Abstract TMP40: Secondary Motor Nerve Deficit Correlates With Poorer Outcome in Acute Stroke Patients
Bibliographic record
Abstract
Introduction: Anterograde degeneration after stroke leads to secondary injury of peripheral motor nerves. It remains unclear whether this secondary dysfunction affects functional improvement and whether early electrophysiological parameters could possibly predict rehabilitative outcome. Methods: A total of 43 adult patients of middle cerebral artery infarction (MCAI) within 2 weeks after onset was prospectively recruited from January 2016 to December 2017. Ten healthy subjects were recruited as control. All the subjects were investigated by electromyography to record and analyze electrophysiological parameters on admission. All the patients were evaluated by NIHSS, BI, mRS, Fugl-Meyer assessment (FMA) and Alberta Stroke Program Early CT score on admission, then by BI, mRS and FMA in the 6-month follow-up. Multiple regression analysis was used to screen the possible predictive factor for neurological outcome. Results: Twenty-six patients were with massive MCAI and 17 patients with subcortical MCAI. The compound muscle action potential (CMAP) amplitude of median, ulnar, tibial and common peroneal nerves, and motor unit number estimation in abductor of pollicis brevis were significant decreased in the hemiplegic limbs than those in the unaffected limbs and in the healthy controls, and further diminished in massive MCAI compared to those in subcortical MCAI. Fibrillation potentials / positive sharp waves in abductor digiti minimi and tibialis anterior were found in majority of patients, and were more frequently detected in massive MCAI, confirming the motor axonal deficit. CMAP amplitude of the affected ulnar nerves was significantly decreased in patients with unfavorable outcome (mRS>3) 3 and 6 months after attack, shown as an independent predictor for poorer outcome. In addition, the affected ulnar CMAP ≥10.45mV was associated with more than 50% decrement of mRS 6 months post stroke, with sensitivity and specificity of nearly 80%. Conclusions: The data indicated that secondary peripheral motor deficit occurred within 2 weeks after stroke, correlated with severity of the disease. Relatively low CMAP amplitude of hemiplegic ulnar nerve could serve as an independent factor to predict poorer outcome and worse recovery in the 6-month follow-up.
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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 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 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".