Cervical Vestibular-Evoked Myogenic Potentials in Individuals with Diabetes Mellitus: A Systematic Review and Meta-Analysis
Bibliographic record
Abstract
Vestibular evoked myogenic potentials (VEMPs) in individuals with diabetes mellitus (DM) provide evidence as how diabetes can bring about changes in the peripheral nervous system. Cervical VEMP (cVEMP) evaluates the function and integrity of the sacullo- collic pathway and ocular VEMP (oVEMP) evaluates the utriculo-collic pathway. cVEMP is an ipsilateral inhibitory response of the sternocleidomastoid muscle. cVEMP is recorded at higher intensity above 80-85 dBnHL with biphasic waveforms having initial peak positivity P13 followed by a negativity N23. We performed a systematic review following the preferred reporting items for systematic reviews and meta-analyses (PRISMA) guidelines to evaluate cVEMP in diabetes mellitus. The search was conducted in the databases: PubMed, Cumulative Index of Nursing and Allied Health Literature, Scopus, and Cochrane library using the keywords "diabetes mellitus" and "vestibular evoked myogenic potential" or "cVEMP." A two-phase selection process was used for the final inclusion of studies, and the methodological quality of these studies was assessed using the Newcastle Ottawa scale (NCOS). Meta-analysis was performed using a random-effects model. For comparisons between DM and healthy controls, a significant difference was observed for cVEMP amplitude (P = 0.01). Our meta-analysis's results suggest peripheral vestibular dysfunction can be observed in DM. It appears that cVEMPs may be useful in the early detection of neuropathy in DM.
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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 | 0.009 | 0.023 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.015 | 0.023 |
| Bibliometrics | 0.007 | 0.008 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".