External quality assessment for molecular detection of Ureaplasma urealyticum in China

外部质量评估 解脲支原体 核酸扩增试验 医学 检出限 高分辨率 生物 色谱法 微生物学 妇科 化学 病理 支原体 遥感 地质学 沙眼衣原体
作者
Yanxi Han,Jian Jiang,Yu Ma,Yuqing Chen,Zhenli Diao,Tao Huang,Jing Li,Wanyu Feng,Ziqiang Li,Jinming Li,Rui Zhang
出处
期刊:Clinica Chimica Acta [Elsevier]
卷期号:557: 117864-117864
标识
DOI:10.1016/j.cca.2024.117864
摘要

A pilot external quality assessment (EQA) scheme for molecular detection of Ureaplasma urealyticum (UU) was conducted by the National Center for Clinical Laboratories (NCCL) to evaluate the testing capabilities of clinical laboratories and the actual performance of DNA-based nucleic acid amplification tests (NAAT) and RNA-based NAATs when applied in clinical settings.The EQA panel contained twelve lyophilized samples, including positive samples containing inactivated cell culture supernatants of UU at different concentrations and sterile saline for negative samples. The positive samples were further divided into three groups of high, moderate and low concentrations. The panels were distributed to the participants and the datasets were analyzed according to the qualitative results.A total of 365 laboratories participated in the EQA scheme, and 360 results submitted by 338 laboratories were collected, of which 96.11 % (346/360) of the returned results and 95.86 % (324/338) of the laboratories were deemed competent. The positive percentage agreement (PPA) was ≥ 97.5 % for high and moderate concentration samples, but varied significantly for low concentration samples, decreasing from 86.94 % to 51.94 % as the sample concentration decreased. Additionally, for low concentration samples, RNA-based NAAT showed higher PPAs than DNA-based NAATs, but these results were specific to UU supernatants used in this study.Most of UU detection assays employed by the participants were generally consistent with their estimated limit of detection (LOD), and the majority of participants can reliably detect UU samples with high and moderate concentrations, while the poor analytical performance for low concentration samples requires further improvement and optimization.

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