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Abstract <p>Coma represents a critical failure of brain systems regulating arousal and awareness, posing significant diagnostic challenges when its origin is unknown. Accurate and timely diagnosis is essential to identify reversible causes and guide treatment. Here, we propose a comprehensive stepwise diagnostic algorithm integrating clinical examination, electroencephalography, neuroimaging, and laboratory investigations, emphasizing iterative reassessment to inform early decision-making. This approach, grounded in the pathophysiology of coma and current consciousness frameworks, facilitates localization of brain dysfunction and prioritizes detection of treatable etiologies. Emerging neurotechnologies, including advanced MRI and multimodal AI, hold promise for enhancing diagnosis and personalized management. Our framework aims to improve clinical outcomes by promoting systematic, physiology-based evaluation of coma of unknown origin in acute-care settings.</p> Visual abstract <p></p>

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Stepwise clinical and diagnostic strategy for coma of unknown origin

  • 期刊论文

  • 出版模式：

    开放获取

  • 发表日期：

    2026年4月30日

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  • Stein Silva,
  • Miriam Treggiari,
  • Giuseppe Citerio,
  • Robert David Stevens,
  • Marzia De Lucia,
  • Virginia Newcombe,
  • Aurore Thibaut,
  • Nicolas Weiss,
  • Romain Sonneville

摘要

Abstract

Coma represents a critical failure of brain systems regulating arousal and awareness, posing significant diagnostic challenges when its origin is unknown. Accurate and timely diagnosis is essential to identify reversible causes and guide treatment. Here, we propose a comprehensive stepwise diagnostic algorithm integrating clinical examination, electroencephalography, neuroimaging, and laboratory investigations, emphasizing iterative reassessment to inform early decision-making. This approach, grounded in the pathophysiology of coma and current consciousness frameworks, facilitates localization of brain dysfunction and prioritizes detection of treatable etiologies. Emerging neurotechnologies, including advanced MRI and multimodal AI, hold promise for enhancing diagnosis and personalized management. Our framework aims to improve clinical outcomes by promoting systematic, physiology-based evaluation of coma of unknown origin in acute-care settings.

Visual abstract