Increased motor cortex inhibition as a marker of compensation to chronic pain in knee osteoarthritis
Bibliographic record
Abstract
This study aims to investigate the associative and multivariate relationship between different sociodemographic and clinical variables with cortical excitability as indexed by transcranial magnetic stimulation (TMS) markers in subjects with chronic pain caused by knee osteoarthritis (OA). This was a cross-sectional study. Sociodemographic and clinical data were extracted from 107 knee OA subjects. To identify associated factors, we performed independent univariate and multivariate regression models per TMS markers: motor threshold (MT), motor evoked potential (MEP), short intracortical inhibition (SICI), intracortical facilitation (ICF), and cortical silent period (CSP). In our multivariate models, the two markers of intracortical inhibition, SICI and CSP, had a similar signature. SICI was associated with age (β: 0.01), WOMAC pain (β: 0.023), OA severity (as indexed by Kellgren-Lawrence Classification) (β: - 0.07), and anxiety (β: - 0.015). Similarly, CSP was associated with age (β: - 0.929), OA severity (β: 6.755), and cognition (as indexed by the Montreal Cognitive Assessment) (β: - 2.106). ICF and MT showed distinct signatures from SICI and CSP. ICF was associated with pain measured through the Visual Analogue Scale (β: - 0.094) and WOMAC (β: 0.062), and anxiety (β: - 0.039). Likewise, MT was associated with WOMAC (β: 1.029) and VAS (β: - 2.003) pain scales, anxiety (β: - 0.813), and age (β: - 0.306). These associations showed the fundamental role of intracortical inhibition as a marker of adaptation to chronic pain. Subjects with higher intracortical inhibition (likely subjects with more compensation) are younger, have greater cartilage degeneration (as seen by radiographic severity), and have less pain in WOMAC scale. While it does seem that ICF and MT may indicate a more acute marker of adaptation, such as that higher ICF and MT in the motor cortex is associated with lesser pain and anxiety.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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 | 0.000 |
| 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 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".