Nimodipine improves vocal fold and facial motion recovery after injury: A systematic review and meta‐analysis
Bibliographic record
Abstract
INTRODUCTION: Nimodipine is a calcium channel blocker that has been used to treat hypertension and vasospasm. Emerging evidence in the literature suggests that it is neuroprotective by reducing cellular apoptosis after neuronal injury and promoting axonal sprouting at the nodes of Ranvier. OBJECTIVES: To conduct a systematic review of the usage of nimodipine in cranial nerve injury and to perform a meta-analysis to estimate the efficacy of nimodipine on functional recovery of the injured cranial nerves. METHODS: Literature search was performed in eight databases using preferred reporting items for systematic reviews and meta analyses (PRISMA) guidelines. Human studies that used nimodipine as a monotherapy for treating cranial nerve injury were included for review. Cranial nerve function recovery was the primary outcome measure. RESULTS: 672 records were screened and 58 full texts in English were assessed. Nine studies were included in the final review. 5 of these, including 110 participants who received nimodipine for either recurrent laryngeal nerve or facial nerve injury and 556 controls, were used for meta-analysis. Nimodipine significantly increased the odds of vocal fold motion recovery (odds ratio [OR] 13.73, 95% confidence interval [CI] 6.21, 30.38, P < .01), and the odds of facial motion recovery (OR 2.78, 95% CI 1.20, 6.44, P = .02). Overall, nimodipine-treated patients had significantly higher odds of recovering vocal fold or facial motion compared with controls (OR 6.09, 95% CI 3.41, 10.87, P < .01). CONCLUSION: Existing evidence supports the positive effect of nimodipine on vocal fold and facial motion recovery after injury. Future research should focus on randomized clinical trials comparing recovery rates between nimodipine- and placebo-treated groups. Laryngoscope, 129:943-951, 2019.
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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 | 0.007 | 0.019 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.015 | 0.029 |
| Bibliometrics | 0.005 | 0.005 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| 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".