Kidney Dyads: Caregiver Burden and Relationship Strain Among Partners of Dialysis and Transplant Patients
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Bibliographic record
Abstract
Background. Caring for dialysis patients is difficult, and this burden often falls on a spouse or cohabiting partner (henceforth referred to as caregiver-partners). At the same time, these caregiver-partners often come forward as potential living kidney donors for their loved ones who are on dialysis (henceforth referred to as patient-partners). Caregiver-partners may experience tangible benefits to their well-being when their patient-partner undergoes transplantation, yet this is seldom formally considered when evaluating caregiver-partners as potential donors. Methods. To quantify these potential benefits, we surveyed caregiver-partners of dialysis patients and kidney transplant (KT) recipients (N = 99) at KT evaluation or post-KT. Using validated tools, we assessed relationship satisfaction and caregiver burden before or after their patient-partner’s dialysis initiation and before or after their patient-partner’s KT. Results. Caregiver-partners reported increases in specific measures of caregiver burden ( P = 0.03) and stress ( P = 0.01) and decreases in social life ( P = 0.02) and sexual relations ( P < 0.01) after their patient-partner initiated dialysis. However, after their patient-partner underwent KT, caregiver-partners reported improvements in specific measures of caregiver burden ( P = 0.03), personal time ( P < 0.01), social life ( P = 0.01), stress ( P = 0.02), sexual relations ( P < 0.01), and overall quality of life ( P = 0.03). These improvements were of sufficient impact that caregiver-partners reported similar levels of caregiver burden after their patient-partner’s KT as before their patient-partner initiated dialysis ( P = 0.3). Conclusions. These benefits in caregiver burden and relationship quality support special consideration for spouses and partners in risk-assessment of potential kidney donors, particularly those with risk profiles slightly exceeding center thresholds.
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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 it