Psychosocial variables are associated with being wait-listed, but not with receiving a kidney transplant in the Dialysis Outcomes and Practice Patterns Study (DOPPS)
Bibliographic record
Abstract
BACKGROUND: Psychosocial factors are associated with clinical outcomes in patients with end-stage renal disease. It is not known if self-reported depression and quality of life influence the likelihood of being wait-listed and receiving a transplant. METHODS: Prevalent cross section of 18- to 65-year-old hemodialysis (HD) patients in the USA (N = 2033) and seven European countries (N = 4350) from the Dialysis Outcomes and Practice Patterns Study phase II and III was analyzed. Wait-listed patients (N = 1838) were followed until kidney transplantation. Self-reported depressive symptoms were assessed by the Center for Epidemiologic Studies-Depression scale, 10-item version (CES-D) and health-related quality of life (HR-QoL) by the Kidney Disease Quality of Life Short Form 12 scale Physical Component Score (PCS). RESULTS: At study entry, 27% (USA) to 53% (UK) of patients were wait-listed in participating countries. Variables associated with lower odds of being on the waiting list included worse HR-QoL, more severe depressive symptoms, older age, fewer years of education, lower serum albumin, lower hemoglobin, shorter time on dialysis and presence of multiple comorbid conditions. Among wait-listed patients, significantly lower transplantation rates were seen for females, blacks, patients having prior transplantation and multiple comorbid conditions but not PCS or CES-D. CONCLUSIONS: Fewer depressive symptoms and better HR-QoL are associated with being on the waiting list in prevalent HD patients but not with receiving a kidney transplant among wait-listed dialysis patients. Regular assessment of subjective well-being may help identify patients with reduced access to wait-listing and kidney transplantation.
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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 | 0.001 | 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 | 0.001 | 0.000 |
| 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".