Tracking Changes in Neuropathic Pain After Acute Spinal Cord Injury
Bibliographic record
Abstract
Neuropathic pain represents a primary detrimental outcome of spinal cord injury. A major challenge facing effective management is a lack of surrogate measures to examine the physiology and anatomy of neuropathic pain. To this end, we investigated the relationship between psychophysical responses to tonic heat stimulation and neuropathic pain rating after traumatic spinal cord injury. Subjects provided a continuous rating to two minutes of tonic heat at admission to rehabilitation and again at discharge. Adaptation, temporal summation of pain, and modulation profile (i.e., the relationship between adaptation and temporal summation of pain) were extracted from tonic heat curves for each subject. There was no association between any of the tonic heat outcomes and neuropathic pain severity at admission. The degree of adaptation, the degree of temporal summation of pain, and the modulation profile did not change significantly from admission to discharge. However, changes in modulation profiles between admission and discharge were significantly correlated with changes in neuropathic pain symptoms (p=0.027; R2=0.323). The modulation profile may represent an effective measure to track changes in neuropathic pain severity from early to later stages of spinal cord injury.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.001 | 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".