Conditioned Pain Modulation Decreases Over Time in Patients With Neuropathic Pain Following a Spinal Cord Injury
Bibliographic record
Abstract
BACKGROUND: Neuropathic pain is a major problem following spinal cord injury (SCI). Central mechanisms involved in the modulation of nociceptive signals have been shown to be altered at the chronic stage, and it has been hypothesized that they might play a role in the development of chronic pain. OBJECTIVE: This prospective longitudinal study aimed to describe the evolution of pain modulation mechanisms over time after SCI, and to explore the relationships with the presence of clinical (neuropathic and musculoskeletal) pain. METHODS: Patients with an SCI were assessed on admission (n = 35; average of 38 days postinjury) and discharge (n = 25; average of 131 days postinjury) using the International Spinal Cord Injury Pain Basic Data Set. Conditioned pain modulation was assessed using the cold pressor test (10 °C; 120 s) as the conditioning stimulus and tonic heat pain, applied above the level of injury, as the test stimulus (120 s). Heat pain threshold was also assessed. RESULTS: = .010). This decrease was observed only in patients already suffering from neuropathic pain at admission and was not explained by a general increase in sensitivity to thermal nociceptive stimuli. CONCLUSION: These results suggest that the presence of neuropathic pain leads to a decrease in conditioned pain modulation over time, rather than supporting the hypothesis that inefficient conditioned pain modulation mechanisms are leading to the development of neuropathic 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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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) | 0.002 | 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".