Effects of preoperative serum vitamin D levels on early clinical function outcomes and the moderate-to-severe pain prevalence in postmenopausal women after primary total knee arthroplasty
Bibliographic record
Abstract
OBJECTIVE: To investigate the impact of vitamin D levels on early clinical function outcomes and the potential risk factors of moderate-to-severe pain prevalence in postmenopausal women after primary total knee arthroplasty (TKA). METHODS: From April 2017 to December 2019, 226 women were retrospectively recruited. The women were divided into two groups based on their preoperative serum 25-hydroxyvitamin D levels: (1) vitamin D-sufficient group (≥30 ng/mL); (2) vitamin D-deficient group (<30 ng/mL). The visual analog scale, Western Ontario and McMaster Arthritis Index score, and Knee Society Score were used to evaluate clinical outcomes. Risk factors for developing postoperative moderate-to-severe knee pain were studied using multivariate binary logistic regression analyses. RESULTS: There was no significant difference in preoperative clinical function assessment between the two groups. The difference in postoperative Western Ontario and McMaster Arthritis Index score between the two groups was statistically significant (15.3 ± 0.7 vs 15.6 ± 0.7: P = 0.02). However, the differences in postoperative visual analog scale and Knee Society Score scores between the two groups were not significant (P > 0.05). The incidence of postoperative moderate-to-severe pain was 16.4% (95% CI 11.8%-21.9%). Multivariate logistic regression analysis revealed that vitamin D deficiency, smoking, and high body mass index were potential risk factors for moderate-to-severe knee pain in postmenopausal women early after TKA (P < 0.05). CONCLUSION: Preoperative vitamin D deficiency may adversely affect early functional outcomes in postmenopausal women after TKA. In addition, vitamin D deficiency, smoking, and high body mass index were independent risk factors for moderate-to-severe knee pain after surgery.
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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 | 0.003 |
| 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".