Effects of comorbid and demographic factors on dialysis modality choice and related patient survival in Europe
Bibliographic record
Abstract
BACKGROUND: The mean age of patients starting dialysis increased over the years, as has the proportion of patients with diabetes mellitus, ischaemic heart disease, peripheral vascular disease (PVD), cerebrovascular disease (CD) and malignancy. We assessed dialysis modality choice within subgroups of patients with these comorbidities and in different age categories and subsequently evaluated the association between modality choice and patient survival in these subgroups. METHODS: Seven European renal registries participating in the ERA-EDTA Registry provided data from 15,828 incident peritoneal dialysis (PD) and haemodialysis (HD) patients (1998-2006) with available comorbidity data. The likelihood to receive PD rather than HD was assessed with logistic regression and 3-year survival on PD versus HD was evaluated using Cox regression. RESULTS: Besides large international variations in the likelihood to receive PD, we found that elderly patients and patients with PVD, CD, malignancy and multiple comorbidities were significantly less likely to receive PD than HD. Overall patients starting on PD had survival benefits [adjusted hazard ratio (HR(adj)) 0.82 (0.75-0.90)], especially patients without comorbidity [HR(adj) 0.65 (0.53-0.80)] or those with malignancy [HR(adj) 0.73 (0.56-0.94)]. In males, survival benefits of PD were independent of diabetic status. Conversely, diabetic females tended to have increased mortality risk on PD [HR(adj) 1.16 (0.93-1.44)], especially if they were >70 years [HR(adj) 1.55 (1.15-2.08)]. CONCLUSIONS: In general, modality choice was consistent with expected survival. However, elderly patients, non-diabetic patients and those with malignancy were less likely to receive PD, even though they had decreased mortality risk on PD. Also, although a survival benefit of PD was found for male patients without comorbidity, HD was just as likely to be the chosen dialysis modality as was PD for these patients.
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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 | 0.001 | 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 | 0.000 |
| 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".