The Effects of Negotiation on Discordant Home Hemodialysis Patients
Bibliographic record
Abstract
Background: Home hemodialysis (HHD) has demonstrated superior clinical outcomes, improved quality of life and enhanced treatment flexibility in comparison to 3days/week incenter HDs.Nonetheless, some patients are discordant to their dialysis prescription and require a negotiation program to maintain their normal lifestyle and ameliorate their illness behavior. Methods: Retrospective single center observational study of all prevalent HHD patients at UHN (2018-2022). Demographic and clinical data were extracted from clinical charts. Negotiation was defined as weekly contact between nurses and patients by phone, email or clinical visit to discuss the importance of being concordant to treatment and adapting the length and schedule of dialysis to avoid clinical complications. Patients were defined as concordant, concordant with agreement with at least 75%of dialysis prescription and discordant for those skipping/shortening HHD sessions without prior agreement with the clinical team. Results: From 94patients, 33(35%) required negotiation:15(16%) were concordant patients with agreement and 18(19%) discordant patient. There were no demographic differences between groups. Patients requiring negotiation presents higher median time on HHD (7.6years vs 4.3years for concordant patients). Discordant patients tended to be younger and were less likely to be listed for kidney transplant(figure 1). There were no differences in hospitalisation/technique complications amongst the 3groups. Conclusions: A third of HHD patients require negotiation to maintain their lifestyle and safety. Those patients requiring negotiation did not present with more hospitalisation or technique complications than concordant patients. We speculate that a negotiation program should be implemented in HHD centers to ameliorate patient concordance and mitigate attrition. - Total (n = 94) Concordant (n = 61) Concordant with agreement at least 75% of dialysis prescription (n = 15) Discordant (n = 18) p value Gender (male), n (%) 59 (63) 38 (62) 8 (53) 13 (72) 0.519 Age, years; median [IQR] 50 [36.6-60.3] 51 [37-61] 53 [47-61] 46 [35-54] 0.102 Patient living alone, n (%) 12 (13) 8 (13) 1 (7) 3 (17) 0.739 Dependant living at home, n (%) 27 (29) 18 (30) 6 (40) 3 (17) 0.334 Assisted home dialysis, n (%) Hypertension, n (%) 9 (10)72 (77) 8 (13)49 (80) 0 (0)9 (60) 1 (6)14 (79) 0.2460.286 Diabetes mellitus, n (%) 15 (16) 13 (21) 1 (7) 1 (6) 0.219 Access type, n (%) 0.370 AVF 39 (46) 28 (46) 7 (47) 4 (22) Catheter 49 (52) 29 (48) 7 (47) 13 (72) Graft 6 (6) 4 (7) 1 (7) 1 (6) Previous dialysis treatment, n (%) 0.282 No 31 (33) 22 (36) 4 (27) 5 (27.8) Peritoneal dialysis 22 (23) 15 (25) 1 (7) 6 (33.3) In center hemodialysis 41 (44) 24 (40) 10 (67) 7 (38,9) Previous renal transplant, n (%) 35 (37) 19 (31) 8 (53) 8 (44) 0.220 Listed for renal transplant, n (%) 31 (33) 21 (34) 7 (47) 3 (17) 0.174 Hospitalized last 5 years, n (%) 64 (68) 38 (62) 11 (73) 13 (83) 0.244 Technique survival, years; median [IQR] 4.3 [1.9-11] 3 [1.5-10] 7.6 [3-11] 7.6 [2.2-11] 0.145
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".