Publications by authors named "S Kakizaki"
Aim: This study aimed to compare the prognostic performance of the risk models for patients with hepatocellular carcinoma (HCC) receiving atezolizumab and bevacizumab (Atez/Bev) as first-line treatment.
Methods: Among 449 patients included in this retrospective multicenter study, we compared the prognostic performance of 13 risk models for the 12-month and 18-month survival status using area under the curve (AUC), net reclassification improvement (NRI), and relative integrated discrimination improvement (IDI) analysis. We also constructed a calibration plot to assess the fitness of each model.
In the current era of immune therapy, lenvatinib (LEN) continues to be vital for treating unresectable hepatocellular carcinoma (uHCC) patients. This study investigates the importance of nutritional status in the prognosis of uHCC patients receiving LEN and evaluates a new prognostic scoring system that combines the geriatric nutritional risk index (GNRI) and systemic inflammatory response. From 2018 to 2022, 484 uHCC patients treated with LEN (384 males, median age 73).
View Article and Find Full Text PDFBackground: Oral thrombopoietin receptor agonists are used to treat thrombocytopenia in patients with chronic liver disease who are scheduled for invasive procedures. The efficacy of lusutrombopag based on the pretreatment platelet count was investigated.
Methods: Patients treated at nine hospitals from December 2015 to December 2023 were included.
Article Synopsis
- Optical coherence tomography (OCT) is used to identify dangerous plaques in patients with acute coronary syndrome (ACS), but manual analysis has its limitations.
- This study developed a deep-learning model using convolutional neural networks (CNN) and transformers to automatically predict the prognosis of ACS patients from OCT images after they underwent percutaneous coronary intervention (PCI).
- The deep-learning model showed superior predictive performance for target vessel failure compared to traditional models, indicating that it can effectively analyze OCT images as well as or better than human observers.