Calcium‐sensing receptor gene polymorphisms and cardiac valvular calcification in patients with chronic renal failure: A pilot study
Bibliographic record
Abstract
Cardiac valvular calcification (VC) is a frequent finding in chronic hemodialysis patients. In addition to demographic and metabolic factors, genetic susceptibility may also influence the occurrence and severity of these abnormalities and account for interindividual variability among patients. In this report, we studied the relation of calcium-sensing receptor (CaSR) gene polymorphisms to the development of VC in chronic hemodialysis patients. A total of 41 chronic hemodialysis patients (26 male, mean age 47.23 +/- 11.36 years vs. 15 females, mean age 48.13 +/- 14.66 years) undergoing treatment for more than 1 year were evaluated with transthoracic echocardiography. In patients with and without VC, CaSR gene polymorphisms (A990G, C1011G) were investigated by PCR, using allele-specific primers. In randomly chosen subjects, PCR analysis was verified by DNA sequencing. Cardiac valve calcification was detected in 21 patients (51.2%). Five of these patients (12.2%) had mitral valve calcification, 4 (9.75%) had aortic valve calcification, and 12 (29.27%) had both. In patients with VC, the frequency of the A/G genotype was slightly higher than those with no VC with a borderline P value (42.9% vs. 15%, chi(2)=3.840, P=0.050). The frequency of the C/C genotype was similar in patients with and without VC (90.5% vs. 85%, P>0.05). The results of this study are not enough to prove the role of CaSR gene polymorphisms in the development of VC. There is a need for large-scale studies on this topic.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".