Artificial intelligence's suggestions for level of amputation in diabetic foot ulcers are highly correlated with those of clinicians, only with exception of hindfoot amputations.

IF 2.6 3区 医学 Q2 DERMATOLOGY
Merve Mert, Arman Vahabi, Ali Engin Daştan, Abdussamet Kuyucu, Yunus Can Ünal, Okan Tezgel, Anıl Murat Öztürk, Meltem Taşbakan, Kemal Aktuğlu
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Abstract

Diabetic foot ulcers (DFUs) are a growing public health problem, paralleling the increasing incidence of diabetes. While prevention is most effective treatment for DFUs, challenge remains on selecting the optimal treatment in cases with DFUs. Health sciences have greatly benefited from the integration of artificial intelligence (AI) applications across various fields. Regarding amputations in DFUs, both literature and clinical practice have mainly focused on strategies to prevent amputation and identify avoidable risk factor. However, there are very limited data on assistive parameters/tools that can be used to determine the level of amputation. This study investigated how well ChatGPT, with its lately released version 4o, matches the amputation level selection of an experienced team in this field. For this purpose, clinical photographs from patients who underwent amputations due to diabetic foot ulcers between May 2023 and May 2024 were submitted to the ChatGPT-4o program. The AI was tasked with recommending an appropriate amputation level based on these clinical photographs. Data from a total of 60 patients were analysed, with a median age of 64.5 years (range: 41-91). According to the Wagner Classification, 32 patients (53.3%) had grade 4 ulcers, 16 patients (26.6%) had grade 5 ulcers, 10 patients (16.6%) had grade 3 ulcers and 2 patients (3.3%) had grade 2 ulcers. A one-to-one correspondence between the AI tool's recommended amputation level and the level actually performed was observed in 50 out of 60 cases (83.3%). In the remaining 10 cases, discrepancies were noted, with the AI consistently recommending a more proximal level of amputation than what was performed. The inter-rater agreement analysis between the actual surgeries and the AI tool's recommendations yielded a Cohen's kappa coefficient of 0.808 (SD: 0.055, 95% CI: 0.701-0.916), indicating substantial agreement. Relying solely on clinical photographs, ChatGPT-4.0 demonstrates decisions that are largely consistent with those of an experienced team in determining the optimal level of amputation for DFUs, with the exception of hindfoot amputations.

人工智能对糖尿病足溃疡截肢程度的建议与临床医生的建议高度相关,但后足截肢除外。
糖尿病足溃疡(DFUs)是一个日益严重的公共卫生问题,与糖尿病发病率的上升同步。虽然预防是治疗糖尿病足溃疡最有效的方法,但如何为糖尿病足溃疡患者选择最佳治疗方法仍是一项挑战。人工智能(AI)在各个领域的应用使健康科学受益匪浅。关于 DFU 的截肢问题,文献和临床实践主要关注预防截肢和识别可避免风险因素的策略。然而,有关可用于确定截肢程度的辅助参数/工具的数据却非常有限。本研究调查了最新发布的 4o 版 ChatGPT 与该领域经验丰富的团队所选择的截肢等级的匹配程度。为此,我们向 ChatGPT-4o 程序提交了 2023 年 5 月至 2024 年 5 月间因糖尿病足溃疡而截肢的患者的临床照片。人工智能的任务是根据这些临床照片推荐合适的截肢等级。共分析了 60 名患者的数据,中位年龄为 64.5 岁(41-91 岁)。根据瓦格纳分类法,32 名患者(53.3%)患有 4 级溃疡,16 名患者(26.6%)患有 5 级溃疡,10 名患者(16.6%)患有 3 级溃疡,2 名患者(3.3%)患有 2 级溃疡。在 60 个病例中,有 50 例(83.3%)观察到人工智能工具推荐的截肢等级与实际实施的截肢等级一一对应。在其余 10 个病例中发现了差异,人工智能推荐的截肢水平始终高于实际截肢水平。实际手术与人工智能工具建议之间的评分者间一致性分析得出的科恩卡帕系数(Cohen's kappa coefficient)为 0.808(SD:0.055,95% CI:0.701-0.916),表明两者之间的一致性非常高。仅依靠临床照片,ChatGPT-4.0 与经验丰富的团队在确定 DFU 最佳截肢程度时所做出的决定基本一致,但后足截肢除外。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
International Wound Journal
International Wound Journal DERMATOLOGY-SURGERY
CiteScore
4.50
自引率
12.90%
发文量
266
审稿时长
6-12 weeks
期刊介绍: The Editors welcome papers on all aspects of prevention and treatment of wounds and associated conditions in the fields of surgery, dermatology, oncology, nursing, radiotherapy, physical therapy, occupational therapy and podiatry. The Journal accepts papers in the following categories: - Research papers - Review articles - Clinical studies - Letters - News and Views: international perspectives, education initiatives, guidelines and different activities of groups and societies. Calendar of events The Editors are supported by a board of international experts and a panel of reviewers across a range of disciplines and specialties which ensures only the most current and relevant research is published.
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