Educational Exposure to Transgender Patient Care in Otolaryngology Training.

OBJECTIVE: Gender dysphoria is estimated to occur in over 1 million people in the United States. With decreasing stigma regarding the transgender population, it is likely more patients will seek medical and surgical gender transition as parts of their treatment. However, otolaryngologists may lack training in gender-confirming surgery. This study aims to determine the current state of transgender-related education in the United States otolaryngology training programs and to evaluate trainee perceptions regarding the importance of such training. METHODS: A cross-sectional survey was performed among the United States otolaryngology training programs. A representative sample of 22 training programs divided within 4 US Census regions completed a cross-sectional 9-question survey between March and May 2017. Respondents were queried regarding demographics, transgender curricular exposure (didactic and/or clinical), and perceived importance of training in transgender patient care. RESULTS: A total of 285 trainees responded (69.3% response rate). Thirty percent of respondents reported education on or direct exposure to transgender care during residency. Among those with experiences in gender-confirming surgery, more than half were exposed to facial (masculinization or feminization) or pitch alteration surgery. Overall, the majority of respondents believed training in gender-confirming surgery is somewhat important and 63.2% supported incorporation of transgender patient care in existing subspecialty fellowship training. CONCLUSION: Less than one-third of otolaryngology trainees are exposed to transgender patient care. The majority of trainees endorsed the importance of residency and subspecialty fellowship training in gender-confirming surgery. To better serve the transgender population, formal didactics on gender-confirming surgery should be offered.

Autonomous Robotic Systems in Otolaryngology-Head and Neck Surgery.

Robotic surgery is a growing field with increasing applications to patient care. With the rising use of artificial intelligence (AI), a new frontier emerges, allowing semiautonomous robotics. This article reviews the origins of robotic surgery and subsequent trials of automaticity in all fields. It then describes specific nascent robotic and semiautonomous surgical prototypes within the field of otolaryngology. Finally, broader systemic considerations are posited regarding the implementation of AI-driven robotics in surgery.

Impact of Ergonomics on Muscle Fatigue During Surgical Drilling Using Surface Electromyography.

OBJECTIVE: To investigate the relationship between ergonomic positions and electromyographic muscle activity during otologic drilling. STUDY DESIGN: Cross-over experimental trial. SETTING: Tertiary Academic Medical Center. METHODS: Surgeon participants were tasked with delicate eggshell drilling in 3 different seated positions: "neutral," "slouched," and "craned." Surface electromyography (sEMG) sensors recorded the amplitude and frequency of muscle activity. The joint analysis of spectrum and amplitude (JASA) method, which combines temporal trends in frequency and amplitude, was used to identify trials that exhibited patterns of fatigue. RESULTS: The sEMG amplitude and frequency responses demonstrated wide temporal changes. In a majority of experiments, amplitude increased over the course of the experiment, while frequency remained more stable. On analysis of variance testing, only the mean frequency of the deltoid differed significantly between postures (P = .02). Under the JASA framework, external carpi radialis and upper trapezius experienced fatigue in nearly half of the trials regardless of position (47% vs 49%). The upper trapezius demonstrated fatigue during 46% and 69% of the "craned" and "slouched" trials, respectively, compared to just 31% of the "neutral" trials. Fewer attendings demonstrated upper trapezius fatigue compared to trainees (33% vs 62%). Female surgeons experienced fatigue in more trials than male counterparts (73% vs 25%). CONCLUSION: This study highlights a first step in quantifying the relationship between operating postures and muscle fatigue. Results suggest that specific muscle groups are more susceptible to fatigue; gender and experience may also impact muscle activity.

Beyond the manual touch: situational-aware force control for increased safety in robot-assisted skullbase surgery.

PURPOSE: Skullbase surgery demands exceptional precision when removing bone in the lateral skull base. Robotic assistance can alleviate the effect of human sensory-motor limitations. However, the stiffness and inertia of the robot can significantly impact the surgeon's perception and control of the tool-to-tissue interaction forces. METHODS: We present a situational-aware, force control technique aimed at regulating interaction forces during robot-assisted skullbase drilling. The contextual interaction information derived from the digital twin environment is used to enhance sensory perception and suppress undesired high forces. RESULTS: To validate our approach, we conducted initial feasibility experiments involving a medical and two engineering students. The experiment focused on further drilling around critical structures following cortical mastoidectomy. The experiment results demonstrate that robotic assistance coupled with our proposed control scheme effectively limited undesired interaction forces when compared to robotic assistance without the proposed force control. CONCLUSIONS: The proposed force control techniques show promise in significantly reducing undesired interaction forces during robot-assisted skullbase surgery. These findings contribute to the ongoing efforts to enhance surgical precision and safety in complex procedures involving the lateral skull base.

Is a Simple Checklist Associated With Improvement in Gender Representation at the AAO-HNSF Annual Meeting?

OBJECTIVE: In September 2017, the American Academy of Otolaryngology-Head and Neck Surgery (AAO-HNS) added 2 questions querying panel organizers if gender/racial diversity was considered in selecting panel presenters, beginning with the 2018 Annual Meeting (AM). This study examines how this checklist impacted the gender diversity of panel presenters at the AAO-HNS AM. STUDY DESIGN: This was a cross-sectional investigation comparing female representation before and after the addition of questions inquiring about diversity in 2018. SETTING: A review of abstract submissions for the AMs from 2015 to 2021. METHODS: AM Official Program Abstracts were used to obtain presenter names and specialty area for each panel. The percentage of female presenters, in total and stratified by specialty area, were compared before and after 2018 to quantify changes following the addition of the checklist. RESULTS: There was a significant increase in the proportion of female panel presenters from 22.3% (total n = 1199) in 2015 to 2017 to 33.0% (total n = 1868) in 2018 to 2021 (P < .001) and in all panel specialties. The number of female moderated panels also significantly increased after checklist implementation from 22% to 38% (P < .001). Correspondingly, the number of panels with no female representation decreased from 42% in 2015 to 2017 to 23% in 2018 to 2021 (P < .001). CONCLUSION: The addition of a checklist asking panel organizers to consider diversity in selecting panelists was associated with an increased proportion of female presenters at the AM. This simple strategy can be implemented by all medical conferences to help close the gender gap.

Tremor Assessment in Robot-Assisted Microlaryngeal Surgery Using Computer Vision-Based Tool Tracking.

OBJECTIVE: Use microscopic video-based tracking of laryngeal surgical instruments to investigate the effect of robot assistance on instrument tremor. STUDY DESIGN: Experimental trial. SETTING: Tertiary Academic Medical Center. METHODS: In this randomized cross-over trial, 36 videos were recorded from 6 surgeons performing left and right cordectomies on cadaveric pig larynges. These recordings captured 3 distinct conditions: without robotic assistance, with robot-assisted scissors, and with robot-assisted graspers. To assess tool tremor, we employed computer vision-based algorithms for tracking surgical tools. Absolute tremor bandpower and normalized path length were utilized as quantitative measures. Wilcoxon rank sum exact tests were employed for statistical analyses and comparisons between trials. Additionally, surveys were administered to assess the perceived ease of use of the robotic system. RESULTS: Absolute tremor bandpower showed a significant decrease when using robot-assisted instruments compared to freehand instruments (P = .012). Normalized path length significantly decreased with robot-assisted compared to freehand trials (P = .001). For the scissors, robot-assisted trials resulted in a significant decrease in absolute tremor bandpower (P = .002) and normalized path length (P < .001). For the graspers, there was no significant difference in absolute tremor bandpower (P = .4), but there was a significantly lower normalized path length in the robot-assisted trials (P = .03). CONCLUSION: This study demonstrated that computer-vision-based approaches can be used to assess tool motion in simulated microlaryngeal procedures. The results suggest that robot assistance is capable of reducing instrument tremor.

A Deep Learning Framework for Analysis of the Eustachian Tube and the Internal Carotid Artery.

OBJECTIVE: Obtaining automated, objective 3-dimensional (3D) models of the Eustachian tube (ET) and the internal carotid artery (ICA) from computed tomography (CT) scans could provide useful navigational and diagnostic information for ET pathologies and interventions. We aim to develop a deep learning (DL) pipeline to automatically segment the ET and ICA and use these segmentations to compute distances between these structures. STUDY DESIGN: Retrospective cohort. SETTING: Tertiary referral center. METHODS: From a database of 30 CT scans, 60 ET and ICA pairs were manually segmented and used to train an nnU-Net model, a DL segmentation framework. These segmentations were also used to develop a quantitative tool to capture the magnitude and location of the minimum distance point (MDP) between ET and ICA. Performance metrics for the nnU-Net automated segmentations were calculated via the average Hausdorff distance (AHD) and dice similarity coefficient (DSC). RESULTS: The AHD for the ET and ICA were 0.922 and 0.246 mm, respectively. Similarly, the DSC values for the ET and ICA were 0.578 and 0.884. The mean MDP from ET to ICA in the cartilaginous region was 2.6 mm (0.7-5.3 mm) and was located on average 1.9 mm caudal from the bony cartilaginous junction. CONCLUSION: This study describes the first end-to-end DL pipeline for automated ET and ICA segmentation and analyzes distances between these structures. In addition to helping to ensure the safe selection of patients for ET dilation, this method can facilitate large-scale studies exploring the relationship between ET pathologies and the 3D shape of the ET.

Competency-based medical education in the United States: What the otolaryngologist needs to know.

Competency-based medical education (CBME) is an outcomes-focused approach to educating medical professionals that will be central to future efforts to improve resident training in otolaryngology. The transition to CBME for otolaryngology in the United States will require the development of specialty-specific assessments and benchmarks, the financial and administrative support for implementation, the professional development of faculty and learners, and the cooperation of all major stakeholders in graduate medical education. In this article, we describe the need for evidence-based innovation in surgical training, the history of CBME in the United States, and the progress towards defining "entrustable professional activities" as the building blocks of assessments for CBME. We explore what such a paradigm shift in surgical education could mean for academic otolaryngologists by examining innovative educational practices in other surgical specialties and discussing foreseeable challenges in implementation for the American healthcare system.

A Self-Configuring Deep Learning Network for Segmentation of Temporal Bone Anatomy in Cone-Beam CT Imaging.

OBJECTIVE: Preoperative planning for otologic or neurotologic procedures often requires manual segmentation of relevant structures, which can be tedious and time-consuming. Automated methods for segmenting multiple geometrically complex structures can not only streamline preoperative planning but also augment minimally invasive and/or robot-assisted procedures in this space. This study evaluates a state-of-the-art deep learning pipeline for semantic segmentation of temporal bone anatomy. STUDY DESIGN: A descriptive study of a segmentation network. SETTING: Academic institution. METHODS: A total of 15 high-resolution cone-beam temporal bone computed tomography (CT) data sets were included in this study. All images were co-registered, with relevant anatomical structures (eg, ossicles, inner ear, facial nerve, chorda tympani, bony labyrinth) manually segmented. Predicted segmentations from no new U-Net (nnU-Net), an open-source 3-dimensional semantic segmentation neural network, were compared against ground-truth segmentations using modified Hausdorff distances (mHD) and Dice scores. RESULTS: Fivefold cross-validation with nnU-Net between predicted and ground-truth labels were as follows: malleus (mHD: 0.044 ± 0.024 mm, dice: 0.914 ± 0.035), incus (mHD: 0.051 ± 0.027 mm, dice: 0.916 ± 0.034), stapes (mHD: 0.147 ± 0.113 mm, dice: 0.560 ± 0.106), bony labyrinth (mHD: 0.038 ± 0.031 mm, dice: 0.952 ± 0.017), and facial nerve (mHD: 0.139 ± 0.072 mm, dice: 0.862 ± 0.039). Comparison against atlas-based segmentation propagation showed significantly higher Dice scores for all structures (p < .05). CONCLUSION: Using an open-source deep learning pipeline, we demonstrate consistently submillimeter accuracy for semantic CT segmentation of temporal bone anatomy compared to hand-segmented labels. This pipeline has the potential to greatly improve preoperative planning workflows for a variety of otologic and neurotologic procedures and augment existing image guidance and robot-assisted systems for the temporal bone.

Factors related to wellness and burnout in academic otolaryngology: A pre- and Post-COVID-19 analysis.

Objectives: Describe demographic and professional factors predictive of burnout in academic otolaryngology before and during the COVID-19 pandemic. Methods: In 2018 and 2020, cross-sectional surveys on physician wellness and burnout were distributed to faculty members of a single academic institution's otolaryngology department. Faculty were dichotomized into low and high burnout groups for 2018 (n = 8 high burnout, 19%) and 2020 (n = 11 high burnout, 37%). To identify protective factors against burnout, three semi-structured interviews were conducted with faculty that reported no burnout. Results: Forty-two participants (59%) in 2018 and 30 out of 49 participants (62%) in 2020 completed the survey. In multivariate analysis of 2018 survey data, full and associate professors had significantly lower odds of high burnout (OR 0.06, 95% CI 0.00-0.53; p = .03). Female gender was associated with increased in odds of high burnout (OR 15.55, 95% CI 1.86-231.74; p = .02). However, academic rank and gender did not remain independent predictors of high burnout in the 2020 survey. We identified significant differences in drivers of burnout brought on by the pandemic, including a shift from a myriad of work-related stressors in 2018 to a focus on patientcare and family obligations in 2020. Interview analysis identified three themes in faculty who reported no burnout: (1) focus on helping others, (2) happiness over compensation as currency, and (3) gratitude for the ability to have an impact. Conclusion: Approximately 20% of faculty reported high burnout before the pandemic, and this proportion nearly doubled during the pandemic. The risk factors and themes identified in this study may help academic otolaryngologists prevent burnout. Lay Summary: Factors driving burnout among academic otolaryngologists during the COVID-19 pandemic transitioned away from research, conferences, and work outside business hours toward family and patient responsibilities. Females report higher burnout and full professors report lower burnout. Level of evidence: III.

Trends in Timing and Provision of Pediatric Cochlear Implant Care During COVID-19.

Objectives: To identify trends in timing of pediatric cochlear implant (CI) care during COVID-19. Study Design: Retrospective cohort. Setting: Tertiary care center. Methods: Patients under 18 years of age who underwent CI between 1/1/2016 and 2/29/2020 were included in the pre-COVID-19 group, and patients implanted between 3/1/2020 and 12/31/2021 comprised the COVID-19 group. Revision and sequential surgeries were excluded. Time intervals between care milestones including severe-to-profound hearing loss diagnosis, initial CI candidacy evaluation, and surgery were compared among groups, as were the number and type of postoperative visits. Results: A total of 98 patients met criteria; 70 were implanted pre-COVID-19 and 28 during COVID-19. A significant increase in the interval between CI candidacy evaluation and surgery was seen among patients with prelingual deafness during COVID-19 compared with pre-COVID-19 (µ = 47.3 weeks, 95% confidence interval [CI]: 34.8-59.9 vs µ = 20.5 weeks, 95% CI: 13.1-27.9; p < .001). Patients in the COVID-19 group attended fewer in-person rehabilitation visits in the 12 months after surgery (µ = 14.9 visits, 95% CI: 9.7-20.1 vs µ = 20.9, 95% CI: 18.1-23.7; p = .04). Average age at implantation in the COVID-19 group was 5.7 years (95% CI: 4.0-7.5) versus 3.7 years in the pre-COVID-19 group (95% CI: 2.9-4.6; p = .05). The time interval between hearing loss confirmation and CI surgery was on average 99.7 weeks for patients implanted during COVID-19 (95% CI: 48.8-150) versus 54.2 weeks for patients implanted pre-COVID (95% CI: 39.6-68.8), which was not a statistically significant difference (p = .1). Conclusion: During the COVID-19 pandemic patients with prelingual deafness experienced delays in care relative to patients implanted before the pandemic.

A force-sensing surgical drill for real-time force feedback in robotic mastoidectomy.

PURPOSE: Robotic assistance in otologic surgery can reduce the task load of operating surgeons during the removal of bone around the critical structures in the lateral skull base. However, safe deployment into the anatomical passageways necessitates the development of advanced sensing capabilities to actively limit the interaction forces between the surgical tools and critical anatomy. METHODS: We introduce a surgical drill equipped with a force sensor that is capable of measuring accurate tool-tissue interaction forces to enable force control and feedback to surgeons. The design, calibration and validation of the force-sensing surgical drill mounted on a cooperatively controlled surgical robot are described in this work. RESULTS: The force measurements on the tip of the surgical drill are validated with raw-egg drilling experiments, where a force sensor mounted below the egg serves as ground truth. The average root mean square error for points and path drilling experiments is 41.7 (± 12.2) mN and 48.3 (± 13.7) mN, respectively. CONCLUSION: The force-sensing prototype measures forces with sub-millinewton resolution and the results demonstrate that the calibrated force-sensing drill generates accurate force measurements with minimal error compared to the measured drill forces. The development of such sensing capabilities is crucial for the safe use of robotic systems in a clinical context.

Intraoperative Neck Angles in Endoscopic and Microscopic Otologic Surgeries.

OBJECTIVE: To quantitatively compare the ergonomic risk of otologic surgeries performed with endoscopes and microscopes. STUDY DESIGN: Observational cross-sectional study. SETTING: Operating room of a tertiary academic medical center. METHODS: Intraoperative neck angles of otolaryngology attendings, fellows, and residents were assessed during 17 otologic surgeries using inertial measurement unit sensors. Sensors were attached midline between the shoulder blades and on the posterior scalp of participants and were calibrated just prior to beginning each case. Quaternion data were used to calculate neck angles during periods of active surgery. RESULTS: Endoscopic and microscopic cases included similar percentages of time in high-risk neck positions, 75% and 73%, respectively, according to a validated ergonomic risk assessment tool, the Rapid Upper Limb Assessment. However, microscopic cases included a higher percentage of time spent in extension (25%) compared to endoscopic cases (12%) (p < .001). When examining the magnitude of average flexion and extension angles, endoscopic and microscopic cases were not significantly different. CONCLUSION: Utilizing intraoperative sensor data, we found that both endoscopic and microscopic approaches in otologic surgery were associated with high-risk neck angles, which can result in sustained neck strain. These results suggest that optimal ergonomics may be better achieved by the consistent application of basic ergonomic principles than by changing the technology in the operating room.

Outcomes after revision of Advanced Bionics Clarion 1.2 cochlear implants.

INTRODUCTION: Cochlear implant reimplantation (CIR) for external processor upgrade or device failure is becoming increasingly common as the population of cochlear implant recipients ages. Patients with Advanced Bionics (AB) Clarion 1.2 cochlear implants may undergo CIR for device age/failure or desired technology upgrade so that they may use newer external processors that have improved connectivity features. The objective of this study was to evaluate audiologic outcomes for patients who were initially implanted with an AB Clarion 1.2 internal device and underwent CIR for technology upgrade or device failure. METHODS: Retrospective chart review was performed at a single academic medical center for patients (pediatric and adult) with an AB Clarion 1.2 internal device who underwent CIR to a later generation AB internal device and had available audiologic data. RESULTS: Forty-eight individuals with a Clarion 1.2 implant underwent CIR. Pre- and post-CIR speech understanding did not change for AzBio (p-value = 0.11, mean change = 12.1%, 95% CI = -2.9-27.2%), CNCw (p-value = 0.74, mean change = -1%, 95% CI = -10.4-12.4%), or HINT (p-value = 0.12, mean change = 19.9%, 95% CI = -2.6-42.4%) scores. Pure-tone averages improved following CIR (p-value < 0.01, mean change = 4.3 dB, 95% CI = 1.5-7.1 dB). CONCLUSIONS: Revision of AB Clarion 1.2 cochlear implants does not significantly worsen audiologic outcomes and may improve hearing in some individuals, but individual patient-level outcomes are variable.

Statistical Shape Model of the Temporal Bone Using Segmentation Propagation.

HYPOTHESIS: Automated image registration techniques can successfully determine anatomical variation in human temporal bones with statistical shape modeling. BACKGROUND: There is a lack of knowledge about inter-patient anatomical variation in the temporal bone. Statistical shape models (SSMs) provide a powerful method for quantifying variation of anatomical structures in medical images but are time-intensive to manually develop. This study presents SSMs of temporal bone anatomy using automated image-registration techniques. METHODS: Fifty-three cone-beam temporal bone CTs were included for SSM generation. The malleus, incus, stapes, bony labyrinth, and facial nerve were automatically segmented using 3D Slicer and a template-based segmentation propagation technique. Segmentations were then used to construct SSMs using MATLAB. The first three principal components of each SSM were analyzed to describe shape variation. RESULTS: Principal component analysis of middle and inner ear structures revealed novel modes of anatomical variation. The first three principal components for the malleus represented variability in manubrium length (mean: 4.47 mm; ±2-SDs: 4.03-5.03 mm) and rotation about its long axis (±2-SDs: -1.6° to 1.8° posteriorly). The facial nerve exhibits variability in first and second genu angles. The bony labyrinth varies in the angle between the posterior and superior canals (mean: 88.9°; ±2-SDs: 83.7°-95.7°) and cochlear orientation (±2-SDs: -4.0° to 3.0° anterolaterally). CONCLUSIONS: SSMs of temporal bone anatomy can inform surgeons on clinically relevant inter-patient variability. Anatomical variation elucidated by these models can provide novel insight into function and pathophysiology. These models also allow further investigation of anatomical variation based on age, BMI, sex, and geographical location.

Automated Extraction of Anatomical Measurements From Temporal Bone CT Imaging.

OBJECTIVE: Proposed methods of minimally invasive and robot-assisted procedures within the temporal bone require measurements of surgically relevant distances and angles, which often require time-consuming manual segmentation of preoperative imaging. This study aims to describe an automatic segmentation and measurement extraction pipeline of temporal bone cone-beam computed tomography (CT) scans. STUDY DESIGN: Descriptive study of temporal bone measurements. SETTING: Academic institution. METHODS: A propagation template composed of 16 temporal bone CT scans was formed with relevant anatomical structures and landmarks manually segmented. Next, 52 temporal bone CT scans were autonomously segmented using deformable registration techniques from the Advanced Normalization Tools Python package. Anatomical measurements were extracted via in-house Python algorithms. Extracted measurements were compared to ground truth values from manual segmentations. RESULTS: Paired t test analyses showed no statistical difference between measurements using this pipeline and ground truth measurements from manually segmented images. Mean (SD) malleus manubrium length was 4.39 (0.34) mm. Mean (SD) incus short and long processes were 2.91 (0.18) mm and 3.53 (0.38) mm, respectively. The mean (SD) maximal diameter of the incus long process was 0.74 (0.17) mm. The first and second facial nerve genus had mean (SD) angles of 68.6 (6.7) degrees and 111.1 (5.3) degrees, respectively. The facial recess had a mean (SD) span of 3.21 (0.46) mm. Mean (SD) minimum distance between the external auditory canal and tegmen was 3.79 (1.05) mm. CONCLUSIONS: This is the first study to automatically extract relevant temporal bone anatomical measurements from CT scans using segmentation propagation. Measurements from these models can streamline preoperative planning, improve future segmentation techniques, and help develop future image-guided or robot-assisted systems for temporal bone procedures.

Automated Registration-Based Temporal Bone Computed Tomography Segmentation for Applications in Neurotologic Surgery.

OBJECTIVE: This study investigates the accuracy of an automated method to rapidly segment relevant temporal bone anatomy from cone beam computed tomography (CT) images. Implementation of this segmentation pipeline has potential to improve surgical safety and decrease operative time by augmenting preoperative planning and interfacing with image-guided robotic surgical systems. STUDY DESIGN: Descriptive study of predicted segmentations. SETTING: Academic institution. METHODS: We have developed a computational pipeline based on the symmetric normalization registration method that predicts segmentations of anatomic structures in temporal bone CT scans using a labeled atlas. To evaluate accuracy, we created a data set by manually labeling relevant anatomic structures (eg, ossicles, labyrinth, facial nerve, external auditory canal, dura) for 16 deidentified high-resolution cone beam temporal bone CT images. Automated segmentations from this pipeline were compared against ground-truth manual segmentations by using modified Hausdorff distances and Dice scores. Runtimes were documented to determine the computational requirements of this method. RESULTS: Modified Hausdorff distances and Dice scores between predicted and ground-truth labels were as follows: malleus (0.100 ± 0.054 mm; Dice, 0.827 ± 0.068), incus (0.100 ± 0.033 mm; Dice, 0.837 ± 0.068), stapes (0.157 ± 0.048 mm; Dice, 0.358 ± 0.100), labyrinth (0.169 ± 0.100 mm; Dice, 0.838 ± 0.060), and facial nerve (0.522 ± 0.278 mm; Dice, 0.567 ± 0.130). A quad-core 16GB RAM workstation completed this segmentation pipeline in 10 minutes. CONCLUSIONS: We demonstrated submillimeter accuracy for automated segmentation of temporal bone anatomy when compared against hand-segmented ground truth using our template registration pipeline. This method is not dependent on the training data volume that plagues many complex deep learning models. Favorable runtime and low computational requirements underscore this method's translational potential.

Are Speech Perception Scores in Cochlear Implant Recipients Consistent Across Different Tests?

OBJECTIVE: Cochlear implant (CI) candidacy and postoperative outcomes are assessed using sets of speech perception tests that vary from center to center, limiting comparisons across institutions and time periods. The objective of this study was to determine if scores on one speech perception test could be reliably predicted from scores on another test. STUDY DESIGN: Arizona Biomedical (AzBio) Sentence Test, Consonant-Nucleus-Consonant word (CNCw), and Hearing in Noise Test (HINT) scores in quiet for the implanted ear were collected for individuals who received a CI between 1985 and 2019. Scores collected during the same testing session were analyzed using Bland-Altman plots to assess agreement between testing methods. Simple linear regression with logit transformation was used to generate predictive functions and 95% confidence intervals for expected mean and individual scores. SETTING: Single academic medical center. PATIENTS: A total of 1,437 individuals with a median age of 59.9 years (range, 18-95 yr) and 46% (654 of 1,437) male. INTERVENTIONS: N.A. MAIN OUTCOME MEASURES: Agreement as a function of test score, mean, variance, and correlation coefficients. RESULTS: A total of 2,052 AzBio/CNCw, 525 AzBio/HINT, and 7,187 CNCw/HINT same-session score pairings were identified. Pairwise test comparisons demonstrated limited agreement between different tests performed in the same session, and a score correlation between different speech tests revealed large variances. CONCLUSION: Transformation functions between test batteries were predictive of mean scores but performed poorly for prediction of individual scores. Point-wise comparisons of scores across CI test batteries should be used with caution in clinical and research settings.

Assessment of Sudden Sensorineural Hearing Loss After COVID-19 Vaccination.

IMPORTANCE: Emerging reports of sudden sensorineural hearing loss (SSNHL) after COVID-19 vaccination within the otolaryngological community and the public have raised concern about a possible association between COVID-19 vaccination and the development of SSNHL. OBJECTIVE: To examine the potential association between COVID-19 vaccination and SSNHL. DESIGN, SETTING, AND PARTICIPANTS: This cross-sectional study and case series involved an up-to-date population-based analysis of 555 incident reports of probable SSNHL in the Centers for Disease Control and Prevention Vaccine Adverse Events Reporting System (VAERS) over the first 7 months of the US vaccination campaign (December 14, 2020, through July 16, 2021). In addition, data from a multi-institutional retrospective case series of 21 patients who developed SSNHL after COVID-19 vaccination were analyzed. The study included all adults experiencing SSNHL within 3 weeks of COVID-19 vaccination who submitted reports to VAERS and consecutive adult patients presenting to 2 tertiary care centers and 1 community practice in the US who were diagnosed with SSNHL within 3 weeks of COVID-19 vaccination. EXPOSURES: Receipt of a COVID-19 vaccine produced by any of the 3 vaccine manufacturers (Pfizer-BioNTech, Moderna, or Janssen/Johnson & Johnson) used in the US. MAIN OUTCOMES AND MEASURES: Incidence of reports of SSNHL after COVID-19 vaccination recorded in VAERS and clinical characteristics of adult patients presenting with SSNHL after COVID-19 vaccination. RESULTS: A total of 555 incident reports in VAERS (mean patient age, 54 years [range, 15-93 years]; 305 women [55.0%]; data on race and ethnicity not available in VAERS) met the definition of probable SSNHL (mean time to onset, 6 days [range, 0-21 days]) over the period investigated, representing an annualized incidence estimate of 0.6 to 28.0 cases of SSNHL per 100 000 people per year. The rate of incident reports of SSNHL was similar across all 3 vaccine manufacturers (0.16 cases per 100 000 doses for both Pfizer-BioNTech and Moderna vaccines, and 0.22 cases per 100 000 doses for Janssen/Johnson & Johnson vaccine). The case series included 21 patients (mean age, 61 years [range, 23-92 years]; 13 women [61.9%]) with SSNHL, with a mean time to onset of 6 days (range, 0-15 days). Patients were heterogeneous with respect to clinical and demographic characteristics. Preexisting autoimmune disease was present in 6 patients (28.6%). Of the 14 patients with posttreatment audiometric data, 8 (57.1%) experienced improvement after receiving treatment. One patient experienced SSNHL 14 days after receiving each dose of the Pfizer-BioNTech vaccine. CONCLUSIONS AND RELEVANCE: In this cross-sectional study, findings from an updated analysis of VAERS data and a case series of patients who experienced SSNHL after COVID-19 vaccination did not suggest an association between COVID-19 vaccination and an increased incidence of hearing loss compared with the expected incidence in the general population.