Predictors of quality of life in patients within the first year of commencing haemodialysis based on baseline data from the PIVOTAL trial and associations with the study outcomes
Bibliographic record
Abstract
BACKGROUND: Impaired quality of life is common in patients with end-stage kidney disease. We report the baseline quality of life measures in participants from the PIVOTAL randomized controlled trial and the potential relationship with the primary outcome (all-cause mortality, myocardial infarction, stroke, and heart failure hospitalisation), and associations with key baseline characteristics. METHODS: This was a post hoc analysis of 2141 patients enrolled in the PIVOTAL trial. Quality of life was measured using EQ5D index, Visual Analogue Scale, and the KD-QoL [Physical Component Score and Mental Component Score]. RESULTS: Mean baseline EQ5D index and visual analogue scale scores were 0.68 and 60.7 and 33.7 (Physical Component Score) and 46.0 (Mental Component Score), respectively. Female sex, higher Body Mass Index, diabetes mellitus, history of myocardial infarction, stroke or heart failure were associated with significantly worse EQ5D index and visual analogue scale. Higher C-reactive protein levels and lower transferrin saturation were associated with worse quality of life. Haemoglobin was not an independent predictor of quality of life. A lower transferrin saturation was an independent predictor of worse physical component score. A higher C-reactive protein level was associated with most aspects of worse quality of life. Impaired functional status was associated with mortality. CONCLUSION: Quality of life was impaired in patients starting haemodialysis. A higher C-reactive protein level level was a consistent independent predictor of the majority of worse quality of life. Transferrin saturation ≤ 20% was associated with worse physical component score of quality of life. Baseline quality of life was predictive of all-cause mortality and the primary outcome measure. EUDRACT REGISTRATION NUMBER: 2013-002267-25.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.004 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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) | 0.000 | 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 teacher head, 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".