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Adaptation of the Taiwan Version of the Supportive and Palliative Care Indicators Tool (SPICT-TW) and Its Association with Six-Month Mortality: A Multi-Center Validation Study in Older People.
Healthcare (Basel)
November 2024
Department of Family Medicine, Kaohsiung Medical University Hospital, Kaohsiung Medical University, Kaohsiung 807, Taiwan.
The Supportive and Palliative Care Indicators Tool (SPICT) was developed for identifying, in a timely manner, patients who may benefit from supportive and palliative care for better treatment review, care-plan discussion, and end-of-life care. Although the SPICT has been validated in different languages and for patients living in different settings, it has not been validated for patients receiving home-based medical care (HBMC), or in the context of using traditional Chinese characters. The present study aimed to validate the Taiwanese version of the SPICT (SPICT-TW) and to measure its ability to predict six-month mortality in patients who received HBMC in Taiwan.
View Article and Find Full Text PDFBackground: No accurate prognostic tool is available for patients with cancer who spend their final days at home. In this study, we examined whether performance status (PS) and the palliative prognostic index (PPI), a well-known prognostic tool in palliative care units, could be used to predict prognosis in the home care setting at the time of intervention by home physicians.
Subjects And Methods: Using medical records, we conducted a retrospective analysis of 132 patients who were referred to the Home Clinic Naginoki for home care for terminal stages of carcinoma in situ.
Hip contact forces can be predicted with a neural network using only synthesised key points and electromyography in people with hip osteoarthritis.
Osteoarthritis Cartilage
June 2024
Griffith Centre of Biomedical and Rehabilitation Engineering, Menzies Health Institute Queensland, Griffith University, Gold Coast, Australia; School of Health Sciences and Social Work, Griffith University, Gold Coast, Australia. Electronic address:
Objective: To develop and validate a neural network to estimate hip contact forces (HCF), and lower body kinematics and kinetics during walking in individuals with hip osteoarthritis (OA) using synthesised anatomical key points and electromyography. To assess the capability of the neural network to detect directional changes in HCF resulting from prescribed gait modifications.
Design: A calibrated electromyography-informed neuromusculoskeletal model was used to compute lower body joint angles, moments, and HCF for 17 participants with mild-to-moderate hip OA.
M1-like macrophage contributes to chondrogenesis in vitro.
Sci Rep
October 2021
Department of Tissue Engineering, The University of Tokyo Hospital, Tokyo, 113-8655, Japan.
Cartilage tissues have poor self-repairing abilities. Regenerative medicine can be applied to recover cartilage tissue damage in the oral and maxillofacial regions. However, hitherto it has not been possible to predict the maturity of the tissue construction after transplantation or to prepare mature cartilage tissues before transplantation that can meet clinical needs.
View Article and Find Full Text PDFDeep Neural Network for Early Image Diagnosis of Stevens-Johnson Syndrome/Toxic Epidermal Necrolysis.
J Allergy Clin Immunol Pract
January 2022
Division of Dermatology, Niigata University Graduate School of Medical and Dental Sciences, Niigata, Japan. Electronic address:
Background: Stevens-Johnson syndrome (SJS)/toxic epidermal necrolysis (TEN) is a life-threatening cutaneous adverse drug reaction (cADR). Distinguishing SJS/TEN from nonsevere cADRs is difficult, especially in the early stages of the disease.
Objective: To overcome this limitation, we developed a computer-aided diagnosis system for the early diagnosis of SJS/TEN, powered by a deep convolutional neural network (DCNN).
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