Increased survival of immigrant compared to native dialysis patients in an urban setting in the Netherlands
Bibliographic record
Abstract
BACKGROUND: Data from the United States and Canada suggest that survival rates of Caucasian dialysis patients are lower compared to those of black patients and patients from Asian regions. Information regarding the survival rate of immigrant dialysis patients in Europe is scarce. METHODS: We retrospectively analysed incident haemodialysis (HD) and peritoneal dialysis (PD) patients who entered an Amsterdam renal service between January 1996 and December 2005. To explore the origin of differences in survival between natives and immigrants, we ran a series of Cox models with adjustment for demographic, clinical and laboratory variables at baseline and initial adequacy variables. RESULTS: Of 303 incident dialysis patients, 58% were natives and 42% were immigrants. Fifty-nine percent of natives and 54% of immigrants had HD as initial treatment modality. At initiation of dialysis, native patients were older and had higher rates of vascular and coronary artery diseases and malignancies and a lower prevalence of hypertension. Glomerulonephritis was more common among immigrants as primary kidney disease. Mean haematocrit and calcium levels for natives were higher compared to immigrants. Cox proportional hazards analysis revealed an increased relative mortality risk (RR) of 2.7 [95% confidence interval (CI) 1.9-3.9] for natives compared to immigrants. Adjustment for age at the start of dialysis attenuated the RR to 1.9 (CI 1.3-2.7). Adjustment for the other variables did not materially influence this RR. CONCLUSIONS: We demonstrate increased survival for immigrant compared to native dialysis patients in an urban setting in the Netherlands. This survival advantage is only partly explained by younger age of immigrants at the start of dialysis compared to native 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".