Contact heat evoked potentials reveal distinct patterns of spinal cord impairment in degenerative cervical myelopathy beyond <scp>MRI</scp> lesions
Bibliographic record
Abstract
Abstract Background Magnetic resonance imaging may suggest spinal cord compression and structural lesions in degenerative cervical myelopathy (DCM) but cannot reveal functional impairments in spinal pathways. We aimed to assess the value of contact heat evoked potentials (CHEPs) in addition to MRI and hypothesized that abnormal CHEPs may be evident in DCM independent of MR‐lesions and are related to dynamic mechanical cord stress. Methods Individuals with DCM underwent neurologic examination including segmental sensory (pinprick, light touch) and motor testing. The presence or absence of hyperintense signal on T2‐weighted MRI (T2‐positive/negative) was assessed. Phase‐contrast MRI was used to assess spinal cord motion as an indicator of dynamic mechanical stress. Dermatomal somatosensory evoked potentials and CHEPs were recorded after stimulation of dermatomes C6, C8, and T4 (CHEPs only) to assess spinal cord integrity. Results Of 138 individuals included in this study (age 56 ± 13 years), 35% (N = 48) presented with T2‐positive and 65% (N = 90) presented with T2‐negative DCM. Abnormal CHEPs were present in T2‐positive DCM (C6:41%; C8:32%; T4:24%) and T2‐negative DCM (C6:35%; C8:54%; T4:26%). Multisegmental CHEP abnormalities at C6 and C8 were related to increased spinal cord motion (p = 0.030; ϵ2 = 0.072), and reduced upper extremity pinprick (p = 0.046; ϵ2 = 0.063) and motor scores (p = 0.005; ϵ2 = 0.108). Conclusions CHEPs revealed distinct patterns of spinal cord impairment independent of structural T2‐positive lesions, which were associated with measures of cord motion. CHEPs thus provide valuable complementary diagnostic insights into spinal cord integrity beyond MRI. This is especially important in incipient myelopathy to inform early diagnosis and timely interventions before the development of definite cord lesions.
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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 | 0.001 | 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) | 0.003 | 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".