Despite decades of success with cochlear implants, adult utilization remains low. Many patients who could benefit are never referred, often because clinicians lack simple, practical tools to identify candidates, especially those who fall into a gray zone between hearing aid benefit and clear implant eligibility. A study published in JAMA Otolaryngology–Head & Neck Surgery aims to address this gap with a straightforward risk-stratification system based on routine audiometric data.
Researchers including corresponding author Matthew A. Shew, MD, of the Department of Otolaryngology Head & Neck Surgery at Washington University School of Medicine in St Louis, developed a four-level staging system that estimates a patient’s likelihood of meeting cochlear implant candidacy criteria. Rather than labeling patients as “candidates” or “noncandidates,” the tool provides a probability-based assessment that may better support shared decision-making and counseling.
The retrospective cohort study included 1,312 ears with complete audiometric data drawn from a large institutional cochlear implant registry. The researchers focused on patients who were not obvious candidates by excluding those with profound hearing loss and near-zero word recognition, because this is where referral decisions are most challenging.
The main measure used to define cochlear implant candidacy was a consonant-nucleus-consonant word score of 50% or lower, in line with current American Cochlear Implant Alliance recommendations. The researchers used conjunctive consolidation to combine two routinely available measures: pure tone average (PTA) and unaided word recognition score (WRS). This statistical method groups patients into clinically meaningful categories that reflect combined severity rather than relying on a single cutoff.
The resulting four stages showed a clear and clinically intuitive increase in the likelihood of qualifying for a cochlear implant. In stage 0, representing relatively preserved hearing, only 2.8% of ears met candidacy criteria. In stage 1, the likelihood rose to 47%. Stage 2 had a 72.3% chance of qualifying, while stage 3—those with the poorest hearing and speech understanding—had an 88.5% likelihood of candidacy. The model demonstrated strong discrimination, with a C statistic of 0.83.
Secondary measures of candidacy included binaural AzBio sentence scores of 60% or lower in quiet or at a +10 dB signal-to-noise ratio, based on the better-hearing ear. Although overall qualification rates were lower with sentence testing, the same stepwise pattern across stages remained, and model performance remained strong.
Adding demographic or clinical variables such as age, duration of hearing loss, or etiology did not improve predictive performance. As a result, the final tool relies only on PTA and WRS, which are data already available from a standard audiogram, making it easy to apply in everyday practice.
The researchers note that their proposed staging system is intended as an adjunct to patient-clinician joint decision-making. “Clinical judgment remains central to cochlear implant referral decision, but awareness of evolving indications is often limited,” they wrote. “Many may not be familiar with candidacy criteria that extend beyond profound hearing loss and near-zero WRS and may hesitate to refer patients who must travel long distances without high certainty that a cochlear implant will be recommended.”
By moving beyond binary screening rules like the widely used 60/60 guideline, they added, the proposed staging system may help clinicians better counsel borderline patients, set expectations, and decide when a referral for cochlear implant evaluation is warranted. “Ongoing refinement and prospective validation will be important for successful integration into clinical practice,” they concluded.
Dr. Shew reported grants from the National Institute on Deafness and Other Communication Disorders during the conduct of the study. Disclosures can be found in the study.
