Can exercise-based interventions reverse gray and white matter abnormalities in patients with chronic musculoskeletal pain? A systematic review
Bibliographic record
Abstract
BACKGROUND: Recent evidence has suggested that reversal of gray or white matter abnormalities could be a criterion of recovery in patients with chronic pain. OBJECTIVE: To determine the effectiveness of exercise-based interventions in reversing gray and white matter abnormalities in patients with chronic musculoskeletal pain. METHODS: An electronic search was performed in the MEDLINE (Via PubMed), EMBASE, Web of Science, LILACS, SPORTDiscus, CINAHL, PEDro, and CENTRAL databases. Randomized clinical trials (RCTs) including patients with chronic musculoskeletal pain, which assessed the change in gray and white matter abnormalities after exercise-based interventions were selected. The risk of bias was assessed using the Risk of Bias II tool. RESULTS: Four RCTs were included (n= 386). Three studies showed reversal of abnormalities with exercise-based interventions compared to control groups. The reversal was observed in the gray matter volume in the medial orbital prefrontal cortex and in the supplementary motor area of patients with osteoarthritis, in the hippocampus, insula, amygdala and thalamus in fibromyalgia patients. Furthermore, in patients with chronic spinal pain, reversal was observed in the gray matter thickness of the frontal middle caudal cortex and in the caudate, putamen and thalamus gray matter volume. CONCLUSIONS: There is insufficient evidence to determine the effectiveness of exercise-based interventions for reversing gray and white matter abnormalities in patients with chronic pain. Further studies are still needed in this field.
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.
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 | 0.003 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".