This study aimed to assess the diagnostic accuracy of the Posttraumatic Stress Disorder Checklist-Civilian Version (PCL-C; Weathers, Litz, Herman, Huska, & Keane, 1993) and to establish the most accurate cutoff for prevalence estimation of posttraumatic stress disorder (PTSD) in a representative military sample compared to a clinical interview. Danish soldiers (N = 415; 94.4% male, mean age 26.6 years) were assessed with the PCL-C and the Structured Clinical Interview for the DSM-IV (SCID; First, Spitzer, Gibbon, & Williams, 2002) 2.5 years after their return from deployment to Afghanistan. Diagnostic accuracy of the PCL-C was assessed through receiver operating characteristic curve analysis. The PCL-C displayed high overall accuracy (area under the curve = .95, confidence interval [.92, .98]) and performed well (sensitivity > .70 and specificity ≥ .90), with cutoff scores ranging from 37 to 44. When including sensitivity values a little below .70 (.69), the PCL-C performed well for cutoff levels up to 53. Prevalence of PTSD varied considerably with the application of different cutoff values and scoring methods. Our results show that the PCL-C is a relevant and valid tool for screening for probable PTSD in active military samples. However, it is of great importance that cutoff scores be chosen based on the sample and the purpose of the particular study or screening.
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http://dx.doi.org/10.1037/a0034889 | DOI Listing |
Eur Stroke J
January 2025
Department of Neurology, University Hospital RWTH Aachen, Aachen, Germany.
Introduction: Distal arterial occlusions can cause measurable changes in the flow wave profile in proximal segments of the feeding artery. Our objective was to study the diagnostic accuracy of point-of-care ultrasound (POCUS) of the common carotid arteries (CCA) for detection of anterior circulation large vessel occlusion (ac-LVO) in patients with suspected stroke.
Patients And Methods: We conducted a prospective, single-center, observational study of adult patients with suspected stroke admitted in the emergency department.
Nano Lett
January 2025
Key Laboratory of Clinical Laboratory Diagnostics (Chinese Ministry of Education), College of Laboratory Medicine, Chongqing Medical University, Chongqing 400016, P. R. China.
Logical analysis of multiple-miRNA expression information and immediate output of diagnostic results facilitates early cancer detection. In this work, we constructed an isothermal molecular classifier capable of performing computations on multiple miRNAs and directly providing diagnosis results. First, we developed linear-after-the-exponential rolling circle amplification (LATE-RCA), a nearly linear isothermal amplification that does not destroy the original quantitative information about miRNAs.
View Article and Find Full Text PDFHeliyon
January 2025
Information Technology Department, Technical College of Informatics-Akre, Akre University for Applied Sciences, Kurdistan Regain, Iraq.
Deep Learning (DL) has significantly contributed to the field of medical imaging in recent years, leading to advancements in disease diagnosis and treatment. In the case of Diabetic Retinopathy (DR), DL models have shown high efficacy in tasks such as classification, segmentation, detection, and prediction. However, DL model's opacity and complexity lead to errors in decision-making, particularly in complex cases, making it necessary to estimate the model's uncertainty in predictions.
View Article and Find Full Text PDFFront Oncol
December 2024
Gynecologic Oncology, The Third Affiliated Hospital of Zhengzhou University, Zhengzhou, Henan, China.
Background: Ovarian cancer (OC) represents a common neoplasm within the female reproductive tract. The prognosis for patients diagnosed at advanced stages is unfavorable, primarily attributable to the absence of reliable screening markers for early detection. An elevated neutrophil-to-lymphocyte ratio (NLR) serves as an indicator of host inflammatory response and has been linked to poorer overall survival (OS) across various cancer types; however, its examination in OC remains limited.
View Article and Find Full Text PDFJ Anus Rectum Colon
January 2025
Department of Gastroenterological Surgery, Graduate School of Medical Sciences, Kumamoto University, Kumamoto, Japan.
Objectives: This study explored the clinical utility of CT radiomics-driven machine learning as a predictive marker for chemotherapy response in colorectal liver metastasis (CRLM) patients.
Methods: We included 150 CRLM patients who underwent first-line doublet chemotherapy, dividing them into a training cohort (n=112) and a test cohort (n=38). We manually delineated three-dimensional tumor volumes, selecting the largest liver metastasis for measurement, using pretreatment portal-phase CT images and extracted 107 radiomics features.
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