Gadolinium enhancement in cervical dorsal roots in a patient with acute autonomic and sensory neuropathy: a case report
Bibliographic record
Abstract
BACKGROUND: We report an enhancement of the dorsal roots on gadolinium-enhanced cervical magnetic resonance imaging (MRI) in a patient with acute autonomic and sensory neuropathy (AASN). CASE PRESENTATION: A 38-year-old woman visited our university hospital for dizziness and fainting while rising from sitting or lying down and a tingling sensation in the whole body, including her limbs, torso, and abdomen, which was sustained for 15 days. The patient had hyperalgesia in nearly her entire body and slight motor weakness in her bilateral upper and lower limbs. Autonomic dysfunction was confirmed using autonomic testing. Furthermore, the nerve conduction study showed an absence of sensory nerve action potentials in all evaluated peripheral nerves. Cervical MRI was performed 18 days after dysautonomia onset. In the axial T1-gadolinum-enhanced MRIs, enhancement in cervical ventral and dorsal nerve roots and the posterior column of the spinal cord were observed, and the axial T2-weighted MRI showed high signal intensity in the posterior column of the cervical spinal cord. Considering the clinical, electrophysiological and imaging findings, the patient was diagnosed with AASN. A total dose of 90 g (2 g/kg) of intravenous immunoglobulin was administered over 5 days. At the follow-up at 4 years after AASN symptom onset, the hyperalgesia and orthostatic hypotension symptoms improved. However, her systolic blood pressure intermittently decreased to < 80 mmHg. CONCLUSION: Gadolinium-enhanced MRI may facilitate the accurate and prompt diagnosis of AASN.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.004 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".