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Oxidative Stress Markers and Prediction of Severity With a Machine Learning Approach in Hospitalized Patients With COVID-19 and Severe Lung Disease: Observational, Retrospective, Single-Center Feasibility Study

Oxidative Stress Markers and Prediction of Severity With a Machine Learning Approach in Hospitalized Patients With COVID-19 and Severe Lung Disease: Observational, Retrospective, Single-Center Feasibility Study

Furthermore, many respiratory viral infections, including COVID-19, cause death of the infected cells, activation of the innate immune response, and secretion of inflammatory cytokines. All these processes are associated with the development of OS, which makes an important contribution to the pathogenesis of viral infections.

Olivier Raspado, Michel Brack, Olivier Brack, Mélanie Vivancos, Aurélie Esparcieux, Emmanuelle Cart-Tanneur, Abdellah Aouifi

JMIR Form Res 2025;9:e66509

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Effect of Continuous Positive Airway Pressure or Positional Therapy Compared to Control for Treatment of Obstructive Sleep Apnea on the Development of Gestational Diabetes Mellitus in Pregnancy: Protocol for Feasibility Randomized Controlled Trial

Effect of Continuous Positive Airway Pressure or Positional Therapy Compared to Control for Treatment of Obstructive Sleep Apnea on the Development of Gestational Diabetes Mellitus in Pregnancy: Protocol for Feasibility Randomized Controlled Trial

Participant consent forms, printed results, and other identifying information on hard copy will be stored in a locked cabinet in a security-access area of the Respiratory and Sleep Medicine Research Department at Liverpool or Campbelltown Hospitals. Where possible, study data will be stored separately to participant identifiers.

Frances Clements, Hima Vedam, Yewon Chung, John Smoleniec, Colin Sullivan, Renuka Shanmugalingam, Annemarie Hennessy, Angela Makris

JMIR Res Protoc 2025;14:e51434

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Estimation of Static Lung Volumes and Capacities From Spirometry Using Machine Learning: Algorithm Development and Validation

Estimation of Static Lung Volumes and Capacities From Spirometry Using Machine Learning: Algorithm Development and Validation

PFTs are critical for the diagnosis and prognostication of respiratory disorders, and provide a noninvasive method for measuring and monitoring the degree of respiratory impairment [2]. They are recommended for the initial evaluation of patients with chronic dyspnea and other respiratory symptoms, as well as for individuals at risk of respiratory complications due to transplant or surgery [3,4].

Scott A Helgeson, Zachary S Quicksall, Patrick W Johnson, Kaiser G Lim, Rickey E Carter, Augustine S Lee

JMIR AI 2025;4:e65456

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