Sociodemographic reporting in videomics research: a review of practices in otolaryngology - head and neck surgery.

OBJECTIVE: To assess reporting practices of sociodemographic data in Upper Aerodigestive Tract (UAT) videomics research in Otolaryngology-Head and Neck Surgery (OHNS). STUDY DESIGN: Narrative review. METHODS: Four online research databases were searched for peer-reviewed articles on videomics and UAT endoscopy in OHNS, published since January 1, 2017. Title and abstract search, followed by a full-text screening was performed. Dataset audit criteria were determined by the MINIMAR reporting standards for patient demographic characteristics, in addition to gender and author affiliations. RESULTS: Of the 57 studies that were included, 37% reported any sociodemographic information on their dataset. Among these studies, all reported age, most reported sex (86%), two (10%) reported race, and one (5%) reported ethnicity and socioeconomic status. No studies reported gender. Most studies (84%) included at least one female author, and more than half of the studies (53%) had female first/senior authors, with no significant differences in the rate of sociodemographic reporting in studies with and without female authors (any female author: p = 0.2664; first/senior female author: p > 0.9999). Most studies based in the US reported at least one sociodemographic variable (79%), compared to those in Europe (24%) and in Asia (20%) (p = 0.0012). The rates of sociodemographic reporting in journals of different categories were as follows: clinical OHNS: 44%, clinical non-OHNS: 40%, technical: 42%, interdisciplinary: 10%. CONCLUSIONS: There is prevalent underreporting of sociodemographic information in OHNS videomics research utilizing UAT endoscopy. Routine reporting of sociodemographic information should be implemented for AI-based research to help minimize algorithmic biases that have been previously demonstrated.

A deep learning pipeline for automated classification of vocal fold polyps in flexible laryngoscopy.

PURPOSE: To develop and validate a deep learning model for distinguishing healthy vocal folds (HVF) and vocal fold polyps (VFP) on laryngoscopy videos, while demonstrating the ability of a previously developed informative frame classifier in facilitating deep learning development. METHODS: Following retrospective extraction of image frames from 52 HVF and 77 unilateral VFP videos, two researchers manually labeled each frame as informative or uninformative. A previously developed informative frame classifier was used to extract informative frames from the same video set. Both sets of videos were independently divided into training (60%), validation (20%), and test (20%) by patient. Machine-labeled frames were independently verified by two researchers to assess the precision of the informative frame classifier. Two models, pre-trained on ResNet18, were trained to classify frames as containing HVF or VFP. The accuracy of the polyp classifier trained on machine-labeled frames was compared to that of the classifier trained on human-labeled frames. The performance was measured by accuracy and area under the receiver operating characteristic curve (AUROC). RESULTS: When evaluated on a hold-out test set, the polyp classifier trained on machine-labeled frames achieved an accuracy of 85% and AUROC of 0.84, whereas the classifier trained on human-labeled frames achieved an accuracy of 69% and AUROC of 0.66. CONCLUSION: An accurate deep learning classifier for vocal fold polyp identification was developed and validated with the assistance of a peer-reviewed informative frame classifier for dataset assembly. The classifier trained on machine-labeled frames demonstrates improved performance compared to the classifier trained on human-labeled frames.

Drivers of heterogeneity in synovial fibroblasts in rheumatoid arthritis.

Inflammation of non-barrier immunologically quiescent tissues is associated with a massive influx of blood-borne innate and adaptive immune cells. Cues from the latter are likely to alter and expand activated states of the resident cells. However, local communications between immigrant and resident cell types in human inflammatory disease remain poorly understood. Here, we explored drivers of fibroblast-like synoviocyte (FLS) heterogeneity in inflamed joints of patients with rheumatoid arthritis using paired single-cell RNA and ATAC sequencing, multiplexed imaging and spatial transcriptomics along with in vitro modeling of cell-extrinsic factor signaling. These analyses suggest that local exposures to myeloid and T cell-derived cytokines, TNF, IFN-γ, IL-1ß or lack thereof, drive four distinct FLS states some of which closely resemble fibroblast states in other disease-affected tissues including skin and colon. Our results highlight a role for concurrent, spatially distributed cytokine signaling within the inflamed synovium.

Are There Differences between the Stress Responses of Philippine Men and Women to the COVID-19 Pandemic?

The SARS-CoV-2 pandemic has had a deleterious impact on human health since its beginning in 2019. The purpose of this study was to examine the psychosocial impact of the COVID-19 pandemic in the Philippines and determine if there were differential impacts on women compared to men. A web-based survey was conducted in the Luzon Islands of the Philippines, during the pandemic quarantine. A total of 1879 participants completed online surveys between 28 March-12 April 2020. A bivariate analysis of both men and women for each psychological measure (stress, anxiety, depression, and impact of COVID-19) was conducted. Multivariable logistic regression models were built for each measure, dichotomized as high or low, separately for men and women. Younger age (p < 0.001), being married (p < 0.001), and being a parent (p < 0.004) were associated with women's poor mental health. Marriage and large household size are protective factors for men (p < 0.002 and p < 0.0012, respectively), but marriage may be a risk factor for women (p < 0.001). Overall, women were disproportionately negatively impacted by the pandemic compared to men.