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ImportanceUnderstanding the global barriers to otolaryngology–head and neck surgery (OHNS) care is crucial in addressing disparities in access to care, particularly in low-income and middle-income countries (LMICs).ObjectiveTo characterize barriers to comprehensive otolaryngology care across World Bank income groups.Design, Setting, and ParticipantsUsing an online cross-sectional survey that was administered by the Global OHNS Initiative via international and national professional societies, personal contacts, and social media, this study captured the perceptions of otolaryngologists regarding barriers to OHNS care at the levels of the country, health sector, clinician, and patient. Participants included otolaryngologists from the 194 World Health Organization member states and Taiwan. Eligibility criteria included a medical degree and specialized training in managing conditions of the ear, nose, and throat. The nonresponse rate was not recorded. The data collection period spanned from October 2022 to June 2023.ExposuresExposures included World Bank income group classification.Main Outcomes and MeasuresThe primary outcomes were Likert scale responses regarding frequency of barriers to OHNS care. The a priori hypothesis was that LMICs would report more frequent barriers to OHNS care.ResultsThe study involved 146 otolaryngologists (47 female individuals [32%]), with 69 (47%) from high-income countries and 77 (53%) from LMICs. Male individuals represented 45 high-income country respondents (65%) and 54 LMIC respondents (70%). Barriers were reported across income groups at all levels of the health system, with a higher frequency in LMICs. Several barriers were reported to be more substantial in LMICs, such as the national volume and distribution of otolaryngologists, financial compensation for clinicians, and patient stigma, and others were common across income settings, such as the availability of operating rooms and inflexible working hours. Common concerns included national and health sector barriers: OHNS workforce, referral networks, government support; clinician barriers: excessive clinician workloads, understaffing, poor administration support; patient barriers: distance to health care facilities, financial burdens such as medical costs and foregone wages, stigma, and health literacy.Conclusions and RelevanceThe results of this cross-sectional study suggest that there are barriers to otolaryngology care globally that affected all levels of the health care system. This work may inform prioritization of otolaryngology within research and policy, and it emphasizes the need for effective strategies to expand access to otolaryngology care, particularly in lower-income settings.

Background: Anatomically accurate illustrations are imperative in medical education, serving as crucial tools to facilitate comprehension of complex anatomical structures. While traditional illustration methods involving human artists remain the gold standard, the rapid advancement of Generative Artificial Intelligence (GAI) models presents a new opportunity to automate and accelerate this process. This study evaluated the potential of GAI models to produce craniofacial anatomy illustrations for educational purposes. Methods: Four GAI models, including Midjourney v6.0, DALL-E 3, Gemini Ultra 1.0, and Stable Diffusion 2.0 were used to generate 736 images across multiple views of surface anatomy, bones, muscles, blood vessels, and nerves of the cranium in both oil painting and realistic photograph styles. Four reviewers evaluated the images for anatomical detail, aesthetic quality, usability, and cost-effectiveness. Inter-rater reliability analysis assessed evaluation consistency. Results: Midjourney v6.0 scored highest for aesthetic quality and cost-effectiveness, and DALL-E 3 performed best for anatomical detail and usability. The inter-rater reliability analysis demonstrated a high level of agreement among reviewers (ICC = 0.858, 95% CI). However, all models showed significant flaws in depicting crucial anatomical details such as foramina, suture lines, muscular origins/insertions, and neurovascular structures. These limitations were further characterized by abstract depictions, mixing of layers, shadowing, abnormal muscle arrangements, and labeling errors. Conclusions: These findings highlight GAI’s potential for rapidly creating craniofacial anatomy illustrations but also its current limitations due to inadequate training data and incomplete understanding of complex anatomy. Refining these models through precise training data and expert feedback is vital. Ethical considerations, such as potential biases, copyright challenges, and the risks of propagating inaccurate information, must also be carefully navigated. Further refinement of GAI models and ethical safeguards are essential for safe use.

We describe the design and results from the BraTS 2023 Intracranial Meningioma Segmentation Challenge. The BraTS Meningioma Challenge differed from prior BraTS Glioma challenges in that it focused on meningiomas, which are typically benign extra-axial tumors with diverse radiologic and anatomical presentation and a propensity for multiplicity. Nine participating teams each developed deep-learning automated segmentation models using image data from the largest multi-institutional systematically expert annotated multilabel multi-sequence meningioma MRI dataset to date, which included 1000 training set cases, 141 validation set cases, and 283 hidden test set cases. Each case included T2, FLAIR, T1, and T1Gd brain MRI sequences with associated tumor compartment labels delineating enhancing tumor, non-enhancing tumor, and surrounding non-enhancing FLAIR hyperintensity. Participant automated segmentation models were evaluated and ranked based on a scoring system evaluating lesion-wise metrics including dice similarity coefficient (DSC) and 95% Hausdorff Distance. The top ranked team had a lesion-wise median dice similarity coefficient (DSC) of 0.976, 0.976, and 0.964 for enhancing tumor, tumor core, and whole tumor, respectively and a corresponding average DSC of 0.899, 0.904, and 0.871, respectively. These results serve as state-of-the-art benchmarks for future pre-operative meningioma automated segmentation algorithms. Additionally, we found that 1286 of 1424 cases (90.3%) had at least 1 compartment voxel abutting the edge of the skull-stripped image edge, which requires further investigation into optimal pre-processing face anonymization steps.

Cardiovascular disease (CVD) is the leading cause of mortality and morbidity worldwide. Low-dose colchicine is a novel and nonstandard management approach for patients with CVDs who are at an increased risk of adverse events. However, few studies have reported the risk of stroke with colchicine, with controversial results. This meta-analysis aimed to compare the efficacy of colchicine and placebo for stroke prevention in patients with CVD. Major electronic databases were screened for randomized controlled trials (RCTs) comparing colchicine and placebo in patients with CVDs from inception to June 2024. Pooled estimates were calculated as risk ratios (RRs) with 95% confidence intervals (CIs) using an inverse-variance random-effects model. Statistical significance was set at P < 0.05. A total of 15 RCTs encompassing 25,116 patients with CVDs were included (12,568: colchicine and 12,548: placebo). The pooled analysis demonstrated a significant reduction in stroke [RR, 0.80 (95% CI, 0.64–0.99); P = 0.04] with colchicine compared with placebo. The risk of all-cause mortality [RR, 1.00 (95% CI, 0.77–1.28)] was comparable between the 2 groups. On subgroup analysis, low-dose colchicine (0.5 mg/day) demonstrated a significantly lower risk of stroke compared with high-dose (>0.5 mg/day) colchicine, which failed to achieve statistical significance. Based on this meta-analysis, colchicine significantly reduced stroke in patients with CVDs compared with placebo. This effect was most significant with low-dose colchicine at 0.5 mg/day. However, no differences were observed in all-cause mortality. Further long-term RCTs are warranted to investigate stroke prevention using colchicine in this population.

ABSTRACTImportanceHighlighting the global disparities in otolaryngology training and, ultimately, service delivery, emphasizing the need for equitable access to training resources and programs.ObjectiveTo describe the relationship between the quality, content, and location of otolaryngology–head and neck surgery training and education and the resulting impact on the delivery of otolaryngology care globally.DesignAn online cross‐sectional survey to otolaryngologists, gathering information on their training and education experiences, and factors influencing their choice of training location and practice.SettingThe online survey was available in multiple languages, distributed via national and international professional otolaryngology societies, snowballing and social media.ParticipantsThe respondents were practicing otolaryngologists representing all seven World Health Organization regions.ExposuresWorld Bank income groups classification.Main Outcomes and MeasuresOur expected outcome was that subspecialty training and access to educational resources were significantly readily available to respondents from high‐income countries, leading to more confidence in performing complex procedures post training.ResultsA total of 91 participants were included in the analysis, with 47 (52%) practicing in high‐income countries and 44 (48%) in low‐ and middle‐income countries. Sixty‐one participants (67%) were male. Subspecialty training and access to educational resources were significantly less available in low‐ and middle‐income countries, leading to lower confidence among low‐ and middle‐income countries physicians in performing complex procedures. High‐income country respondents reported better access to diverse training resources and felt more prepared for a broader range of procedures.Conclusion and RelevanceSignificant disparities exist in OHNS training resources and subspecialty training opportunities between high‐ and low‐middle‐income countries. There is a critical need to integrate complementary training and educational modalities into local systems. Addressing the shortage of educational resources and promoting open‐access initiatives in low‐middle‐income countries are essential steps toward enhancing surgical education and improving global otolaryngology healthcare outcomes.

ABSTRACT Objective Availability of surgical equipment and access to essential clinical services remains an important barrier to surgical care delivery, particularly in low‐ and middle‐income countries (LMICs). This study aims to characterize the relative availability of essential equipment for otolaryngology‐head and neck surgery (OHNS) care across World Bank income groups. Methods We conducted a cross‐sectional survey on otolaryngologists' perceptions on the availability of surgical equipment and ancillary services in their respective practice settings per a 5‐point Likert scale ranging from never to always available. The study was disseminated online via professional societies, personal contacts, and social media. Eligible participants included otolaryngologists from 194 WHO‐recognized countries, which were grouped by World Bank income group classification and WHO region. Results The study involved 146 otolaryngologists, 69 (47%) from high‐income countries (HICs), and 77 (53%) from LMICs. LMIC respondents were predominantly from the African and South‐East Asian regions, which comprised 48% and 7.8% of all LMIC respondents, respectively. Results revealed significant differences in the availability of otologic, rhinologic, and endoscopic airway equipment between HICs and LMICs. Differences existed among commonly used equipment such as tympanomastoidectomy equipment and rigid bronchoscopy, to subspecialized equipment such as functional endoscopic sinus surgery equipment and cochlear implants ( p < 0.05 each). Conclusions The study highlighted key disparities in the availability of essential equipment for baseline OHNS care, especially for pediatric airway and otologic conditions. These results can be used to guide investment and advocacy efforts to improve specialty‐specific surgical infrastructure relative to the global burden of OHNS diseases in low‐resource settings. Level of Evidence 3

Artificial intelligence (AI) is not merely a tool for the future of clinical medicine; it is already reshaping the landscape, challenging traditional paradigms, and expanding the horizons of what is achievable in healthcare [...]