Burden on caregivers as perceived by hemodialysis patients in the Frequent Hemodialysis Network (FHN) trials
Bibliographic record
Abstract
BACKGROUND: Patients with end-stage renal disease often rely on unpaid caregivers to assist them with their daily living and medical needs. We characterized the degree to which patients enrolled in the Frequent Hemodialysis Network (FHN) trials perceived burden on their unpaid caregivers. METHODS: Participants completed the Cousineau Perceived Burden Scale, a 10-question scale previously developed in hemodialysis (HD) patients. Associations between baseline burden score and prespecified variables were evaluated using multivariable linear regression. RESULTS: Of 412 participants, 236 (57%) reported having unpaid caregivers. Compared to those without unpaid caregivers, these participants had greater comorbidity (Charlson mean 1.8 ± 1.8 versus 1.2 ± 1.7, P < 0.001), lower Short Form-36 (SF-36) Physical Health Composite (PHC) scores (median 33 versus 41, P < 0.001, higher Beck Depression scores (mean 16 ± 11 versus 12 ± 9, P < 0.001), and worse physical function. Median Cousineau score was 35 (interquartile range 20-53) (theoretical range 0-100). Over 50% felt their caregivers were overextended, yet 60% were confident that their caregivers could handle the demands of caring for them. Higher perceived burden was not associated with ability to be randomized. In adjusted analyses, Cousineau score was inversely associated with SF-36 PHC and Mental Health Composite scores and directly associated with Beck Depression score (each P < 0.001). CONCLUSIONS: Most HD patients in the FHN trials perceived substantial burden on their unpaid caregivers, and self-perceived burden was associated with worse depression and quality of life. Evaluation of the effects of frequent HD on perceived burden borne by caregivers in the FHN trials will help to establish the net benefits/determents of these intensive dialytic strategies.
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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 | 0.018 | 0.029 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".