Machine learning classifier is associated with mortality in interstitial lung disease: a retrospective validation study leveraging registry data.

Background: Mortality prediction in interstitial lung disease (ILD) poses a significant challenge to clinicians due to heterogeneity across disease subtypes. Currently, forced vital capacity (FVC) and Gender, Age, and Physiology (GAP) score are the two most utilized metrics in prognostication. Recently, a machine learning classifier system, Fibresolve, designed to identify a variety of computed tomography (CT) patterns associated with idiopathic pulmonary fibrosis (IPF), was demonstrated to have a significant association with mortality across multiple subtypes of ILD.

Prevalence, Risk Factors, and Interventions of Postpartum Depression in Refugees and Asylum-Seeking Women: A Systematic Review and Meta-Analysis.

Introduction: Refugee women are at an increased risk of developing postpartum depression (PPD) due to a combination of various psychosocial stressors. This systematic review aimed to outline the prevalence of PPD among refugee women and explore related risk factors and interventions currently in practice.

Methods: A search was conducted using MEDLINE, Embase, PsycINFO, CINAHL, and Core Collection (Web of Science) for articles published until August 2022, yielding 1,678 records.

Risk Factors for Hospital Readmission in Patients With Interstitial Lung Disease.

Background: Little is known about the rates, causes, or risk factors for hospital readmission among patients with interstitial lung disease (ILD). We investigated the prevalence, features, and comorbidities of subjects hospitalized with ILD and their subsequent re-hospitalizations in this retrospective study.

Methods: A retrospective analysis of subjects enrolled in the University of Chicago ILD Natural History registry was conducted.

Virtual reality headsets for perimetry testing: a systematic review.

Standard automated perimetery is considered the gold standard for evaluating a patient's visual field. However, it is costly and requires a fixed testing environment. In response, perimetric devices using virtual reality (VR) headsets have emerged as an alternative way to measure visual fields in patients.