Background: Accurate identification of patients with cirrhosis using noninvasive markers of fibrosis is useful for esophageal varices and hepatocellular carcinoma surveillance programs. The aims of our study were to characterize the accuracy of ultrasonography, AST-to-platelet ratio index (APRI), and FIB-4 as noninvasive markers to identify the presence of cirrhosis.
Methods: We conducted a retrospective cohort study of patients who underwent liver biopsy at a large urban safety-net institution between November 2008 and July 2011. The sensitivity, specificity, positive predictive value (PPV), negative predictive value, and overall accuracy using receiver operator characteristic curve analysis for the detection of cirrhosis were calculated for each noninvasive marker.
Results: Liver biopsy was performed in 388 patients, of whom 93 (24.0 %) had cirrhosis. C-statistics for APRI and FIB-4 predicting the presence of cirrhosis were 0.68 (95 % CI 0.63-0.74) and 0.73 (95 % CI 0.68-0.78), respectively. The c-statistic for a nodular appearance on ultrasound was 0.78 (95 % CI 0.72-0.83). The PPV of a shrunken nodular-appearing liver was 64.8 %; however, PPV was significantly higher in the subset with a cirrhotic-appearing liver and signs of portal hypertension (PPV 83.6 %, p = 0.01) as well as in the subset with a noninvasive fibrosis marker also suggesting cirrhosis (PPV 77.8 %, p < 0.001).
Conclusion: Serum and imaging noninvasive markers of fibrosis may have insufficient accuracy when used in isolation; however, a combination of markers may allow sufficient accuracy to systematically identify patients with cirrhosis.
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http://dx.doi.org/10.1007/s10620-015-3531-1 | DOI Listing |
Front Neurosci
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Neurology Associate P.C., Lincoln, NE, United States.
Introduction: As a hallmark feature of amyotrophic lateral sclerosis (ALS), bulbar involvement significantly impacts psychosocial, emotional, and physical health. A validated objective marker is however lacking to characterize and phenotype bulbar involvement, positing a major barrier to early detection, progress monitoring, and tailored care. This study aimed to bridge this gap by constructing a multiplex functional mandibular muscle network to provide a novel objective measurement tool of bulbar involvement.
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Chronic Disease and Health Management Research Center, Geriatric Hospital of Nanjing Medical University, Nanjing 210024, Jiangsu Province, China.
Metabolic dysfunction-associated steatotic liver disease (MASLD), particularly in patients with type 2 diabetes mellitus (T2DM), is increasingly recognized as a multi-system disease that affects both hepatic and cardiovascular health. This study explores the association between MASLD-related liver fibrosis and cardiac dysfunction, focusing on how liver fibrosis contributes to cardiac remodeling and dysfunction. Cernea 's research highlights the strong correlation between liver fibrosis and changes in left ventricular mass, left atrial dimensions, and systolic and diastolic function in diabetic patients.
View Article and Find Full Text PDFBioelectromagnetics
January 2025
Micropropulsion and Nanotechnology Laboratory, School of Engineering and Applied Science, George Washington University, Washington, DC, USA.
Cancer remains a formidable global health challenge, necessitating the development of innovative diagnostic techniques capable of early detection and differentiation of tumor/cancerous cells from their healthy counterparts. This review focuses on the confluence of advanced computational algorithms with noninvasive, label-free impedance-based biophysical methodologies-techniques that assess biological processes directly without the need for external markers or dyes. This review elucidates a diverse array of state-of-the-art impedance-based technologies, illuminating distinct electrical signatures inherent to cancer vs healthy tissues.
View Article and Find Full Text PDFSci Rep
January 2025
Department of Electrical Electronical Engineering, Yaşar University, Bornova, İzmir, Turkey.
We aimed to build a robust classifier for the MGMT methylation status of glioblastoma in multiparametric MRI. We focused on multi-habitat deep image descriptors as our basic focus. A subset of the BRATS 2021 MGMT methylation dataset containing both MGMT class labels and segmentation masks was used.
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