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1. Evaluation of Artificial Intelligence Algorithms for Diabetic Retinopathy Detection: Protocol for a Systematic Review and Meta-Analysis.

Author

Sesgundo Iii JA, Maeng DC, Tukay JA, Ascano MP, Suba-Cohen J, and Sampang V

Subjects
Humans, Algorithms, Diabetic Retinopathy diagnosis, Systematic Reviews as Topic, Meta-Analysis as Topic, Artificial Intelligence
Abstract

Background: Diabetic retinopathy (DR) is one of the most common complications of diabetes mellitus. The global burden is immense with a worldwide prevalence of 8.5%. Recent advancements in artificial intelligence (AI) have demonstrated the potential to transform the landscape of ophthalmology with earlier detection and management of DR., Objective: This study seeks to provide an update and evaluate the accuracy and current diagnostic ability of AI in detecting DR versus ophthalmologists. Additionally, this review will highlight the potential of AI integration to enhance DR screening, management, and disease progression., Methods: A systematic review of the current landscape of AI's role in DR will be undertaken, guided by the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analysis) model. Relevant peer-reviewed papers published in English will be identified by searching 4 international databases: PubMed, Embase, CINAHL, and the Cochrane Central Register of Controlled Trials. Eligible studies will include randomized controlled trials, observational studies, and cohort studies published on or after 2022 that evaluate AI's performance in retinal imaging detection of DR in diverse adult populations. Studies that focus on specific comorbid conditions, nonimage-based applications of AI, or those lacking a direct comparison group or clear methodology will be excluded. Selected papers will be independently assessed for bias by 2 review authors (JS and DM) using the Quality Assessment of Diagnostic Accuracy Studies tool for systematic reviews. Upon systematic review completion, if it is determined that there are sufficient data, a meta-analysis will be performed. Data synthesis will use a quantitative model. Statistical software such as RevMan and STATA will be used to produce a random-effects meta-regression model to pool data from selected studies., Results: Using selected search queries across multiple databases, we accumulated 3494 studies regarding our topic of interest, of which 1588 were duplicates, leaving 1906 unique research papers to review and analyze., Conclusions: This systematic review and meta-analysis protocol outlines a comprehensive evaluation of AI for DR detection. This active study is anticipated to assess the current accuracy of AI methods in detecting DR., International Registered Report Identifier (irrid): DERR1-10.2196/57292., (©Jaime Angeles Sesgundo III, David Collin Maeng, Jumelle Aubrey Tukay, Maria Patricia Ascano, Justine Suba-Cohen, Virginia Sampang. Originally published in JMIR Research Protocols (https://www.researchprotocols.org), 27.05.2024.)

Published
2024
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2. Differentiating Giant Bullous Emphysema From Tension Pneumothorax: A Case Report.

Author

Ascano MP, Kramer N, and Le K

Abstract

Giant bullous emphysema (GBE) is a progressive disease that commonly presents with severe progressive dyspnea attributed to the progressive destruction of alveolar walls and the formation of large air pockets, resulting in impaired gas exchange. This presentation is most commonly seen in young, thin male smokers. GBE poses an interesting and unique clinical challenge due to its radiologic findings, which can be easily mistaken for tension pneumothorax. Despite the decreased acuity of GBE as compared to tension pneumothorax, inadequate treatment in a severe case can lead to spontaneous pneumothorax, infection, and/or respiratory failure. In this report, we highlight a case of severe GBE that presents similarly to tension pneumothorax in both symptomatology and radiologic findings. The case at hand is of a 50-year-old male patient with a history of chronic obstructive pulmonary disease (COPD) with complaints of dyspnea and subsequent findings of tachycardia, tachypnea, and hypoxemia with significantly decreased breath sounds in the right lung. Radiologic findings showed increased lucency of the right hemithorax and a mass effect with a mediastinal shift to the left. History and further imaging with CT led to an ultimate diagnosis of severe GBE and COPD exacerbations. The patient was treated with non-invasive medical management. With the challenges of overlapping presentations, landing on the correct diagnosis is imperative to accurately and adequately treat the patient since GBE and tension pneumothorax significantly differ in acuity and overall management, hence the need for a high level of suspicion based on the clinical picture and the use of high-resolution CT., Competing Interests: The authors have declared that no competing interests exist., (Copyright © 2024, Ascano et al.)

Published
2024
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