Systematic review and meta‐analysis of the risk factors for sudden sensorineural hearing loss in adults
Bibliographic record
Abstract
OBJECTIVES/HYPOTHESIS: To review the medical literature evidence of potential risk factors for sudden sensorineural hearing loss (SSNHL) in the adult general population. STUDY DESIGN: Systematic review of prospective and retrospective studies; meta-analysis of case-controlled studies. METHODS: Three researchers independently reviewed MEDLINE (January 1, 1950-November 30, 2010), Embase (January 1, 1980-November 30, 2010), and Evidence-Based Medicine Reviews databases in addition to conducting a manual reference search. Randomized controlled trials, prospective cohort studies, consecutive/nonconsecutive case series, and retrospective reviews in which a clear definition of SSNHL was stated were included in the study. Researchers individually extracted data regarding patient information and the presumed risk factors. Discrepancies were resolved by mutual consensus. RESULTS: Twenty-two articles met the inclusion criteria. Cardiovascular risk factors (smoking, increased alcohol consumption) appeared to be associated with a higher risk of developing SSNHL. A low level of serum folate may also be implicated as a risk factor. Factor V Leiden and MTHFR gene polymorphisms were found to occur more frequently in patients with SSNHL in several studies, suggesting these inherited prothrombophilic mutations could be independent risk factors of SSNHL. CONCLUSIONS: Acquired and inherited cardiovascular risk factors appeared to be associated with an increased risk of developing SSNHL.
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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 | 0.032 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.014 | 0.014 |
| Bibliometrics | 0.007 | 0.007 |
| Science and technology studies | 0.000 | 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".