Suppr超能文献

新生儿呼吸窘迫综合征中的肺部超声:过去十年的叙述性综述

Lung Ultrasound in Neonatal Respiratory Distress Syndrome: A Narrative Review of the Last 10 Years.

作者信息

Costa Federico, Titolo Annachiara, Ferrocino Mandy, Biagi Eleonora, Dell'Orto Valentina, Perrone Serafina, Esposito Susanna

机构信息

Pediatric Clinic, Parma University Hospital, Department of Medicine and Surgery, University of Parma, 43126 Parma, Italy.

Neonatology Unit, Parma University Hospital, Department of Medicine and Surgery, University of Parma, 43126 Parma, Italy.

出版信息

Diagnostics (Basel). 2024 Dec 12;14(24):2793. doi: 10.3390/diagnostics14242793.

Abstract

Neonatal respiratory distress syndrome (RDS) is a common and potentially life-threatening condition in preterm infants, primarily due to surfactant deficiency. Early and accurate diagnosis is critical to guide timely interventions such as surfactant administration and respiratory support. Traditionally, chest X-rays have been used for diagnosis, but lung ultrasound (LUS) has gained prominence due to its non-invasive, radiation-free, and bedside applicability. Compared to chest X-rays and CT scans, LUS demonstrates superior sensitivity and specificity in diagnosing RDS, particularly in identifying surfactant need and predicting CPAP failure. Additionally, LUS offers real-time imaging without radiation exposure, an advantage over other modalities. However, its broader adoption is limited by challenges in standardizing training, ensuring diagnostic reproducibility, and validating scoring systems, especially in resource-limited settings. This narrative review aims to evaluate the role of LUS in the diagnosis and management of neonatal RDS over the past decade, focusing on its clinical utility, scoring systems, and emerging applications. We reviewed the literature from 2013 to 2023, focusing on studies evaluating LUS' diagnostic accuracy, scoring systems, and its potential role in guiding surfactant therapy and predicting CPAP failure. Despite its benefits, addressing the variability in operator expertise and integrating artificial intelligence to enhance usability are crucial for ensuring LUS' efficacy across diverse clinical environments. Future research should prioritize standardizing training and scoring protocols to facilitate wider implementation and optimize neonatal respiratory care outcomes.

摘要

新生儿呼吸窘迫综合征(RDS)是早产儿常见且可能危及生命的病症,主要原因是表面活性物质缺乏。早期准确诊断对于指导及时干预(如给予表面活性物质和呼吸支持)至关重要。传统上,胸部X光用于诊断,但肺部超声(LUS)因其无创、无辐射且可在床边应用而受到关注。与胸部X光和CT扫描相比,LUS在诊断RDS方面表现出更高的敏感性和特异性,尤其是在确定是否需要表面活性物质以及预测持续气道正压通气(CPAP)失败方面。此外,LUS可提供无辐射暴露的实时成像,这是优于其他检查方式的优势。然而,其更广泛应用受到标准化培训、确保诊断可重复性以及验证评分系统等挑战的限制,尤其是在资源有限的环境中。本叙述性综述旨在评估过去十年中LUS在新生儿RDS诊断和管理中的作用,重点关注其临床实用性、评分系统及新兴应用。我们回顾了2013年至2023年的文献,重点关注评估LUS诊断准确性、评分系统及其在指导表面活性物质治疗和预测CPAP失败方面潜在作用的研究。尽管LUS有诸多益处,但解决操作人员专业水平的差异并整合人工智能以提高其可用性,对于确保LUS在不同临床环境中的有效性至关重要。未来研究应优先标准化培训和评分方案,以促进更广泛的应用并优化新生儿呼吸护理结果。

相似文献

本文引用的文献

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验