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基于机器学习算法的输卵管糖蛋白1（OVGP1）诊断多囊卵巢综合征（PCOS）

Oviduct Glycoprotein 1 (OVGP1) Diagnoses Polycystic Ovary Syndrome (PCOS) Based on Machine Learning Algorithms.

作者信息

Wang Fengjuan, Liu Xinran, Hao Xiaoyan, Wang Jing, Liu Jiayun, Bai Congxia

机构信息

Department of Clinical Laboratory Medicine, Xijing Hospital, Fourth Military Medical University (Air Force Military Medical University), Xi'an 710032, China.

出版信息

ACS Omega. 2024 Dec 3;9(50):49054-49063. doi: 10.1021/acsomega.4c03111. eCollection 2024 Dec 17.

DOI:10.1021/acsomega.4c03111
PMID:39713694
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC11656370/
Abstract

: To investigate the diagnostic value of oviduct glycoprotein 1 (OVGP1) levels for polycystic ovary syndrome (PCOS). : Serum OVGP1 concentrations were measured by enzyme-linked immunosorbent assay (ELISA). Associations between OVGP1 and endocrine parameters were evaluated by Spearman's correlation analysis. Diagnostic capacity was assessed by utilizing machine learning algorithms and receiver operating characteristic (ROC) curves. : OVGP1 levels were significantly decreased in PCOS patients and correlated with the serum follicle-stimulating hormone (FSH) concentration and the luteinizing hormone/follicle-stimulating hormone (LH/FSH) ratio, which are predictors of PCOS occurrence. The diagnostic value of OVGP1 combined with six signatures (LH/FSH, progesterone, total cholesterol, triglyceride, high-density lipoprotein cholesterol, and anti-Müllerian hormone) or three clinical indicators has the potential to significantly improve the accuracy of diagnosing PCOS patients. : OVGP1 enhances the ability to diagnose when combined with clinical indicators.

摘要

: 探讨输卵管糖蛋白1（OVGP1）水平对多囊卵巢综合征（PCOS）的诊断价值。: 采用酶联免疫吸附测定（ELISA）法检测血清OVGP1浓度。通过Spearman相关分析评估OVGP1与内分泌参数之间的关联。利用机器学习算法和受试者工作特征（ROC）曲线评估诊断能力。: PCOS患者的OVGP1水平显著降低，且与血清促卵泡生成素（FSH）浓度以及黄体生成素/促卵泡生成素（LH/FSH）比值相关，这两者是PCOS发生的预测指标。OVGP1与六个特征（LH/FSH、孕酮、总胆固醇、甘油三酯、高密度脂蛋白胆固醇和抗苗勒管激素）或三个临床指标联合的诊断价值有可能显著提高诊断PCOS患者的准确性。: OVGP1与临床指标联合时可提高诊断能力。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3b88/11656370/ee463ee65b44/ao4c03111_0004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3b88/11656370/2aa8e3c40458/ao4c03111_0001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3b88/11656370/67724802b827/ao4c03111_0002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3b88/11656370/7db44bf09b6e/ao4c03111_0003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3b88/11656370/ee463ee65b44/ao4c03111_0004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3b88/11656370/2aa8e3c40458/ao4c03111_0001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3b88/11656370/67724802b827/ao4c03111_0002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3b88/11656370/7db44bf09b6e/ao4c03111_0003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3b88/11656370/ee463ee65b44/ao4c03111_0004.jpg

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