Bone Loss and Muscle Atrophy in Spinal Cord Injury: Epidemiology, Fracture Prediction, and Rehabilitation Strategies
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Individuals with spinal cord injury (SCI) often experience bone loss and muscle atrophy. Muscle atrophy can result in reduced metabolic rate and increase the risk of metabolic disorders. Sublesional osteoporosis predisposes individuals with SCI to an increased risk of low-trauma fracture. Fractures in people with SCI have been reported during transfers from bed to chair, and while being turned in bed. The bone loss and muscle atrophy that occur after SCI are substantial and may be influenced by factors such as completeness of injury or time postinjury. A number of interventions, including standing, electrically stimulated cycling or resistance training, and walking exercises have been explored with the aim of reducing bone loss and/or increasing bone mass and muscle mass in individuals with SCI. Exercise with electrical stimulation appears to increase muscle mass and/or prevent atrophy, but studies investigating its effect on bone are conflicting. Several methodological limitations in exercise studies with individuals with SCI to date limit our ability to confirm the utility of exercise for improving skeletal status. The impact of standing or walking exercises on muscle and bone has not been well established. Future research should carefully consider the study design, skeletal measurement sites, and the measurement techniques used in order to facilitate sound conclusions.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.005 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.003 |
| 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 it