Recent advances in viral inner ear disorders
Bibliographic record
Abstract
PURPOSE OF REVIEW: To highlight the recent advances in the understanding of the diagnosis and management of viral inner ear disorders. Congenital sensorineural hearing loss (cSNHL), sudden sensorineural hearing loss (SSNHL), Ménière's disease, and vestibular neuritis/viral labyrinthitis are discussed. RECENT FINDINGS: Cytomegalovirus infection during pregnancy is an under-recognized cause of hearing loss and central nervous system disease amongst the general population. Prevention of maternal infection and treatment of affected newborns with ganciclovir are promising interventions. Recent evidence in SSNHL patients has resulted in recommendations against viral serology or the use of antivirals. There appears to be an increased risk of SSNHL in patients with comorbid hypertension and diabetes. The viral hypothesis of Ménière's disease remains unproven. In patients with an acute episode of vestibular neuritis, there is presently not sufficient evidence to support the routine use of corticosteroids or antiviral medications. SUMMARY: cSNHL remains the most clearly defined of the viral inner ear disorders. The evidence for viral involvement in SSNHL, Ménière's disease, and vestibular neuritis is indirect and equivocal. This review highlights the recent advancements in the diagnosis and management of these disorders.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.003 |
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".