Sudden Sensorineural Hearing Loss: Our Experience in Diagnosis, Treatment, and Outcome
Bibliographic record
Abstract
OBJECTIVES: To describe our experience concerning sudden sensorineural hearing loss (SSNHL) in a large single-institution series of SSNHL patients and to discuss the results. METHOD: This was a retrospective study, and the charts of 156 consecutive inpatients (65 males, mean age 44 years, range 10-74 years; 91 females, mean age 46 years, range 15-75 years) with the diagnosis of SSNHL from 1987 to 2000 were reviewed. One hundred forty-three of 156 patients received multidrug therapy (plasma expanders, antiaggregants, steroids), whereas only 13 SSNHL patients received hyperbaric oxygen therapy. RESULTS: Old age, vascular and metabolic risk factors, and cigarette smoking do not a have a high prevalence in the SSNHL population. An etiologic factor was detected in 23 of 156 (15%) cases (16 cases of acute infection, 4 cases of neurovascular conflicts, 2 cases of cerebellar angiomas, 1 case of cochleovestibular schwannoma). The outcome was not related to the laterality, age, or hearing loss type. On the contrary, a statistically significant association between poor recovery and male sex, both tinnitus and vertigo, and the initial severity of the hearing loss was observed. CONCLUSIONS: Mostly, SSNHL results in idiopathic disease. At present, diagnostic and therapeutic efforts appear to be inadequate to improve the prognosis of SSNHL. Further studies are needed to obtain better knowledge about the etiopathogenesis of SSNHL so that new therapeutic strategies can be considered in the treatment of this challenging ear disease.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".