AIMC Topic: Sarcopenia

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Development and validation of nomogram and machine learning models to predict sarcopenia in patients with chronic kidney disease.

Scientific reports
Chronic kidney disease (CKD) is a growing public health problem worldwide. CKD not only leads to renal function decline but also increases the risk of multiple complications, sarcopenia being particularly common and severe. At present, there is a lac...

Impact of imaging biomarkers from body composition analysis on outcome of endovascularly treated acute ischemic stroke patients.

Journal of neurointerventional surgery
BACKGROUND: We investigate the association of imaging biomarkers extracted from fully automated body composition analysis (BCA) of computed tomography (CT) angiography images of endovascularly treated acute ischemic stroke (AIS) patients regarding an...

A neural network approach to sarcopenia prediction based on bioelectrical impedance in community-dwelling older adults.

PloS one
This study aimed to apply a neural network to raw bioelectrical impedance analysis data and to test whether sarcopenia could be predicted with high accuracy. The study population comprised 727 community-dwelling older adults aged 65-85 years who part...

Application of interpretable machine learning to predict activities of daily living disability in sarcopenia: insights from the CHARLS dataset.

BMC geriatrics
PURPOSE: The decline in activities of daily living (ADL) among older persons is a significant public health concern. Sarcopenia is a major risk factor for ADL disability. This study aimed to develop and validate an interpretable machine learning (IML...

Plantar pressure distribution can be used to identify sarcopenia in maintenance hemodialysis patients.

Scientific reports
Patients undergoing maintenance hemodialysis (MHD) often suffer from sarcopenia, which affects their balance and significantly increases the risk of falls and death. Actively identifying sarcopenia, understanding the relationship between sarcopenia a...

3D deep learning-based muscle volume quantification from thoracic CT as a surrogate for DXA-Derived appendicular muscle mass in older adults.

Aging clinical and experimental research
BACKGROUND: In order to identify patients with sarcopenia, the use of routine imaging could provide valuable support. One of the most common radiological examinations, especially in geriatric inpatient care, is CT thoracic imaging. Therefore, it woul...

Microenvironment-driven satellite cell regeneration and repair in aging-related sarcopenia: mechanisms and therapeutic frontiers.

Stem cell research & therapy
Sarcopenia, a progressive age-related decline in skeletal muscle mass and function, is closely linked to impaired regenerative capacity of satellite cells (SCs), also known as satellite cells. Age-dependent SCs dysfunction, driven by intrinsic senesc...

Construct prediction models for low muscle mass with metabolic syndrome using machine learning.

PloS one
BACKGROUND: Metabolic syndrome (MetS) and sarcopenia are major global public health problems, and their coexistence significantly increases the risk of death. In recent years, this trend has become increasingly prominent in younger populations, posin...

Implementation of Fully Automated AI-Integrated System for Body Composition Assessment on Computed Tomography for Opportunistic Sarcopenia Screening: Multicenter Prospective Study.

JMIR formative research
BACKGROUND: Opportunistic computed tomography (CT) screening for the evaluation of sarcopenia and myosteatosis has been gaining emphasis. A fully automated artificial intelligence (AI)-integrated system for body composition assessment on CT scans is ...