Vitamin D receptor BsmI and TagI gene polymorphisms in Turkish ESRD population and influences on parathyroid hormone response
Bibliographic record
Abstract
Background/Aim: Clinical presentation and complications of end‐stage renal disesase (ESRD) patients are under influence of many enviromental and genetic factors. In this study we aimed to define frequencies of BsmI and TagI Vitamin D receptor (VDR) gene polymorphisms and possible influences on clinical presentations in Turkish ESRD population. Methodology and Patients: 186 patients (111 male, 75 female) who are being maintained on hemodialysis were included. Genotyping was performed for the insertion/deletion BsmI (B→b, restriction site, exon VIII→IX), TagI (T→t, 352 exon IX) VDR gene polymorphisms. Last 12 months’ laboratory values (C‐reactive protein, intact parathyroid hormone, albumin, calcium, phosphorus, Ca x P product) and clinical findings (vitamin D requirement, body weight) were recorded and analysed retrospectively. Results: Mean age and follow‐up period lengths were 42.1 ± 12.6 years and 76.3 ± 43.9 months, respectively. Polymorphism percentages were as follows: BsmI; BB/Bb/bb: 28.9/65.3/5.8%, TagI; TT/Tt/tt: 36.7/60.5/2.8%, respectively. Further analysis revealed that TT variant of TagI was related with hyperparathyroidism (p < 0.05). Analysis of data after regrouping patients according to iPTH levels (0–249, 250–499, 500 + pg/mL) and hemodialysis duration (<60 vs ≥60 months) revealed that influence of TT variation on hyperparathyroidism became more frequent in case of increased hemodialysis duration and iPTH levels (p < 0.005). Conclusion: TT variation of TagI VDR gene influences the development of hyperparathyroidism in HD patients. This influence becomes more evident in patients with longer HD duration.
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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 | 0.001 |
| 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 | 0.000 | 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".