Search

Purpose: COVID-19 immunizations are novel and there is widespread public concern for the lack of data on their potential adverse effects. Cases of Bell's palsy following COVID-19 vaccination were reported disproportionately in the vaccine group during phase 3 clinical trials and have now been reported multiple times post-licensure. The U.S. Food and Drug Administration has stated the frequency of Bell's palsy in the vaccine group is consistent with the expected background rate of Bell's palsy in the population but recommends “surveillance for cases of Bell's palsy with deployment of the vaccine into larger populations.“1 Here we present a case of Bell's palsy following Pfizer/BioNTech BNT162b2 COVID-19 vaccine administration in an HIV+ patient as a potential adverse event following immunization. Observations: A 60-year-old male with HIV presented to the emergency department for evaluation of left facial droop. He had received the first dose of Pfizer/BioNTech BNT162b2 vaccination approximately 42 hours prior to symptom onset. Physical examination in the ED revealed left-sided facial weakness with involvement of the forehead, inability to raise left eyebrow, and inability to close left eye with sensation and strength intact in bilateral upper and lower extremities. Physical examination in our outpatient ophthalmology clinic on day 2 following symptom onset was revealing for mild exposure keratopathy, 5 mm lagophthalmos and very poor Bell's reflex in the left eye with otherwise normal exam findings. These findings were judged to be consistent with uncomplicated Bell's palsy. He was provided ophthalmic lubricating ointment to use hourly, artificial tears as needed, moisture goggles and suggested to tape eyelids nightly in addition to standard systemic glucocorticoid and antiviral therapy. The patient's facial weakness and exposure keratopathy were completely resolved at approximately 90 days following symptom onset. Conclusions: Though there is insufficient evidence at this time to support any causal association between COVID-19 vaccines and Bell's palsy, the temporal relationship between vaccination and classic clinical features of Bell's palsy in our patient certainly raises suspicion for association with Pfizer/BioNTech BNT162b2 COVID-19 vaccination. It will be important to monitor for cases of Bell's palsy following COVID-19 immunization as an increasing percentage of the global population receives vaccination.

Background: Social media posts by clinicians are not bound by the same rules as peer-reviewed publications, raising ethical concerns that have not been extensively characterized or quantified., Objective: We aim to develop a scale to assess ethical issues on medical social media (SoMe) and use it to determine the prevalence of these issues among posts with 3 different hashtags: #MedTwitter, #IRad, and #CardioTwitter., Methods: A scale was developed based on previous descriptions of professionalism and validated via semistructured cognitive interviewing with a sample of 11 clinicians and trainees, interrater agreement, and correlation of 100 posts. The final scale assessed social media posts in 6 domains. This was used to analyze 1500 Twitter posts, 500 each from the 3 hashtags. Analysis of posts was limited to original Twitter posts in English made by health care professionals in North America. The prevalence of potential issues was determined using descriptive statistics and compared across hashtags using the Fisher exact and χ 2 tests with Yates correction., Results: The final scale was considered reflective of potential ethical issues of SoMe by participants. There was good interrater agreement (Cohen κ=0.620, P<.01) and moderate to strong positive interrater correlation (=0.602, P<.001). The 6 scale domains showed minimal to no interrelation (Cronbach α=0.206). Ethical concerns across all hashtags had a prevalence of 1.5% or less except the conflict of interest concerns on #IRad, which had a prevalence of 3.6% (n=18). Compared to #MedTwitter, posts with specialty-specific hashtags had more patient privacy and conflict of interest concerns., Conclusions: The SoMe professionalism scale we developed reliably reflects potential ethical issues. Ethical issues on SoMe are rare but important and vary in prevalence across medical communities., (©Vongai Christine Mlambo, Eric Keller, Caroline Mussatto, Gloria Hwang. Originally published in JMIR Infodemiology (https://infodemiology.jmir.org), 27.03.2024.)

Objective: To localize structural laryngeal lesions within digital flexible laryngoscopic images and to classify them as benign or suspicious for malignancy using state-of-the-art computer vision detection models., Study Design: Cross-sectional diagnostic study SETTING: Tertiary care voice clinic METHODS: Digital stroboscopic videos, demographic and clinical data were collected from patients evaluated for a structural laryngeal lesion. Laryngoscopic images were extracted from videos and manually labeled with bounding boxes encompassing the lesion. Four detection models were employed to simultaneously localize and classify structural laryngeal lesions in laryngoscopic images. Classification accuracy, intersection over union (IoU) and mean average precision (mAP) were evaluated as measures of classification, localization, and overall performance, respectively., Results: In total, 8,172 images from 147 patients were included in the laryngeal image dataset. Classification accuracy was 88.5 for individual laryngeal images and increased to 92.0 when all images belonging to the same sequence (video) were considered. Mean average precision across all four detection models was 50.1 using an IoU threshold of 0.5 to determine successful localization., Conclusion: Results of this study showed that deep neural network-based detection models trained using a labeled dataset of digital laryngeal images have the potential to classify structural laryngeal lesions as benign or suspicious for malignancy and to localize them within an image. This approach provides valuable insight into which part of the image was used by the model to determine a diagnosis, allowing clinicians to independently evaluate models' predictions., (© 2023 American Academy of Otolaryngology-Head and Neck Surgery Foundation.)

Use of artificial intelligence (AI) is a burgeoning field in otolaryngology and the communication sciences. A virtual symposium on the topic was convened from Duke University on October 26, 2020, and was attended by more than 170 participants worldwide. This review presents summaries of all but one of the talks presented during the symposium; recordings of all the talks, along with the discussions for the talks, are available at https://www.youtube.com/watch?v=ktfewrXvEFg and https://www.youtube.com/watch?v=-gQ5qX2v3rg . Each of the summaries is about 2500 words in length and each summary includes two figures. This level of detail far exceeds the brief summaries presented in traditional reviews and thus provides a more-informed glimpse into the power and diversity of current AI applications in otolaryngology and the communication sciences and how to harness that power for future applications., (© 2022. The Author(s) under exclusive licence to Association for Research in Otolaryngology.)