Changes in Brain GABA and Glutamate and Improvements in Physical Functioning Following Intensive Pain Rehabilitation in Youth With Chronic Pain
Bibliographic record
Abstract
Intensive interdisciplinary pain treatments (IIPT) have been developed to treat youth with unmanaged chronic pain and functional disability. Dysregulation of metabolites gamma-aminobutyric acid (GABA) and glutamate are thought to play a role in the chronification of pain due to imbalances in inhibition and excitation in adults. Using magnetic resonance spectroscopy (MRS), we investigated the effect of IIPT on GABA and Glx (glutamate + glutamine) in 2 pain-related brain regions: the left posterior insula (LPI) and the anterior cingulate cortex (ACC). Data were collected in 23 youth (mean age = 16.09 ± 1.40, 19 female) at entry and discharge from a hospital-based outpatient IIPT. GABA and Glx were measured using GABA-edited MEGA-PRESS and analyzed using Gannet. Physical measures including a 6-minute walk test were recorded, and patients completed the PLAYSelf Physical Literacy Questionnaire, PROMIS Pain Interference Questionnaire, and Functional Disability Inventory. LPI GABA (P < .05) significantly decreased, but not ACC GABA (P > .05), following IIPT. There were no significant Glx changes (P > .05). The decrease in LPI GABA was associated with increased distance in the 6-minute walk test (P < .001). IIPT may decrease GABAergic inhibitory tone within the LPI, thereby promoting plasticity and contributing to improvements in physical outcomes with IIPT. PERSPECTIVE: Regional GABA changes are associated with a reduction in pain interference and improvement in physical function in youth following intensive pain rehabilitation. GABA may serve as a possible biomarker for IIPT; and may also further aid in the development of IIPT, and other treatments for chronic pain in youth.
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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 | 0.000 |
| 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".