Publications by authors named "Y NOHARA"

This report discusses a rare case of delayed migration of a Sapien 3 Ultra Resilia (S3UR) valve following transcatheter aortic valve implantation. An 81-year-old Japanese woman had a borderline aortic annular size of 20-23 mm according to the manufacturer's size chart. We chose to implant a smaller S3UR of 20 mm with an 80/20 depth ratio to allow for a second intervention, ensuring good hemodynamics and minimizing paravalvular leak.

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Background And Purpose: Maintaining mitochondrial quality is attracting attention as a new strategy to treat diabetes and diabetic complications. We previously reported that mitochondrial hyperfission by forming a protein complex between dynamin-related protein (Drp) 1 and filamin, mediates chronic heart failure and cilnidipine, initially developed as an L/N-type Ca channel blocker, improves heart failure by inhibiting Drp1-filamin protein complex. We investigated whether cilnidipine improves hyperglycaemia of various diabetic mice models.

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Article Synopsis
  • This study investigates the effectiveness of machine learning models in predicting poststroke outcomes compared to traditional stroke prognostic scores using data from over 10,000 patients in Japan.
  • The research focuses on predicting poor functional status and mortality after stroke, using various machine learning techniques and regularization methods for model development.
  • Results indicate differences in the variables used by machine learning models versus traditional scores, highlighting the potential for improved predictive performance in stroke outcomes.
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Delirium is common in the emergency department, and once it develops, there is a risk of self-extubation of drains and tubes, so it is critical to predict delirium before it occurs. Machine learning was used to create two prediction models in this study: one for predicting the occurrence of delirium and one for predicting self-extubation after delirium. Each model showed high discriminative performance, indicating the possibility of selecting high-risk cases.

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