通讯作者: 刘雪兰, lhlliuxuelan@nbu.edu.cn

DOI：10.12201/bmr.202606.00012

Advances in Exhaled Breath Analysis for Diagnosis of Diabetic Ketoacidosis

• 摘要：糖尿病酮症酸中毒(diabetic ketoacidosis,DKA)是糖尿病最严重的急性并发症之一,其发病率在全球范围内持续上升。现有诊断主要依赖血酮体和尿酮体检测,具有侵入性、延迟性等局限。呼气分析(exhaled breath analysis, EBA)作为一种新兴的无创检测手段,通过检测呼出气体中丙酮等挥发性有机化合物(volatile organic compounds,VOCs),可实现DKA的快速、实时筛查。近年来,基于质谱技术、气体传感器、电子鼻以及人工智能算法的呼气分析技术取得了重要进展。多项临床研究证实呼气丙酮与血酮体水平呈显著正相关,基于传感器的便携式设备在DKA诊断、疗效监测及钠-葡萄糖共转运体2(SGLT2)抑制剂相关酮症风险评估中展现出良好的应用前景。然而,该领域仍面临呼气采集标准化不足、个体间变异大、缺乏大规模多中心临床验证及监管审批设备等挑战。本文就DKA的酮体代谢特征及呼气丙酮的生物学基础、检测技术、人工智能辅助算法以及临床研究进展与局限性等方面进行综述,以期为DKA的无创早期诊断提供参考。

  关键词： 糖尿病酮症酸中毒; 呼气分析; 丙酮; 生物标志物; 气体传感器; 电子鼻

   

  Abstract: Diabetic ketoacidosis (DKA) is one of the most serious acute complications of diabetes mellitus, with its incidence continuing to rise globally. Current diagnosis relies mainly on blood and urine ketone testing, which has limitations including invasiveness and delayed results. Exhaled breath analysis(EBA), as an emerging non-invasive detection approach, can achieve rapid and real-time screening of DKA by detecting acetone and other volatile organic compounds (VOCs) in exhaled breath. In recent years, significant advances have been made in breath analysis technologies based on mass spectrometry, gas sensors, electronic noses, and artificial intelligence algorithms. Multiple clinical studies have confirmed a significant positive correlation between breath acetone and blood ketone levels, and portable sensor-based devices have demonstrated promising prospects in DKA diagnosis, therapeutic monitoring, and ketosis risk assessment associated with sodium-glucose cotransporter 2 (SGLT2) inhibitors. However, this field still faces challenges including lack of standardized breath collection protocols, significant inter-individual variability, insufficient large-scale multicenter clinical validation, and absence of regulatory-approved devices. This article reviews the biological basis of ketone body metabolism and breath acetone in DKA, detection technologies, AI-assisted algorithms, clinical research progress and limitations, aiming to provide references for non-invasive early diagnosis of DKA.

  Key words: Diabetic ketoacidosis; Exhaled breath analysis; Acetone; Biomarker; Gas sensor; Electronic nose

  提交时间：2026-06-05

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• 序号	提交日期	编号	操作
  1	2026-05-14	10.12201/bmr.202606.00012V1	下载

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