Publications by authors named "J J Yeh"

We aimed to compare the scar quality and recovery rate of joint activity for patients with joint-involved burn injuries receiving either artificial dermis (AD) with split-thickness skin graft (STSG) or full-thickness skin graft (FTSG) for reconstruction. The primary outcomes were %skin graft (SG) take. Secondary outcomes included complications such as the infection rate and donor site morbidity, 12-month scar quality evaluated using the Vancouver scar scale (VSS), recovery rate of joint activity and incidence of scar contracture requiring further revision.

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Objective: The management of preoperative medications is an essential component of perioperative care for the cardiac surgical patient. This turnkey order set is part of a series created by the Enhanced Recovery After Surgery Cardiac Society, first presented at the Annual Meeting of The American Association for Thoracic Surgery in 2023. Numerous guidelines and expert consensus documents have been published to provide guidance in preoperative medication management.

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: The aim of the study was to assess the effect of high-intensity focused electromagnetic (HIFEM) technology in the treatment of female stress urinary incontinence (SUI). : 20 women with SUI were delivered a treatment course with HIFEM technology. Patients attended 6 therapies scheduled twice a week.

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Complete spinal cord injury (SCI) causes permanent locomotor, sensory and neurological dysfunctions. Targeting complex immunopathological microenvironment at SCI sites comprising inflammatory cytokines infiltration, oxidative stress and massive neuronal apoptosis, the conductive oriented nanofiber felt with efficient ROS clearance, anti-inflammatory effect and accelerating neural regeneration is constructed by step-growth addition polymerization and electrostatic spinning technique for SCI repair. The formation of innovative Fe-PDA-PAT chelate in nanofiber felt enhances hydrophilic, antioxidant, antibacterial, hemostatic and binding factor capacities, thereby regulating immune microenvironment of SCI.

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Objective: Myasthenia gravis (MG), a low-prevalence autoimmune disorder characterized by clinical heterogeneity and unpredictable disease fluctuations, presents significant risks of acute exacerbations requiring intensive care. These crises contribute substantially to patient morbidity and mortality. This study aimed to develop and validate machine-learning models for predicting intensive care unit (ICU) admission risk among patients with MG-related disease instability.

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