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Background: During the coronavirus disease 2019 (COVID-19) pandemic, healthcare facilities developed surveillance systems to identify patients suspected of having COVID-19 to segregate them during their hospital stay. As a part of this infection control strategy, the Ministry of Health in the Kingdom of Saudi Arabia developed a visual triage (VT) checklist for early screening and isolation of patients in the hospital. The aim of this study was to evaluate the diagnostic accuracy of this visual triage checklist in identifying children with COVID-19.
Methods: This was a retrospective, single center study that included all children who were tested for COVID-19 and were admitted to the hospital through the pediatric emergency department. The diagnostic accuracy of the visual triage checklist was assessed using COVID-19 PCR as the gold standard.
Results: A total of 1333 patients were included. The visual triage checklist had a sensitivity of 94.3% (95% CI: 87.2-98.1) and a specificity of 16.0% (95% CI: 14-18) with an area under the receiver operating characteristic curve of 0.55 (0.53-0.58). The positive predictive value of the checklist was low at 7.35% (95% CI: 5.9-9.0).
Conclusion: The VT checklist has high sensitivity, and is therefore potentially useful as an initial screening tool. However, the diagnosis of COVID-19 requires early secondary confirmation to avoid the large number of false positive cases associated with this tool.
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http://dx.doi.org/10.1186/s12887-025-05693-7 | DOI Listing |
PLoS One
September 2025
Department of Obstetrics and Gynecology, Beth Israel Deaconess Medical Center, Boston, Massachusetts, United States of America.
Cervical cancer remains the leading cause of cancer death among women in sub-Saharan Africa and is more severe in high HIV-burdened countries due to persistent high-risk human papillomavirus (hrHPV). In 2021, the World Health Organization recommended primary hrHPV testing for cervical cancer screening; however, optimal triage strategies following positive hrHPV tests remain unclear. We conducted a prospective cost analysis of triage methods for positive hrHPV results among women living with and without HIV in Gaborone, Botswana.
View Article and Find Full Text PDFAnalyst
September 2025
Laboratory of New Drug Research and Clinical Pharmacy, School of Pharmacy, Xuzhou Medical University, Xuzhou, 221004, China.
Mustard agents, including sulphur mustard (SM) and nitrogen mustard (NM), are chemical warfare agents that can cause blistering of the skin and mucous membranes upon contact. Although SM and NM both have dermal effects, their medical management of systemic poisoning differs significantly. A rapid and simple method for detecting and discriminating between SM and NM would be greatly valuable.
View Article and Find Full Text PDFSci Rep
August 2025
Department of Medical Oncology, Lund University, 221 00, Lund, Sweden.
Pregnant women have historically and are currently being excluded from cervical cancer screening in most low and middle-income countries (LMICs). The aim of this study was to assess the feasibility and outcomes of including pregnant women in a HPV self-sampling-based screening program in Ethiopia. Pregnant women, recruited from a previously established cohort, were included.
View Article and Find Full Text PDFActa Radiol
August 2025
Centre for Medical Image Science and Visualization (CMIV), Linköping University, Linköping Sweden.
BackgroundArtificial intelligence (AI)-based systems have the potential to increase the efficiency and effectiveness of breast cancer screening programs but need to be carefully validated before clinical implementation.PurposeTo retrospectively evaluate an AI system to safely reduce the workload of a double-reading breast cancer screening program.Material and MethodsAll digital mammography (DM) screening examinations of women aged 40-74 years between August 2021 and January 2022 in Östergötland, Sweden were included.
View Article and Find Full Text PDFIEEE Trans Vis Comput Graph
August 2025
At the beginning of the COVID-19 pandemic, HealthLink BC (HLBC) rapidly integrated physicians into the triage process of their virtual healthcare service to improve patient outcomes and satisfaction with this service and preserve health care system capacity. We present the design and implementation of a visual analytics tool, VIVA (Virtual healthcare Interactions using Visual Analytics), to support HLBC in analysing various forms of usage data from the service. We abstract HLBC's data and data analysis tasks, which we use to inform our design of VIVA.
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