Publications by authors named "Diana-Federica Balta"
Diabetic foot ulcers represent a serious and costly complication of diabetes, with significant morbidity and mortality. The purpose of this study was to explore advancements in Artificial Intelligence, and wearable technologies for the prevention and management of diabetic foot ulcers. Key findings indicate that Artificial Intelligence-driven predictive analytics can identify early signs of diabetic foot ulcers, enabling timely interventions.
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- Type 2 diabetes mellitus (DM) is a significant global health issue, with infected diabetic foot ulcers (IDFUs) being a major complication that is linked to other conditions like neuropathy and dyslipidemia.
- The study aimed to analyze lipid profiles in DM patients with IDFUs compared to those without ulcers and healthy controls, involving a total of 140 participants divided into three groups.
- Results indicated that patients with IDFUs had lower high-density lipoprotein cholesterol (HDL-C) levels but improved levels of other lipids and apolipoprotein E (ApoE), highlighting an unusual lipid profile pattern associated with diabetic complications.
Strategies have been researched and implemented to reduce the number of people with diabetic foot ulcers (DFUs). One problem is the accurate assessment of DFU severity, which is the main factor in resource allocation and treatment choice. The primary objective of this study was to assess pentraxin-3 as a biomarker of an infected DFU (IDFU), the limb amputation level prognosis, and patient survival.
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