Sex differences in cardiac and autonomic response to clinical and experimental pain in LBP patients
Bibliographic record
Abstract
Rehabilitation professionals are currently using heart rate (HR) in order to assess the sincerity of effort in certain evaluations. It has been shown that a relation exists between HR and pain but no study has measured cardiac response during both clinical and experimental pain among a patient population using an intra-subject design. Thirty patients with low back pain (LBP) participated in this study including 16 men. Clinical pain was induced by applying a postero-anterior pressure (PA) on a painful lumbar segment for 15 and 30s in order to reproduce the patient's typical LBP at an intensity ranging between 50 and 70/100. Experimental pain was induced with a 15s thermal stimulus at a temperature which reproduced the same pain intensity as the 15s PA. For both reproduced clinical pain durations, we observed a rise in HR ranging between 8.5% and 12.67%. However, unlike men, women's cardiac response failed to show a constant rise in HR during the 30s PA. For all subjects, the rise in HR was much lower during the experimental pain condition (p<0.001), reaching only 5%. On the other hand, galvanic skin responses were significantly higher during the experimental pain condition (p<0.001). During this same condition, women also had a greater rise in galvanic skin responses than men (p=0.04). Finally, a significant correlation was found between both types of pain. These results suggest that pain induced during a clinical evaluation will produce a significant HR augmentation. However, heart rate variability analysis showed greater sympathetic cardiac regulation for men. The sex differences observed in this study call for caution when interpreting HR during pain assessment.
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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 | 0.002 |
| 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) | 0.002 | 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".