Gene mutations as a non-invasive measure of adult cochlear implant performance: Variable outcomes in patients with select TMPRSS3 mutations
Bibliographic record
Abstract
BACKGROUND: The cochlear implant (CI) has proven to be a successful treatment for patients with severe-to-profound sensorineural hearing loss, however outcome variance exists. We sought to evaluate particular mutations discovered in previously established sensory and neural partition genes and compare post-operative CI outcomes. MATERIALS AND METHODS: Utilizing a prospective cohort study design, blood samples collected from adult patients with non-syndromic hearing loss undergoing CI were tested for 54 genes of interest with high-throughput sequencing. Patients were categorized as having a pathogenic variant in the sensory partition, pathogenic variant in the neural partition, pathogenic variant in both sensory and neural partition, or with no variant identified. Speech perception performance was assessed pre- and 12 months post-operatively. Performance measures were compared to genetic mutation and variant status utilizing a Wilcoxon rank sum test, with P<0.05 considered statistically significant. RESULTS: Thirty-six cochlear implant patients underwent genetic testing and speech understanding measurements. Of the 54 genes that were interrogated, three patients (8.3%) demonstrated a pathogenic mutation in the neural partition (within TMPRSS3 genes), one patient (2.8%) demonstrated a pathogenic mutation in the sensory partition (within the POU4F3 genes). In addition, 3 patients (8.3%) had an isolated neural partition variance of unknown significance (VUS), 5 patients (13.9%) had an isolated sensory partition VUS, 1 patient (2.8%) had a variant in both neural and sensory partition, and 23 patients (63.9%) had no mutation or variant identified. There was no statistically significant difference in speech perception scores between patients with sensory or neural partition pathogenic mutations or VUS. Variable performance was found within patients with TMPRSS3 gene mutations. CONCLUSION: The impact of genetic mutations on post-operative outcomes in CI patients was heterogenous. Future research and dissemination of mutations and subsequent CI performance is warranted to elucidate exact mutations within target genes providing the best non-invasive prognostic capability.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".