Association Between FokI Polymorphism of Vitamin D Receptor Gene and Lumbar Spine Disc Degeneration
Bibliographic record
Abstract
OBJECTIVE: The aim of the present meta-analysis was to explore the association between FokI polymorphism of the vitamin D receptor gene and lumbar spine disc degeneration. DESIGN: The search was performed in PubMed, Scopus, and Web of Science databases up to January 2020. The authors selected nine studies comprising a total of 1549 cases and 1672 controls. The association analysis included the allelic, dominant, recessive, homozygous, and heterozygous genetic models. Odds ratios with 95% confidence intervals were used to evaluate the association. The Newcastle-Ottawa Scale was used to measure the quality of the studies included in the analyses; a cut-off of 6 stars was applied. RESULTS: This meta-analysis indicated that FokI polymorphism is significantly associated with lumbar degenerative disc disorder and disc herniation in the homozygous (odds ratio, 1.77; 95% confidence interval, 1.23-2.54; Z test P = 0.002, Q test P = 0.416) and recessive (odds ratio, 1.53; 95% confidence interval, 1.23-1.90; Z test P < 0.000, Q test P = 0.224) models. CONCLUSIONS: This study indicates that the vitamin D receptor gene FokI polymorphism may be correlated with the risk of developing a lumbar degenerative disc disorder and disc herniation. However, the small sample population studied and the lack of an evaluation of environmental factors must be taken as limitations in the present meta-analysis.
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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 | 0.007 | 0.016 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.008 | 0.021 |
| Bibliometrics | 0.004 | 0.005 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".