Serum 25(OH)D is associated with an altered bone turnover marker response after a hip fracture
Bibliographic record
Abstract
C-terminal telopeptide of type I collagen (CTX) and procollagen type 1 N-terminal propeptide (P1NP) are bone turnover markers (BTMs) that are promising surrogate measures of fracture healing; however, it is unknown if their response is affected by other bone healing metabolites. Since 70% of fracture patients are reported to have insufficient serum vitamin D, we sought to determine if serum 25(OH)D levels are associated with differential changes in CTX and P1NP concentrations after hip fracture. This prospective cohort included hip fracture patients 65 years of age or older admitted to one of eight Baltimore-area hospitals. Serum samples were collected at baseline, 2-, 6-, and 12-month post-fracture. A mixed-effects repeated-measures analysis was used to determine the longitudinal association between vitamin D deficiency (25(OH)D < 20 ng/ml) and CTX and P1NP. Baseline lab values were obtained for 296 participants (mean age, 80.8 years; 51% male; 55% 25(OH)D < 20 ng/ml). During the acute fracture healing period P1NP concentrations increased by 14% (95%CI: 7-21%, p < 0.01) while CTX levels did not change (p = 0.07). Both CTX and P1NP decreased below baseline at 6 and 12 months. CTX levels were higher in participants with baseline 25(OH)D < 20 ng/ml (p = 0.01). There was no association between 25(OH)D < 20 ng/ml and P1NP levels over the study duration (p = 0.33). Data from this large, longitudinal cohort support claims that CTX and P1NP concentrations change during fracture healing; however, the differential response of CTX among vitamin D deficient patients highlights important questions for its utility as a reliable surrogate marker of fracture healing. © 2018 Orthopaedic Research Society. Published by Wiley Periodicals, Inc. J Orthop Res.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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".