The association between physiological markers of stress response systems and experimentally induced pain assessments in chronic primary pain : a systematic review and meta-analysis
Bibliographic record
Abstract
Background and aims: Besides psychological distress, (dys)functioning of stress systems, i.e. the autonomic nervous system (ANS) and hypothalamuspituitary-adrenal (HPA-)axis, has been implicated in pain. However, the exact interplay between (re)activity of stress and pain systems in chronic pain remains unclear. This study will synthesize the evidence regarding their interactions in chronic pain. Methods: A systematic review and meta-analysis was pre-registered on PROSPERO (CRD42024495934). Six databases were searched to identify studies examining at least one physiological stress marker of ANS or HPA-axis reflecting basal levels, reactivity and/or recovery, and one experimental outcome measure of pain in adults with chronic primary pain. Risk of bias (RoB) was evaluated with the Newcastle-Ottawa Scale, and certainty of evidence (CoE) with GRADE. Results: Forty-six studies (3 cross-sectional, 43 case-control; n=2407) were included and scored averagely 9/12 (5-11) on RoB. Overall CoE was (very) low. At baseline, qualitative analyses showed significant correlations between lower mean arterial pressure and higher pain sensitivity in patients with chronic pain which was confirmed in the meta-analyses (r=.301-.373, p=.013-.033). Furthermore, meta-analyses showed that higher cortisol levels were associated with lower pressure pain thresholds (PPTs) at baseline. Higher heart rate was associated with lower PPTs, and lower high-frequency heart rate variability with lower cold pain tolerance when stress markers were measured both during and after a stressor (r=.218-.429, p=.009-.050). Conclusions: Dysregulation of baroreceptor and HPA-axis functioning seems to be related to higher pain sensitivity at baseline, and autonomic dysfunction might be related to higher pain sensitivity under acute stress in patients. However, the evidence is low and limited.
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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 | 0.007 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.007 | 0.013 |
| 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".