Objectives: To evaluate the predictive value of advanced non-contrasted computed tomography (NCCT) post-processing using novel CT-calculometry (CT-CM) parameters compared to established predictors of success of shock wave lithotripsy (SWL) for urinary calculi.
Materials And Methods: NCCT post-processing was retrospectively performed in 312 patients suffering from upper tract urinary calculi who were treated by SWL. Established predictors such as skin to stone distance, body mass index, stone diameter or mean stone attenuation values were assessed. Precise stone size and shape metrics, 3-D greyscale measurements and homogeneity parameters such as skewness and kurtosis, were analysed using CT-CM. Predictive values for SWL outcome were analysed using logistic regression and receiver operating characteristics (ROC) statistics.
Results: Overall success rate (stone disintegration and no re-intervention needed) of SWL was 59% (184 patients). CT-CM metrics mainly outperformed established predictors. According to ROC analyses, stone volume and surface area performed better than established stone diameter, mean 3D attenuation value was a stronger predictor than established mean attenuation value, and parameters skewness and kurtosis performed better than recently emerged variation coefficient of stone density. Moreover, prediction of SWL outcome with 80% probability to be correct would be possible in a clearly higher number of patients (up to fivefold) using CT-CM-derived parameters.
Conclusions: Advanced NCCT post-processing by CT-CM provides novel parameters that seem to outperform established predictors of SWL response. Implementation of these parameters into clinical routine might reduce SWL failure rates.
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http://dx.doi.org/10.1007/s00345-018-2348-x | DOI Listing |
Front Sociol
January 2025
School of Education, Humanities and Social Sciences, Halmstad University, Halmstad, Sweden.
The article analyses how a norm scientific perspective can advance our understanding of cross-border regions and guide future directions of research. Cross-border regions are territorial spaces comprising territory from two or more national states, located directly at the borders of those spaces. Since the 1950s it has become increasingly common that cross-border organizations, constituted by local municipalities and regional authorities and sometimes private entities, are established to coordinate governance processes around shared policy problems.
View Article and Find Full Text PDFJHEP Rep
February 2025
Division of Hematology/Oncology, Department of Medicine, Tisch Cancer Institute, Mount Sinai Hospital, New York, NY, USA.
Background & Aims: Atezolizumab/bevacizumab (A/B) is now a standard first-line treatment for advanced hepatocellular carcinoma (HCC), but the optimal second-line regimen is not known. We evaluated real-world treatment patterns and outcomes to investigate factors associated with post-progression survival (PPS).
Methods: In this multicenter, international, retrospective study, we examined clinical characteristics and outcomes of patients with advanced HCC who progressed on first-line A/B.
Front Cardiovasc Med
January 2025
Clinical Laboratory, Children's Hospital Affiliated to Shandong University, Jinan, China.
Background: The nomogram is a powerful and robust tool in disease risk prediction that summarizes complex variables into a visual model that is interpretable with a quantified risk probability. In the current study, a nomogram was developed to predict the occurrence of coronary artery lesions (CALs) among patients with Kawasaki disease (KD). This is especially valuable in the early identification of the risk of CALs, which will lead to proper diagnosis and treatment to reduce their associated complications.
View Article and Find Full Text PDFSpine (Phila Pa 1976)
January 2025
Department of Neurosurgery, Lilavati Hospital and Research Center, Bandra, Mumbai, India.
Study Design: A systematic literature review and consensus using Delphi method.
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Summary Of Background: Os odontoideum (OO) is a rare anomaly of the cranio-vertebral junction (CVJ).
BMC Med Inform Decis Mak
January 2025
Department of Critical Care Medicine, First Affiliated Hospital of Harbin Medical University, Heilongjiang, China.
Background: Acute respiratory distress syndrome (ARDS) is a serious threat to human life. Hence, early and accurate diagnosis and treatment are crucial for patient survival. This meta-analysis evaluates the accuracy of artificial intelligence in the early diagnosis of ARDS and provides guidance for future research and applications.
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