Objective: The chest radiograph (CXR) is the predominant imaging investigation being used to triage patients prior to either performing a SARS-CoV-2 polymerase chain reaction (PCR) test or a diagnostic CT scan, but there are limited studies that assess the diagnostic accuracy of CXRs in COVID-19.To determine the accuracy of CXR diagnosis of COVID-19 compared with PCR in patients presenting with a clinical suspicion of COVID-19.
Methods And Materials: The CXR reports of 569 consecutive patients with a clinical suspicion of COVID-19 were reviewed, blinded to the PCR result and classified into the following categories: normal, indeterminate for COVID-19, classic/probable COVID-19, non-COVID-19 pathology, and not specified. Severity reporting and reporter expertise were documented. The subset of this cohort that had CXR and PCR within 3 days of each other were included for further analysis for diagnostic accuracy.
Results: Classic/probable COVID-19 was reported in 29% (166/569) of the initial cohort. 67% (382/569) had PCR tests. 344 patients had CXR and PCR within 3 days of each other. Compared to PCR as the reference test, initial CXR had a 61% sensitivity and 76% specificity in the diagnosis of COVID-19.
Conclusion: Initial CXR is useful as a triage tool with a sensitivity of 61% and specificity of 76% in the diagnosis of COVID-19 in a hospital setting.
Advances In Knowledge: .Diagnostic accuracy does not differ significantly between specialist thoracic radiologists and general radiologists including trainees following training.There was a 40% prevalence of PCR positive disease in the cohort of patients ( = 344) having CXR and PCR within 3 days of each other.Classic/probable COVID-19 was reported in 29% of total cohort of patients presenting with clinical suspicion of COVID-19 ( = 569).Initial CXR is useful as a triage tool with a sensitivity of 61% and specificity of 76% in the diagnosis of COVID-19 in a hospital setting.
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http://dx.doi.org/10.1259/bjro.20200034 | DOI Listing |
Appl Neuropsychol Adult
January 2025
Faculty Xavier Institute of Engineering, Mahim, India.
In the fields of engineering, science, technology, and medicine, artificial intelligence (AI) has made significant advancements. In particular, the application of AI techniques in medicine, such as machine learning (ML) and deep learning (DL), is rapidly growing and offers great potential for aiding physicians in the early diagnosis of illnesses. Depression, one of the most prevalent and debilitating mental illnesses, is projected to become the leading cause of disability worldwide by 2040.
View Article and Find Full Text PDFJ Med Internet Res
January 2025
Department of Computer Science and Software Engineering, United Arab Emirates University, Al Ain, United Arab Emirates.
Background: Neuroimaging segmentation is increasingly important for diagnosing and planning treatments for neurological diseases. Manual segmentation is time-consuming, apart from being prone to human error and variability. Transformers are a promising deep learning approach for automated medical image segmentation.
View Article and Find Full Text PDFCrit Care Sci
January 2025
Department of Neurointensive Care, Instituto Estadual do Cérebro Paulo Niemeyer - Rio de Janeiro (RJ), Brazil.
Objective: To define the incidence of ventriculostomy-associated infections and their impact on the mortality and functional outcomes of patients with aneurysmal subarachnoid hemorrhage.
Methods: We prospectively included all consecutive adult aneurysmal subarachnoid hemorrhage patients admitted to the neurological intensive care units of the Instituto Estadual do Cérebro Paulo Niemeyer (Rio de Janeiro, Brazil) and Hospital Cristo Redentor (Rio Grande do Sul, Brazil) who required external ventricular drains from July 2015 to December 2020. Daily clinical and laboratory variables were collected at admission and during the hospital stay.
Codas
January 2025
Programa de Pós-graduação em Distúrbios da Comunicação Humana, Departamento de Fonoaudiologia, Universidade Federal de Santa Maria - UFSM - Santa Maria (RS), Brasil.
Purpose: To present the criterion validity, sensitivity, specificity, and cut-off scores for the Profiles of Early Expressive Phonological Skills Test - Brazilian Portuguese (PEEPS-BP) - Expanded List.
Methods: This was a quantitative cross-sectional psychometric study. The sample consisted of 30 children with no identified neurodevelopmental disorders aged 24 to 36 months.
Arq Bras Oftalmol
January 2025
Department of Ophthalmology and Visual Sciences, Escola Paulista de Medicina, Universidade Federal de São Paulo, São Paulo, SP, Brazil.
Purpose: To assess the sensitivity and specificity of the retinopathy of prematurity score (ROPScore) and weight, insulin-like growth factor-1, retinopathy of prematurity algorithm in predicting the risk of developing severe retinopathy of prematurity (prethreshold type 1) in a sample of preterm infants in Brazil.
Methods: Retrospective analysis of medical records of preterm infants (n=288) with birth weight of ≤1500 g and/or gestational age of 23-32 weeks in a neonatal unit in Southern Brazil from May 2013 to December 2020 (92 months).
Results: The incidence of confirmed severe retinopathy of prematurity was 6.
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