Assessment of Posterior Spinal Cord Function with Electrical Perception Threshold in Spinal Cord Injury
Bibliographic record
Abstract
The objective of this study was to evaluate the relevant sensory spinal pathways involved in conveying conduction of electrical perceptual threshold (EPT). In 34 individuals with cervical spinal cord injury (SCI) and eight healthy control subjects, combined EPT and electrical pain perception (EPP), and dermatomal somatosensory evoked potentials (dSSEP) from cervical dermatomes were examined. Stimulation intensities for EPT were recorded to determine quantitative sensory perception and related neurophysiological dSSEP interpretation of posterior spinal cord conduction based on onset latency and waveform configuration. The preservation of EPP in dermatomes was examined relative to EPT to dissociate the involvement of the posterior (dorsal horn and ascending dorsal column) and anterior (decussating and ascending spinothalamic fibers) spinal cord according to different nerve fiber recruitment in the periphery. Pathological EPT values were significantly (p < 0.05) accurate at predicting pathological and abolished dSSEP recordings (>80%), and the mean EPT of pathological and abolished dSSEPs was significantly (p < 0.05) increased compared to non-affected and control dSSEPs. dSSEPs demonstrated normal early onset latency at perceptually low stimulation intensities (<2.5 mA), and selectively absent EPP was dissociated from preserved EPT and/or dSSEP in 22.2% of dermatomes with incomplete sensory deficit. The relationship between EPT and dSSEP interpretation, dSSEP early onset latency and perceptual stimulation intensity, and the dissociation of EPT from EPP suggests that EPT is conducted within the posterior spinal cord. The combination of EPT and EPP with dSSEPs provides reliable quantitative sensory information to assess the segmental integrity of the posterior and anterior spinal cord, and may improve the sensitivity to monitor changes in sensory function after SCI.
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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) | 0.001 | 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 | 0.001 | 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".