The effects of unilateral cochlear implantation on the tinnitus handicap inventory and the influence on quality of life
Bibliographic record
Abstract
OBJECTIVES/HYPOTHESIS: Cochlear implantation is now the standard of care in patients with significant sensorineural hearing loss. It is well known that patients with severe hearing loss also experience disabling tinnitus. The purpose of this study was to assess the effects of cochlear implants on the perception of tinnitus using the Tinnitus Handicap Inventory (THI). STUDY DESIGN: Prospective, longitudinal study of 142 cochlear implant patients. METHODS: The THI was administered to 142 patients pre- and postimplantation. Outcome measures were obtained 12 months after the implantation. Secondary analyses to examine the correlation between changes in THI scores and outcome measures such as Hearing Handicap Inventory, Hearing in Noise Test (HINT), and short-form 36 (SF-36) quality-of-life scores were performed. RESULTS: Patients demonstrated statistically significant reduction of the THI scores including its subscales (P < .001). Prior to implantation, 37% of patients described their tinnitus as moderate to severe. Postoperatively, this percentage decreased to 10%. Cochlear implantation resulted in complete tinnitus suppression in 37% and tinnitus reduction in another 29% of patients. THI scores significantly correlated with three domains of the SF-36 quality-of-life questionnaire, namely social, emotional, and general health domains. CONCLUSIONS: Cochlear implants have a significant suppressive effect on tinnitus in 66% of implant users. Although the reduction in the subjectively perceived tinnitus was statistically significant, it did not correlate with HINT; however, it did correlate with three quality-of-life domains, more significantly for those whose pretreatment conditions were moderate or worse.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".