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肺部超声在 ARDS 诊断及局灶性或非局灶性 ARDS 亚表型鉴别中的诊断准确性:系统评价和荟萃分析。

Diagnostic accuracy of lung ultrasound in diagnosis of ARDS and identification of focal or non-focal ARDS subphenotypes: a systematic review and meta-analysis.

机构信息

Department of Intensive Care Medicine, Noordwest Ziekenhuisgroep, Wilhelminalaan 12, Alkmaar, The Netherlands.

Department of Intensive Care Medicine, Amsterdam UMC, Vrije Universiteit Amsterdam, De Boelelaan 1117, Amsterdam, The Netherlands.

出版信息

Crit Care. 2024 Jul 8;28(1):224. doi: 10.1186/s13054-024-04985-1.

DOI:10.1186/s13054-024-04985-1
PMID:38978055
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC11232316/
Abstract

BACKGROUND

Acute respiratory distress syndrome (ARDS) is a life-threatening respiratory condition with high mortality rates, accounting for 10% of all intensive care unit admissions. Lung ultrasound (LUS) as diagnostic tool for acute respiratory failure has garnered widespread recognition and was recently incorporated into the updated definitions of ARDS. This raised the hypothesis that LUS is a reliable method for diagnosing ARDS.

OBJECTIVES

We aimed to establish the accuracy of LUS for ARDS diagnosis and classification of focal versus non-focal ARDS subphenotypes.

METHODS

This systematic review and meta-analysis used a systematic search strategy, which was applied to PubMed, EMBASE and cochrane databases. Studies investigating the diagnostic accuracy of LUS compared to thoracic CT or chest radiography (CXR) in ARDS diagnosis or focal versus non-focal subphenotypes in adult patients were included. Quality of studies was evaluated using the QUADAS-2 tool. Statistical analyses were performed using "Mada" in Rstudio, version 4.0.3. Sensitivity and specificity with 95% confidence interval of each separate study were summarized in a Forest plot.

RESULTS

The search resulted in 2648 unique records. After selection, 11 reports were included, involving 2075 patients and 598 ARDS cases (29%). Nine studies reported on ARDS diagnosis and two reported on focal versus non-focal ARDS subphenotypes classification. Meta-analysis showed a pooled sensitivity of 0.631 (95% CI 0.450-0.782) and pooled specificity of 0.942 (95% CI 0.856-0.978) of LUS for ARDS diagnosis. In two studies, LUS could accurately differentiate between focal versus non-focal ARDS subphenotypes. Insufficient data was available to perform a meta-analysis.

CONCLUSION

This review confirms the hypothesis that LUS is a reliable method for diagnosing ARDS in adult patients. For the classification of focal or non-focal subphenotypes, LUS showed promising results, but more research is needed.

摘要

背景

急性呼吸窘迫综合征(ARDS)是一种危及生命的呼吸系统疾病,死亡率高,占所有重症监护病房入院人数的 10%。肺部超声(LUS)作为急性呼吸衰竭的诊断工具已经得到广泛认可,并于最近被纳入 ARDS 的更新定义中。这就提出了一个假设,即 LUS 是一种可靠的 ARDS 诊断方法。

目的

我们旨在确定 LUS 诊断 ARDS 和分类局灶性与非局灶性 ARDS 亚表型的准确性。

方法

本系统评价和荟萃分析采用系统搜索策略,应用于 PubMed、EMBASE 和 Cochrane 数据库。纳入研究旨在比较 LUS 与胸部 CT 或胸部 X 线摄影(CXR)在 ARDS 诊断或成人患者局灶性与非局灶性亚表型中的诊断准确性。使用 QUADAS-2 工具评估研究质量。使用 Rstudio 版本 4.0.3 中的"Mada"进行统计分析。汇总每个单独研究的敏感性和特异性及其 95%置信区间,并绘制森林图。

结果

搜索结果产生了 2648 条独特的记录。经过筛选,有 11 项研究被纳入,共涉及 2075 名患者和 598 例 ARDS 患者(29%)。9 项研究报告了 ARDS 诊断,2 项研究报告了局灶性与非局灶性 ARDS 亚表型分类。荟萃分析显示,LUS 诊断 ARDS 的汇总敏感性为 0.631(95%CI 0.450-0.782),汇总特异性为 0.942(95%CI 0.856-0.978)。在两项研究中,LUS 能够准确地区分局灶性与非局灶性 ARDS 亚表型。由于数据不足,无法进行荟萃分析。

结论

本综述证实了 LUS 是一种可靠的成人 ARDS 诊断方法的假设。对于局灶性或非局灶性亚表型的分类,LUS 显示出有前景的结果,但需要进一步的研究。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4222/11232316/4d0c485a137b/13054_2024_4985_Fig4_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4222/11232316/cebbbb1b17df/13054_2024_4985_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4222/11232316/b08f24551d44/13054_2024_4985_Fig2_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4222/11232316/5378c46c05e3/13054_2024_4985_Fig3_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4222/11232316/4d0c485a137b/13054_2024_4985_Fig4_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4222/11232316/cebbbb1b17df/13054_2024_4985_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4222/11232316/b08f24551d44/13054_2024_4985_Fig2_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4222/11232316/5378c46c05e3/13054_2024_4985_Fig3_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4222/11232316/4d0c485a137b/13054_2024_4985_Fig4_HTML.jpg

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