Introduction: Cerebral hydrodynamics complications in shunted patients are due to the malfunction of the system. The objective of this retrospective, single-center, single-arm cohort study is to confirm the safety and performance of Sphera® Duo when used in adult patients suffering from hydrocephalus, pseudotumor cerebri or arachnoid cysts.
Methods: Data were generated by reviewing 112 adult patient's charts, who were submitted to a ventriculoperitoneal shunt surgery and followed for one year after surgery.
Results: The results show us that 76% of patients had their neurological symptoms improved and that the reoperation rate was 15% in the first year following surgery.
Discussion: Sphera Duo® shunt system is an applicable shunt option in routine neurosurgical management of hydrocephalus by several causes. It has presented good results while mitigating effects of overdrainage. Overdrainage is especially important in adults with non-hypertensive hydrocephalus and can cause functional shunt failure, which causes subnormal ICP (particularly in the upright position) and is associated with characteristic neurological symptoms, such as postural headache and nausea.
Conclusion: Sphera Duo® shunt system is safe when used in adult patients suffering from hydrocephalus, pseudotumor cerebri or arachnoid cyst.
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http://dx.doi.org/10.1590/0004-282X20190135 | DOI Listing |
JCO Clin Cancer Inform
December 2024
Onc.AI, San Carlos, CA.
Purpose: This study developed and validated a novel deep learning radiomic biomarker to estimate response to immune checkpoint inhibitor (ICI) therapy in advanced non-small cell lung cancer (NSCLC) using real-world data (RWD) and clinical trial data.
Materials And Methods: Retrospective RWD of 1,829 patients with advanced NSCLC treated with PD-(L)1 ICIs were collected from 10 academic and community institutions in the United States and Europe. The RWD included data sets for discovery (Data Set A-Discovery, n = 1,173) and independent test (Data Set B, n = 458).
Radiology
November 2024
From Koninklijke Philips NV, Amsterdam, the Netherlands (C.L.T., M.V.G., S.N., C.M., J.G., O.S., S.T.); and Department of Radiology, Vanderbilt University Medical Center, 1211 Medical Center Dr, VUH 1145, Nashville, TN 37212 (D.P., R.A.O., D.E.C., J.R.S.).
Background Climate change, driven primarily by human-induced greenhouse gas (GHG) emissions, poses major risks to human health. Health care contributes 8.5% of GHG emissions in the United States.
View Article and Find Full Text PDFSci Rep
November 2024
Department of Civil Engineering and Architecture DICAr and Water Research Centre CRA, University of Pavia, via Ferrata 3, Pavia, 27100, Italy.
This study illustrates the full-scale 3D numerical simulation of the coupled water-landslide dynamics of the 1963 Vajont catastrophic event. The focus is given to the early phase of the event when about 270 million cubic meters of rock fell into the reservoir within an estimated runout time of about 25 s. A complex surge wave system developed throughout the basin in the first 40-55 s, producing maximum run-up of 270 m above the dam crowning.
View Article and Find Full Text PDFLancet Oncol
November 2024
Department of Radiology, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA.
Lancet Oncol
November 2024
Institute of Neuroscience and Medicine (INM-4), Research Center Juelich (FZJ), Juelich, Germany; Department of Neurology, Faculty of Medicine and University Hospital Cologne, Cologne, Germany.
The development, application, and benchmarking of artificial intelligence (AI) tools to improve diagnosis, prognostication, and therapy in neuro-oncology are increasing at a rapid pace. This Policy Review provides an overview and critical assessment of the work to date in this field, focusing on diagnostic AI models of key genomic markers, predictive AI models of response before and after therapy, and differentiation of true disease progression from treatment-related changes, which is a considerable challenge based on current clinical care in neuro-oncology. Furthermore, promising future directions, including the use of AI for automated response assessment in neuro-oncology, are discussed.
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