Background: Baveno-VI guidelines recommend that patients with compensated cirrhosis with liver stiffness by transient elastography (LSM-TE) <20 kPa and platelets >150,000/mm(3) do not need an esophagogastroduodenoscopy (EGD) to screen for varices, since the risk of having varices needing treatment (VNT) is <5%. It remains uncertain if this tool can be used in patients with cholestatic liver diseases (ChLDs): primary biliary cholangitis (PBC) and primary sclerosing cholangitis (PSC). These patients may have a pre-sinusoidal component of portal hypertension that could affect the performance of this rule. In this study we evaluated the performance of Baveno-VI, expanded Baveno-VI (LSM-TE <25 kPa and platelets >110,000/mm(3)), and other criteria in predicting the absence of VNT.
Methods: This was a multicenter cross-sectional study in four referral hospitals. We retrospectively analyzed data from 227 patients with compensated advanced chronic liver disease (cACLD) due to PBC (n = 147) and PSC (n = 80) that had paired EGD and LSM-TE. We calculated false negative rate (FNR) and number of saved endoscopies for each prediction rule.
Results: Prevalence of VNT was 13%. Baveno-VI criteria had a 0% FNR in PBC and PSC, saving 39 and 30% of EGDs, respectively. In PBC the other LSM-TE-based criteria resulted in FNRs >5%. In PSC the expanded Baveno criteria had an adequate performance. In both conditions LSM-TE-independent criteria resulted in an acceptable FNR but saved less EGDs.
Conclusions: Baveno-VI criteria can be applied in patients with cACLD due to ChLDs, which would result in saving 30-40% of EGDs. Expanded criteria in PBC would lead to FNRs >5%.
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http://dx.doi.org/10.1038/s41395-018-0265-7 | DOI Listing |
BMJ Oncol
August 2024
Cyrus Tang Medical Institute, State Key Laboratory of Radiation Medicine and Prevention, Collaborative Innovation Center of Hematology, Soochow University, Suzhou, Jiangsu, China.
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Alzheimer's disease is a disabling neurodegenerative disorder for which no effective treatment currently exists. To predict the diagnosis of Alzheimer's disease could be crucial for patients' outcome, but current Alzheimer's disease biomarkers are invasive, time consuming or expensive. Thus, developing MRI-based computational methods for Alzheimer's disease early diagnosis would be essential to narrow down the phenotypic measures predictive of cognitive decline.
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Regardless of the underlying etiology and success of PE, progressive liver fibrosis and eventually cirrhosis represent the dominant pathology and the end-stage of BA. Ascending bile duct injury-induced cholestasis, inflammation and ductular reaction provide profibrogenic cytokine environment leading to myofibroblast activation and rapid progression of fibrosis especially after unsuccessful portoenterostomy. Although liver fibrosis and development of cirrhosis play a crucial role in determining BA outcomes, the exact prognostic significance and dynamics of mild to moderate liver fibrosis remain unclear.
View Article and Find Full Text PDFSemin Pediatr Surg
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Dept of Paediatric Surgery, Kings College Hospital, London SE59RS, England, United Kingdom. Electronic address:
Biliary atresia (BA) remains a disease of significant morbidity and mortality world-wide. Early and accurate diagnosis facilitates early intervention and improves outcomes. The gold standard in diagnosing BA is a liver biopsy followed by cholangiography, usually performed intra-operatively.
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January 2025
Department of Mechanical and Metallurgical Engineering, School of Engineering, Pontificia Universidad Católica de Chile, Santiago, Chile; Institute for Biological and Medical Engineering, Schools of Engineering, Medicine and Biological Sciences, Pontificia Universidad Católica de Chile, Santiago, Chile; Millennium Institute for Intelligent Healthcare Engineering, iHEALTH, Chile. Electronic address:
The identification of the Purkinje conduction system in the heart is a challenging task, yet essential for a correct definition of cardiac digital twins for precision cardiology. Here, we propose a probabilistic approach for identifying the Purkinje network from non-invasive clinical data such as the standard electrocardiogram (ECG). We use cardiac imaging to build an anatomically accurate model of the ventricles; we algorithmically generate a rule-based Purkinje network tailored to the anatomy; we simulate physiological electrocardiograms with a fast model; we identify the geometrical and electrical parameters of the Purkinje-ECG model with Bayesian optimization and approximate Bayesian computation.
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