Health-Related Quality of Life During Dialysis Modality Transitions: A Mixed-Methods Study
Bibliographic record
Abstract
Background: Dialysis transitions may have an impact on health related quality of life (HRQOL), a patient defined priority for research and clinical care. We measured HRQOL and explored perceptions of adults who were initiating dialysis for the first time or transitioning to a new dialysis modality in a large urban centre in Canada. Methods: In this prospective convergent parallel mixed-methods study we recruited eligible patients who were transitioning to dialysis from pre-care (n=9, incident) or undertaking a dialysis modality change (n=10, prevalent) between July and September 2017. Patients completed the five domains of the Kidney Disease Quality of Life-36 (KDQOL-36) survey on their first day of dialysis treatment or first day of home dialysis training and underwent a semi-structured interview and follow up KDQOL-36 survey at 3 months. Results: 19 patients completed KDQOL-36 at baseline and at 3 months; 15 also participated in an interview. Statistically significant increases in all measured domains of the KDQOL-36 were observed from baseline to three months: “Symptoms” [mean difference (MD)=14.9, p<0.01]; “Effects” (MD=14.3, p<0.01); “Burden” (MD=7.3, p=0.04); “PCS” (MD=7.5, p<0.01); “MCS” (MD=7.2, p=0.04). These patterns of change were similar for both incident and prevalent patients and across the different types of transitions. The qualitative interviews identified the following themes: 1) adapting to new circumstances (tackling change, accepting change), 2) adjusting together 3) trade offs, and 4) challenges of chronicity (the impact of dialysis, living with a complex disease, planning with uncertainty. Conclusions: The transition to a new or different type of dialysis is associated with improvements in HRQOL. In addition, qualitative data provided an in depth understanding of the transition experience, and revealed significant emotional and psychosocial processes that need to be considered during both incident and prevalent dialysis transitions.
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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 | 0.009 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".