Citations

Objective To evaluate cochlear implant speech perception among patients with sporadic inner ear schwannoma who underwent ipsilateral implantation. Study Design Retrospective multi-institutional cohort study. Setting Eleven tertiary academic medical centers across Germany, Denmark, and the United States. Patients One hundred six patients with sporadic inner ear schwannoma who received an ipsilateral cochlear implant from 2011 to 2022. Interventions Ipsilateral cochlear implantation with observation, stereotactic radiosurgery, or microsurgery for tumor management. Main Outcome Measures Monosyllabic speech perception testing scores and rates of open-set speech perception. Results Among 106 patients studied, 101 (95%) achieved open-set speech perception with a median of 24 months (interquartile range [IQR] 12–42 mo) of audiometric follow-up. Median ipsilateral monosyllabic speech perception testing achieved was 72% (IQR 54–85%), and median ipsilateral AzBio in quiet was 75% (IQR 46–90%). Most (91 of 106 [86%]) underwent microsurgery for tumor control, with cochlear implantation performed simultaneously in 98% (89 of 91) of these patients. The ability to achieve gross total resection significantly differed by tumor complexity, with 97% of low-complexity tumors, 100% of intermediate complexity, and 0% of high-complexity tumors undergoing gross total resection (p < 0.001). However, among patients managed with microsurgery, there was not a statistically significant difference in post-cochlear implantation monosyllabic speech perception scores across complexity groupings, with median scores of 75 and 70% for patients with tumors of low or intermediate complexity and those with tumors of high complexity, respectively (p = 0.5). Eight of 102 patients (8%) assessed experienced deterioration in cochlear implant performance over time. Among the subset of 39 patients with available MRI to review, the region of surveillance interest could be visualized postoperatively on MRI in all cases. Conclusions Open-set speech perception is achieved in most patients with inner ear schwannoma undergoing ipsilateral cochlear implantation. Although cochlear implantation in high-complexity inner ear schwannomas is only possible with incomplete tumor resection, long-term open-set speech perception outcomes are similar to lower-complexity tumors.

Abstract Deep learning is revolutionizing medical imaging analysis by enabling the classification of various pathoanatomical conditions at scale. Unfortunately, there have been a limited number of accurate and efficient machine learning (ML) algorithms that have been developed for the diagnostic workup of morphological hip pathologies, including developmental dysplasia of the hip and femoroacetabular impingement. The current study reports on the performance of a novel ML model with YOLOv5 and ConvNeXt-Tiny architecture in predicting the morphological features of these conditions, including cam deformity, ischial spine sign, dysplastic appearance, and other abnormalities. The model achieved 78.0% accuracy for detecting cam deformity, 87.2% for ischial spine sign, 76.6% for dysplasia, and 71.6% for all abnormalities combined. The model achieved an Area under the Receiver Operating Curve of 0.89 for ischial spine sign, 0.80 for cam deformity, 0.80 for dysplasia, and 0.81 for all abnormalities combined. Inter-rater agreement among surgeons, assessed using Gwet’s AC1, was substantial for dysplasia (0.83) and all abnormalities (0.88), and moderate for ischial spine sign (0.75) and cam deformity (0.61).

Purpose To use the All of Us database to investigate barriers to health care access for patients with meniscus tears and to examine how specific demographic, socioeconomic, and health‐related factors independently influence their health care utilization. Methods The National Institutes of Health All of Us database was queried for patient data between March 2017 and March 2023 to form a cohort of patients with meniscal tears. Patients with meniscal tears were identified using Systematized Nomenclature of Medicine clinical terms. All patients with self‐reported meniscus tears were included, with no exclusion criteria to ensure a diverse representation of underrepresented individuals. Patient responses to the “Healthcare Access and Utilization Survey” were analyzed across 4 domains: “delayed care,” “could not afford care,” “skipped medication,” and “have not seen a provider in over one year.” Results In total, 5,671 survey respondents with meniscal tears were included for analysis from a population of 436,000 eligible records. Among them, 27.7% reported delayed care, 23.9% were unable to afford care, 11.8% skipped medication, and 2.0% had not seen a provider in over a year. Patients with annual incomes under $50,000 were more likely to delay care (odds ratio [OR], 1.41; P < .001), be unable to afford care (OR, 1.73; P < .001), or skip medications (OR, 1.79; P < .001). Younger age than the cohort mean of 65.4 years, female sex, and poor physical and mental health were associated with impaired access in at least 1 care domain. Conclusions Over one‐fourth of patients with a diagnosis of meniscus tear who responded to the All of Us “Healthcare Access and Utilization Survey” reported difficulties with access to care across 4 domains, with those of low income, younger age, female sex, and poor mental or physical health experiencing significant barriers to care. Clinical Relevance This research can inform strategies for equitable treatment of meniscal injuries by highlighting disparities in orthopaedic care access and utilization.

BACKGROUND Previous epidemiologic studies of autoimmune diseases in the US have included a limited number of diseases or used metaanalyses that rely on different data collection methods and analyses for each disease. METHODS To estimate the prevalence of autoimmune diseases in the US, we used electronic health record data from 6 large medical systems in the US. We developed a software program using common methodology to compute the estimated prevalence of autoimmune diseases alone and in aggregate that can be readily used by other investigators to replicate or modify the analysis over time. RESULTS Our findings indicate that over 15 million people, or 4.6% of the US population, have been diagnosed with at least 1 autoimmune disease from January 1, 2011, to June 1, 2022, and 34% of those are diagnosed with more than 1 autoimmune disease. As expected, females (63% of those with autoimmune disease) were almost twice as likely as males to be diagnosed with an autoimmune disease. We identified the top 20 autoimmune diseases based on prevalence and according to sex and age. CONCLUSION Here, we provide, for what we believe to be the first time, a large-scale prevalence estimate of autoimmune disease in the US by sex and age. FUNDING Autoimmune Registry Inc., the National Heart Lung and Blood Institute, the National Center for Advancing Translational Sciences, the Intramural Research Program of the National Institute of Environmental Health Sciences.