Prognostic significance of 25‐hydroxivitamin <scp>D</scp> entirely explained by a higher comorbidity burden: Experience from a <scp>S</scp>outh‐<scp>E</scp>astern <scp>E</scp>uropean <scp>D</scp>ialysis <scp>C</scp>ohort
Bibliographic record
Abstract
Vitamin D deficiency is still a common problem particularly in the elderly and in individuals with various degrees of renal impairment. The present study aimed to evaluate the association between plasma concentrations of 25(OH)D and death in a large cohort of prevalent patients on hemodialysis (HD) from south-east Romania, a typical Balkan region. This is an observational prospective study that included a total of 570 patients on maintenance HD. Study patients were classified into three groups by baseline 25(OH)D levels: (1) sufficient 25(OH)D--i.e., >30 ng/mL; (2) insufficient 25(OH)D--i.e., between 10 and 29 ng/mL; and (3) deficient 25(OH)D--i.e., <10 ng/mL. During the follow-up period of 14 months, 68 patients (11.9%) died, the Kaplan-Meier analysis showing significant differences in all-cause mortality for chronic kidney disease patients in different 25(OH)D groups (P = 0.002). Unadjusted Cox regression analysis also showed significant differences in survival. The multivariate Cox regression model showed no significant differences in survival according to vitamin D levels. Hazard ratio for death in the "<10 ng/mL" group was 1.619 (P = 0.190) and in the "10-30 ng/mL" group was 0.837 (P = 0.609). In our dialysis population with a high comorbidity burden, low 25(OH)D concentration was not associated with mortality in the adjusted Cox model, suggesting that vitamin D deficiency could represent only a non-specific marker for a poor health status, with less impact on mortality.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".