Trunk Muscle Activity Is Modified in Osteoporotic Vertebral Fracture and Thoracic Kyphosis with Potential Consequences for Vertebral Health
Bibliographic record
Abstract
This study explored inter-relationships between vertebral fracture, thoracic kyphosis and trunk muscle control in elderly people with osteoporosis. Osteoporotic vertebral fractures are associated with increased risk of further vertebral fractures; but underlying mechanisms remain unclear. Several factors may explain this association, including changes in postural alignment (thoracic kyphosis) and altered trunk muscle contraction patterns. Both factors may increase risk of further fracture because of increased vertebral loading and impaired balance, which may increase falls risk. This study compared postural adjustments in 24 individuals with osteoporosis with and without vertebral fracture and with varying degrees of thoracic kyphosis. Trunk muscle electromyographic activity (EMG) associated with voluntary arm movements was recorded and compared between individuals with and without vertebral fracture, and between those with low and high thoracic kyphosis. Overall, elderly participants in the study demonstrated co-contraction of the trunk flexor and extensor muscles during forwards arm movements, but those with vertebral fractures demonstrated a more pronounced co-contraction than those without fracture. Individuals with high thoracic kyphosis demonstrated more pronounced alternating flexor and extensor EMG bursts than those with less kyphosis. Co-contraction of trunk flexor and extensor muscles in older individuals contrasts the alternating bursts of antagonist muscle activity in previous studies of young individuals. This may have several consequences, including altered balance efficacy and the potential for increased compressive loads through the spine. Both of these outcomes may have consequences in a population with fragile vertebrae who are susceptible to fracture.
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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 | 0.001 |
| 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".