Burden of Dialysis, Health-Related Quality of Life, and Employment Comparisons Between Peritoneal Dialysis and In-Center Hemodialysis: Findings from the DOPPS Program
Bibliographic record
Abstract
Background: The Dialysis Outcomes and Practice Patterns Study (DOPPS) and the Peritoneal Dialysis Outcomes and Practice Patterns Study (PDOPPS) collect information annually about quality of life, including employment and functional status. Differences in these domains by dialysis modality (PD vs. centre-based hemodialysis) may inform individuals in choosing a dialysis modality. Methods: PD and HD patients with comparable characteristics were analyzed. For baseline patient questionnaire, we used logistic regression to analyze binary outcomes employment (full- or part-time versus unemployed), depression (CES-D ≥10 vs. <10), and functional status (≥11 vs. <11), and used linear mixed models to analyze continuous outcomes (PCS, MCS, and burden of kidney disease score). Change of outcomes were described descriptively. Results: There were 3227 PD and 4544 HD patients at baseline. Burden of kidney disease scores were better for PD compared to HD (overall 9-point adjusted difference, [95%CI: 7-11]) with a higher proportion of patients on PD in the lowest burden range (10%-37%) compared to 8%-24% on HD, depending on country. PD patients also had better PCS and MCS, though these were less marked (overall adjusted difference of 0.9 [0.2-1.6] for PCS, 1.0 [0.2-1.9] for MCS). HD patients had worse functional status scores (adjusted OR HD vs. PD 0.6, [0.5, 0.8] for score ≥ 11); were less likely employed (OR=0.6, [0.5, 0.8]); and had worse CES-D scores (OR=0.8, [0.7, 1.0] for CES-D < 10). In Australia/New Zealand, HD patients had better MCS and CES-D scores and a higher proportion being employed than PD patients. 174 PD patients and 254 HD patients died within one year; 614 PD patients and 535 HD patients left the study between questionnaires. Changes over time in the continuous measures were small. Trends in employment, CES-D score, and functional status were small and not statistically significant. Conclusions: Compared to HD patients, PD patients reported a lower burden of kidney disease score and among survivors, remains stable on either PD or HD over 12 months. This information, when shared with patients choosing a dialysis modality, could result in an increased uptake of PD. Funding: Commercial Support - Global support for the ongoing DOPPS Programs is provided without restriction on publications by a variety of funders. For details see https://www.dopps.org/AboutUs/Support.aspx.
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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 | 0.002 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| 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".