The interface between inhibition of descending noradrenergic pain control pathways and negative affects in post-traumatic pain patients
Bibliographic record
Abstract
BACKGROUND: Animal studies have shown that surgical trauma activates the descending noradrenergic pathway. However, perioperative patients have decreased concentrations of noradrenaline (NA) in the cerebrospinal fluid (CSF). We proposed that the descending monoaminergic pathway is altered in post-traumatic pain patients and that CSF monoamine neurotransmitters may be more closely related to affective symptoms. We investigated the levels of monoamine neurotransmitters and assessed pain in these patients. METHODS: Patients were divided into a post-traumatic pain group, a pain-free group, a painful labor group, and a pain-free labor group. CSF was collected from all patients, and concentrations of NA, 3-methoxy-4-hydroxyphenylglycol (MHPG), dopamine, homovanillic acid, and 5-hydroxyindoleacetic acid (5-HIAA) were measured by high-performance liquid chromatography. RESULTS: In the post-traumatic pain group, lumbar CSF concentrations of NA and MHPG were significantly decreased (P < 0.01) compared to the control group. The post-traumatic pain group displayed a significant negative correlation between NA and the respective total value of the short form of the McGill pain questionnaire (SF-MPQ), SF-MPQ (affective), and visual analog scale (r = -0.388, r = -0.433, and r = -0.367; P < 0.05). CONCLUSIONS: Post-traumatic pain patients demonstrated decreased concentrations of NAin CSF, indicating that descending noradrenergic pain control pathways may be inhibited. NA is more closely related to negative affects in post-traumatic pain patients.
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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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".