ArticleJournal of clinical medicine2023
Evolving a Model for Cochlear Implant Outcome.
Article in Journal of clinical medicine, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers, 1 of them a synthesis that pooled it.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
17 citing papers in PubMed, 1 synthesis or guideline pooled it, 19 citations in OpenAlex.
- Cochlear implantation in patients with inner ear schwannomas: a systematic review and meta-analysis of audiological outcomes.European archives of oto-rhino-laryngology : official journal of the European Federation of Oto-Rhino-Laryngological Societies (EUFOS) : affiliated with the German Society for Oto-Rhino-Laryngology - Head and Neck Surgery · 2024Pooled it
- Trial
- Article
- Machine Learning Versus Simple Clinical Models for Cochlear Implant Outcome Prediction.Audiology research · 2025Article
- Large language model-based prediction of speech intelligibility after Vibrant Soundbridge implantation using multidimensional outcome data: Part 2 of a prospective study.Scientific reports · 2025Article
- Comprehensive analysis of predictors and outcomes following Vibrant Soundbridge implantation - part 1 of a prospective study.Scientific reports · 2025Observational
- Optimizing CI Systems for Better Recognition of Soft Speech -the Concept of Broad-Range Mapping.Laryngoscope investigative otolaryngology · 2025Article
- Accuracy and variability in clinical predictions of speech recognition outcomes for cochlear implant users.International journal of audiology · 2025Article
- External Validation and Extension of a Cochlear Implant Performance Prediction Model: Analysis of the Oldenburg Cohort.Audiology research · 2025Article
- A Machine Learning Model to Predict Postoperative Speech Recognition Outcomes in Cochlear Implant Recipients: Development, Validation, and Comparison with Expert Clinical Judgment.Journal of clinical medicine · 2025Article
- [Fitting of cochlear implant systems].HNO · 2025Review
- Illness perceptions in cochlear implant users - a longitudinal study.European archives of oto-rhino-laryngology : official journal of the European Federation of Oto-Rhino-Laryngological Societies (EUFOS) : affiliated with the German Society for Oto-Rhino-Laryngology - Head and Neck Surgery · 2025Article
- Article
- Factors to Describe the Outcome Characteristics of a CI Recipient.Journal of clinical medicine · 2024Article
- Comparison of hearing performance in patients with borderline indication for active middle ear or cochlear implants: clinical outcomes to guide preoperative counseling and decision making.European archives of oto-rhino-laryngology : official journal of the European Federation of Oto-Rhino-Laryngological Societies (EUFOS) : affiliated with the German Society for Oto-Rhino-Laryngology - Head and Neck Surgery · 2024Article
- Outcome Prediction of Speech Perception in Quiet and in Noise for Cochlear Implant Candidates Based on Pre-Operative Measures.Journal of clinical medicine · 2024Article
- Article
Corrections and comments
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Authors and funding
4 authors.
Funding
Abstract
backgroundCochlear implantation is an efficient treatment for postlingually deafened adults who do not benefit sufficiently from acoustic amplification. Implantation is indicated when it can be foreseen that speech recognition with a cochlear implant (CI) is superior to that with a hearing aid. Especially for subjects with residual speech recognition, it is desirable to predict CI outcome on the basis of preoperative audiological tests. PURPOSE: The purpose of the study was to extend and refine a previously developed model for CI outcome prediction for subjects with preoperative word recognition to include subjects with no residual hearing by incorporating additional results of routine examinations.
resultsBy introducing the duration of unaided hearing loss (DuHL), the median absolute error (MAE) of the prediction was reduced. While for subjects with preoperative speech recognition, the model modification did not change the MAE, for subjects with no residual speech recognition before surgery, the MAE decreased from 23.7% with the previous model to 17.2% with the extended model.
conclusionsPrediction of word recognition with CI is possible within clinically relevant limits. Outcome prediction is particularly important for preoperative counseling and in CI aftercare to support systematic monitoring of CI fitting.
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What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.