Azadeh Doozandeh, Mohammadmehdi Hatami, Zahra Khorrami, Ali Sadatmoosavi, Mohammad Farjami, Ghazale Soltani
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引用次数: 0
Abstract
Optical coherence tomography (OCT) diagnostic technology is increasingly being integrated into clinical practice and is evolving rapidly. Performing a meta-analysis of these advancements can provide valuable insights to clinicians and healthcare decision-makers and help identify gaps that need further research and development. We conducted a systematic review and network meta-analysis (NMA) comparing the diagnostic accuracy of three key OCT-derived parameters in identifying early glaucoma: peripapillary retinal nerve fiber layer (RNFL) thickness, macular metrics, and optic nerve head (ONH) characteristics. We systematically searched PubMed, Embase, Web of Science, and Scopus for studies published from January 2004 through March 2024, and identified 47 eligible studies. These studies comprised 12,723 eyes from 8177 participants, including patients with mild primary open-angle glaucoma, pre-perimetric glaucoma (PPG), and ocular hypertension, as well as healthy controls. Our NMA summarized the existing evidence on the diagnostic performance of these parameters. The highest diagnostic accuracies for glaucoma detection were observed for average and inferior RNFL parameters, both achieving an accuracy of 0.77 and macular GLV parameter with an accuracy of 0.76. These were followed by inferotemporal GCIPL and two ONH parameters-rim area and cup-to-disc ratio-each with an accuracy of 0.75. In conclusion, the overall diagnostic accuracy was comparable across all three categories of OCT parameters. The results also suggest the potential benefits of combining two or three of these parameters in a single report, along with the application of artificial intelligence. This approach could significantly enhance the diagnostic accuracy of OCT in detecting glaucoma at its earliest stages, ultimately improving patient outcomes through earlier intervention.
光学相干断层扫描(OCT)诊断技术越来越多地应用于临床实践,并且正在迅速发展。对这些进展进行荟萃分析可以为临床医生和医疗保健决策者提供有价值的见解,并有助于确定需要进一步研究和开发的差距。我们进行了一项系统综述和网络荟萃分析(NMA),比较了识别早期青光眼的三个关键oct来源参数的诊断准确性:乳头状周围视网膜神经纤维层(RNFL)厚度、黄斑指标和视神经头(ONH)特征。我们系统地检索了PubMed, Embase, Web of Science和Scopus从2004年1月到2024年3月发表的研究,并确定了47项符合条件的研究。这些研究包括来自8177名参与者的12723只眼睛,包括轻度原发性开角型青光眼、前周型青光眼(PPG)和高眼压患者,以及健康对照。我们的NMA总结了这些参数的诊断性能的现有证据。平均RNFL参数和较差RNFL参数的青光眼诊断准确率最高,均达到0.77,黄斑GLV参数的准确率为0.76。其次是颞下GCIPL和两个ONH参数-边缘面积和杯盘比-每一个精度为0.75。总之,在所有三类OCT参数中,总体诊断准确性是可比的。研究结果还表明,在一份报告中结合两个或三个参数,以及人工智能的应用,可能会带来潜在的好处。该方法可显著提高OCT在青光眼早期发现的诊断准确性,最终通过早期干预改善患者预后。