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The role of artificial intelligence (AI) in healthcare is evolving, offering promising avenues for enhancing clinical decision making and patient management. Limited knowledge about lipedema often leads to patients being frequently misdiagnosed with conditions like lymphedema or obesity rather than correctly identifying lipedema. Furthermore, patients with lipedema often present with intricate and extensive medical histories, resulting in significant time consumption during consultations. AI could, therefore, improve the management of these patients. This research investigates the utilization of OpenAI's Generative Pre-Trained Transformer 4 (GPT-4), a sophisticated large language model (LLM), as an assistant in consultations for lipedema patients. Six simulated scenarios were designed to mirror typical patient consultations commonly encountered in a lipedema clinic. GPT-4 was tasked with conducting patient interviews to gather medical histories, presenting its findings, making preliminary diagnoses, and recommending further diagnostic and therapeutic actions. Advanced prompt engineering techniques were employed to refine the efficacy, relevance, and accuracy of GPT-4's responses. A panel of experts in lipedema treatment, using a Likert Scale, evaluated GPT-4's responses across six key criteria. Scoring ranged from 1 (lowest) to 5 (highest), with GPT-4 achieving an average score of 4.24, indicating good reliability and applicability in a clinical setting. This study is one of the initial forays into applying large language models like GPT-4 in specific clinical scenarios, such as lipedema consultations. It demonstrates the potential of AI in supporting clinical practices and emphasizes the continuing importance of human expertise in the medical field, despite ongoing technological advancements.
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Lipedema and obesity are chronic, frequently progressive disorders that can present with increased adipose-tissue volume, functional impairment and reduced quality of life. Although often approached as differential diagnoses, they frequently coexist and may aggravate one another. This narrative review addresses how lipedema and obesity interact biologically and clinically and what evidence supports a staged interdisciplinary approach to diagnosis and management. Obesity is increasingly conceptualized as an adiposity-based chronic disease characterized by excess adipose, abnormal adipose-tissue distribution or dysfunction, and associated medical or functional impairment. Obesity can impair lymphatic morphology and function, whereas lymphatic dysfunction may promote subcutaneous adipose-tissue expansion and fibrosis. Literature was identified through iterative PubMed searches and focused supplementary searches in Embase and the Cochrane Library. Publications were selected purposively for their relevance to predefined clinical and mechanistic domains; no systematic screening or formal risk-of-bias assessment was performed. This review synthesizes clinical overlap, biological evidence, diagnostic implications, and staged management for predominantly adult women with suspected or confirmed lipedema, including those with coexisting overweight or obesity. The proposed framework is intended to support clinical reasoning rather than serve as a formal guideline.
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- Lipedema
- Open Access (2)
- Review (1)
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- Journal Article (2)
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- Open Access (2)