The Development of Adolescent Chronic Pain following Traumatic Brain Injury and Surgery: The Role of Diet and Early Life Stress
Bibliographic record
Abstract
Pain is evolutionarily necessary for survival in that it reduces tissue damage by signaling the body to respond to a harmful stimulus. However, in many circumstances, acute pain becomes chronic, and this is often dysfunctional. Adolescent chronic pain is a growing epidemic with an unknown etiology and limited effective treatment options. Given that the relationship between acute pain and chronic pain is not straightforward, there is a need to better understand the factors that contribute to the chronification of pain. Since early life factors are critical to a variety of outcomes in the developmental and adolescent periods, they pose promise as potential mechanisms that may underlie the transition from acute to chronic pain. This review examines two early life factors: poor diet and adverse childhood experiences (ACEs); they may increase susceptibility to the development of chronic pain following surgical procedures or traumatic brain injury (TBI). Beyond their high prevalence, surgical procedures and TBI are ideal models to prospectively understand mechanisms underlying the transition from acute to chronic pain. Common themes that emerged from the examination of poor diet and ACEs as mechanisms underlying this transition included: prolonged inflammation and microglia activation leading to sensitization of the pain system, and stress-induced alterations to hypothalamic-pituitary-adrenal axis function, where cortisol is likely playing a role in the development of chronic pain. These areas provide promising targets for interventions, the development of diagnostic biomarkers, and suggest that biological treatment strategies should focus on regulating the neuroinflammatory and stress responses in an effort to modulate and prevent the development of chronic pain.
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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 | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".