Intratympanic dexamethasone in sudden sensorineural hearing loss: A systematic review and meta‐analysis
Bibliographic record
Abstract
OBJECTIVE: Systemic dexamethasone has demonstrated conclusive benefits in reversing sudden sensorineural hearing loss (SSNHL) despite considerable number of potential side effects. In contrast, the intratympanic route of steroid administration averts several possible complications. This study aims to examine the literature to delineate the efficacy and side effect of intratympanic dexamethasone (ITD) injection for the treatment of SSNHL. DATA SOURCE: Cochrane, Embase, and MEDLINE electronic databases from January 1950 to August 2014, with an update performed on November 10, 2014. REVIEW METHODS: Systematic review and meta-analysis of randomized controlled clinical trials (RCCTs), using the Preferred Reporting Items for Systematic Reviews and Meta-Analyses flow diagram and guidelines. Quality assessment was performed using The Cochrane Collaboration Tool for Assessing Risk of Bias. RESULTS: Eight RCCTs on SSNHL were included Three of the eight studies had high risk of bias. Substantial heterogeneity was found. The meta-analysis failed to detect statistically significant difference between ITD and alternative treatment (odds ratio = 0.39, 95% credible intervals = 0.11-1.27). The side-effects profile was favorable for ITD. No serious adverse events were recorded. CONCLUSION: There is no sufficient scientific evidence to support a difference between ITD and alternative therapy for SSNHL. We recommend larger RCCTs to determine the effectiveness of ITD compared to oral steroid therapy. We encourage a shift in study design selection toward noninferiority or superiority studies. Avoiding systemic corticotherapy, especially in vulnerable populations, should be the rationale for future research in the field. Laryngoscope, 127:1897-1908, 2017.
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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 | 0.013 | 0.029 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.019 | 0.037 |
| Bibliometrics | 0.006 | 0.007 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.003 | 0.002 |
| 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".