A Comparison of Quality of Life and Travel-Related Factors between In-center and Satellite-Based Hemodialysis Patients
Bibliographic record
Abstract
BACKGROUND AND OBJECTIVES: Shorter travel times and distance to dialysis clinics have been associated with improved patient outcomes and a higher health-related quality of life (HRQOL). The objective of this study was to compare HRQOL between prevalent in-center and satellite dialysis patients, as well as compare travel-related factors that contribute to HRQOL between in-center and satellite-based patients. DESIGN, SETTING, PARTICIPANTS, & MEASURES: The London Health Sciences Centre is a tertiary care center with in-center and regional satellite hemodialysis units. Patients who consented and completed a questionnaire (n = 202) were enrolled into a cross-sectional, cohort observational study. Patients were administered the Medical Outcomes Short-Form 36 (SF-36) and the Kidney Disease Health Related Quality of Life (KDHRQOL) tool and were asked questions relating to travel to dialysis clinics. RESULTS: Patients who underwent dialysis in the satellites had similar demographics, comorbidities, and laboratory parameters. Patients who underwent dialysis in satellite units reported a significantly superior score on the dialysis stress domain of the KDHRQOL questionnaire. There was no significant difference between in-center and satellite patients on the basis of the SF-36. Satellite patients also reported a significantly decreased cost of transportation, a significantly increased proportion who drive themselves to clinics, and significantly decreased travel time. CONCLUSIONS: Patients who underwent dialysis in satellite units demonstrated similar characteristics, comorbidities, surrogate outcomes, and most aspects of HRQOL. Travel time, cost, and receiving treatment in one's own community are important factors that may contribute to a trend toward higher reported HRQOL by patients in satellite dialysis units.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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) | 0.002 | 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".