Student Competition (Knowledge Generation) ID 1985735
Bibliographic record
Abstract
Background Individuals with chronic spinal cord injury or disease (SCI/D) are at an increased risk of lower extremity fractures. Novel interventions, including nutraceuticals and pharmacotherapy, are being explored to reduce fracture-related morbidity and mortality. Objective This retrospective cohort study aims to evaluate the effectiveness of Denosumab injections with dietary calcium and vitamin D supplements on proximaltibia bone mineral density (BMD) in adults with low bone mass and chronic SCI/D. Design/Methods Adult patients with SCI/D over age 18 years, with a baseline distal femur or proximal tibia Z-score <-2.0 or T-score <-2.5 exposed to at least three doses of Denosumab 60mcg/1ml vial injections will consent to chart abstraction. The cumulative Denosumab dose will be the exposure variable. Calcium intake and vitamin D serum levels will be recorded as effect modifiers. Age, sex, and BMI will be recorded as potential confounders. The primary outcome will be the change in proximal tibia BMD from baseline and secondarily the incidence of lower extremity fracture(s). Results/Findings Demographic and impairment characteristics of the study population will be reported using appropriate descriptive statistics. The associations between mean BMD change and Denosumab exposure will be calculated and adjusted for confounders using an appropriate univariate/multivariate model based on sample size and data distribution. Conclusion This retrospective cohort study will determine the effectiveness of Denosumab injections (with calcium and vitamin D) for maintaining or increasing proximal tibia BMD among patients with chronic SCI/D. The study findings will have a significant impact on Denosumab prescribing practices.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.950 | 0.860 |
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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.
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".