Prognostic findings for ICU admission in patients with COVID-19 pneumonia: baseline and follow-up chest CT and the added value of artificial intelligence.
Prognostic findings for ICU admission in patients with COVID-19 pneumonia: baseline and follow-up chest CT and the added value of artificial intelligence.
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DOI：
10.1007/s10140-021-02008-y
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发表时间：
2022-04
影响因子：
2.2
通讯作者：
Savevski V
中科院分区：
文献类型：
--
作者：
Laino ME;Ammirabile A;Lofino L;Lundon DJ;Chiti A;Francone M;Savevski V
在过去的18个月里，SARS-CoV-2感染主导了讨论，并导致了全球医疗保健和经济危机。冠状病毒病19（COVID-19）在大多数人中引起轻度至中度症状。然而，部分患者在出现症状后1-2周内可能会迅速恶化为严重疾病，伴或不伴急性呼吸窘迫综合征（ARDS）。通过对此类患者进行风险分层进行早期识别，这些患者有可能发生COVID-19严重并发症，这具有重要的临床意义。计算机断层扫描（CT）广泛可用，并提供了快速分诊、稳健、快速和微创诊断的潜力：毛玻璃样阴影（GGO）、疯狂铺路模式（GGO伴叠加间隔增厚）和实变是COVID肺炎最常见的胸部CT表现。人们对基线胸部CT的预后价值越来越感兴趣，因为对COVID-19患者进行早期风险分层将有助于更好的资源分配，并有助于改善结果。最近的研究表明，基线胸部CT可用于预测COVID-19患者入住重症监护室（ICU）。此外，将人工智能（AI）与计算机辅助设计（CAD）软件集成用于诊断成像的发展和进步允许客观，公正和快速评估CT图像。
Infection with SARS-CoV-2 has dominated discussion and caused global healthcare and economic crisis over the past 18 months. Coronavirus disease 19 (COVID-19) causes mild-to-moderate symptoms in most individuals. However, rapid deterioration to severe disease with or without acute respiratory distress syndrome (ARDS) can occur within 1–2 weeks from the onset of symptoms in a proportion of patients. Early identification by risk stratifying such patients who are at risk of severe complications of COVID-19 is of great clinical importance. Computed tomography (CT) is widely available and offers the potential for fast triage, robust, rapid, and minimally invasive diagnosis: Ground glass opacities (GGO), crazy-paving pattern (GGO with superimposed septal thickening), and consolidation are the most common chest CT findings in COVID pneumonia. There is growing interest in the prognostic value of baseline chest CT since an early risk stratification of patients with COVID-19 would allow for better resource allocation and could help improve outcomes. Recent studies have demonstrated the utility of baseline chest CT to predict intensive care unit (ICU) admission in patients with COVID-19. Furthermore, developments and progress integrating artificial intelligence (AI) with computer-aided design (CAD) software for diagnostic imaging allow for objective, unbiased, and rapid assessment of CT images.
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