Systematic review of the evidence for the etiology of adult sudden sensorineural hearing loss
Bibliographic record
Abstract
OBJECTIVES/HYPOTHESIS: To determine the evidence for different etiologies of sudden sensorineural hearing loss (SSNHL) identified by clinical diagnostic tests in the adult population. STUDY DESIGN: Systematic literature review. METHODS: Review of MEDLINE (1950-October 2009), EMBASE (1980-October 2009), and EBM Review databases in addition to manual reference search of identified papers. Randomized controlled trials, prospective cohort studies, and retrospective reviews of consecutive patients in which a clear definition of SSNHL was stated and data from consecutive patients were reported with respect to etiology of hearing loss. Three researchers independently extracted data regarding patient demographic information, diagnostic tests employed, and the identified presumed etiologies. Discrepancies were resolved by mutual consensus. RESULTS: : Twenty-three articles met the inclusion criteria. The first group of papers searched for different etiologies among patients with SSNHL. Multiple etiologies were identified, including viral infection, vascular impairment, autoimmune disease, inner ear pathology, and central nervous system anomalies. The diagnosis for the majority of patients remained idiopathic. The second group of papers evaluated SSNHL patients with specific diagnostic tests such as autoimmune markers, hemostatic parameters, and diagnostic imaging. CONCLUSIONS: The suspected etiologies for patients suffering sudden sensorineural hearing loss included idiopathic (71.0%), infectious disease (12.8%), otologic disease (4.7%), trauma (4.2%), vascular or hematologic (2.8%), neoplastic (2.3%), and other causes (2.2%). Establishment of a direct causal link between SSNHL and these etiologies remains elusive. Diagnostic imaging is a useful method for identification of temporal bone or intracranial pathology that can present with SSNHL as a primary symptom.
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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 | 0.011 | 0.060 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.008 | 0.005 |
| Bibliometrics | 0.016 | 0.013 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".