide appropriate and effective supports to medically complex patients in a targeted window of vulnerability. TRIAL REGISTRATION: (NCT01912001).
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".