Can preoperative vitamin D level be a predictive factor for continence after radical prostatectomy?
Bibliographic record
Abstract
Introduction: This study examined whether there is a relationship between vitamin D levels and post-prostatectomy incontinence (PPI). Methods: Patients who underwent robotic radical prostatectomy in a tertiary center constituted the population of this study. Patients whose serum vitamin D levels were measured three months before robotic radical prostatectomy were included. Continence status was recorded at one, three, six, and 12 months postoperatively. Urinary continence was defined as either no urine leak or using a pad to feel secure against potential minimal leakage. Patients were divided into groups according to continence status at the 12th postoperative month (group 1: continent patients, group 2: PPI patients). Groups were compared in terms of patient characteristics, previously known PPI risk factors, and serum vitamin D levels. Results: The entire study cohort consisted of 318 patients. The rate of PPI was 14.5%. Since mean age, body mass index, and prostate volume were significantly higher in group 2 than in group 1, propensity score matching was applied. Before and after propensity score matching, serum vitamin D levels were higher in group 1 than in group 2 at the 12th postoperative month but no statistically significant difference was observed; however, after propensity score matching, serum vitamin D levels were significantly higher in continent patients than in incontinent patients at one, three, and six months postoperatively. Conclusions: Serum vitamin D may be an essential marker in regaining continence in the early period after radical prostatectomy.
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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 | 0.000 | 0.001 |
| 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) | 0.002 | 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".