Using Advanced Imaging To Evaluate Bone Quality And Relative Energy Deficiency Risk In Elite Athletes
Bibliographic record
Abstract
Relative Energy Deficiency in Sport (REDs) is a syndrome observed in athletic populations resulting from long-term low energy availability (LEA). Low bone mineral density (BMD) has emerged as a primary indicator of LEA. Areal BMD (aBMD) is typically assessed using dual X-ray absorptiometry (DXA). Recent advancements to the REDs consensus statement included an updated clinical assessment tool (CAT2). This tool includes aBMD of ≤-1.0 SD at the hip or spine or a loss in aBMD as a primary indicator of REDs risk. High-resolution peripheral quantitative computed tomography (HR-pQCT) is an advanced imaging technique able to assess volumetric BMD (vBMD) at the distal radius and tibia. The new REDs consensus statement mentions HR-pQCT as having potential to identify impaired bone health. HR-pQCT allows for the analysis of advanced parameters of vBMD, bone microarchitecture and bone geometry, which may provide additional parameters for identification of REDs risk. PURPOSE: 1) Assess the prevalence of athletes at-risk of REDs using REDs CAT2; 2) Use HR-pQCT to evaluate differences in vBMD, bone microarchitecture and geometry in athletes at-risk vs. not at-risk based on REDs CAT2. METHODS: Participants included 94 athletes (22.8 ± 3.5 years; 51% female) affiliated with the Canadian Sport Institute Calgary in predominantly elite winter sports. The REDs CAT2 was used to identify athletes at-risk and level of risk (none, mild, moderate, high) of REDs. HR-pQCT scans of the non-dominant radius and left tibia were acquired. HR-pQCT total (TtBMD), cortical (CtBMD), and trabecular (TbBMD) vBMD (mg HA/cm3), cortical thickness (CtTh, mm) and area (CtAr, mm2) were assessed. T-tests compared differences between groups. RESULTS: Eleven athletes (12%; n = 6 female) were at mild risk of REDs based on the CAT2. At the tibia, TtBMD (p = 0.004), CtTh (p = 0.004), and CtAr (p = 0.003) were lower in the mild risk group than the no risk group. Similarly, CtAr (p = 0.003) was lower at the radius. CONCLUSION: We found 12% of elite athletes were at mild risk of REDs based on the new CAT2. Using advanced imaging, total vBMD, cortical bone microarchitecture and geometry were lower in athletes at mild risk of REDs. This study agrees with the new consensus statement that HR-pQCT has the potential to identify impaired bone health in athletes at risk of REDs. Student work supported by the funding of the Dr. Cy Frank Trainee Award in Nutrition for Bone, Joint and Muscle Health by the McCaig Institute at the University of Calgary.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.007 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".