相关实验视频

Updated: May 5, 2026

Single-cell Analysis of Immunophenotype and Cytokine Production in Peripheral Whole Blood via Mass Cytometry

Single-cell Analysis of Immunophenotype and Cytokine Production in Peripheral Whole Blood via Mass Cytometry

Published on: June 26, 2018

PCOS表型和血液学免疫-炎症指数:一个比较性评估

Aykut Kından¹, Goncagül Kından², Çağanay Soysal³

¹Department of Obstetrics and Gynecology, Pursaklar State Hospital, Ankara, Turkey.

Journal of reproductive immunology

|December 18, 2025

概括

像系统性免疫炎症指数 (SII) 这样的血液免疫炎症指数可以帮助区分多囊性卵巢综合征 (PCOS) 表型. SII显示了最高的准确性,表明其作为PCOS诊断生物标志物的潜力.

科学领域:

内分泌学和免疫学.
生殖医学生殖医学

背景情况:

多囊卵巢综合征 (PCOS) 是一种复杂的内分泌疾病,具有多种表型.
血液免疫炎症指数越来越多地被认为是它们在各种炎症状况中的潜在作用.

研究的目的:

在PCOS表型之间研究血液免疫-炎症指数的差异.
评估这些指数作为PCOS表型生物标志物的诊断潜力.

主要方法:

对89名患有PCOS的女性进行了回顾性横截面研究,分为四种表型 (A-D).
对人口,人类,生殖,生化和荷尔蒙数据的分析.
使用统计测试计算和比较不同表型的血液学指数 (NLR,MLR,SII,PLR).
后勤回归和ROC分析以确定预测生物标志物.

主要成果:

现型A显示显著更高的BMI,腰围,葡萄糖,胰岛素和HOMA-IR.
中性粒细胞与淋巴细胞的比率 (NLR),单细胞与淋巴细胞的比率 (MLR) 和全身免疫炎症指数 (SII) 在各类表型之间有显著差异.
SII表现出最高的区分能力 (AUC=0.822),NLR和MLR显示中等的预测值.
NLR和SII与总和自由雄激素指数 (FAI) 有正相关,与SHBG和HDL胆固醇有负相关.

结论:

血液学免疫炎症指数,特别是SII,可以有效地区分PCOS表型.
SII,NLR和MLR显示出作为PCOS表型化可访问和成本效益的生物标志物的潜力.
确定了BMI,SII和LH/FSH比率作为特定PCOS表型的独立预测因素.

关键词:

炎症指数炎症指数现象类型现象类型多囊性卵巢综合征多囊性卵巢综合征系统性免疫-炎症指数

更多相关视频

A Hyperandrogenic Mouse Model to Study Polycystic Ovary Syndrome

A Hyperandrogenic Mouse Model to Study Polycystic Ovary Syndrome

Published on: October 2, 2018

Evaluation of Hepatic Glucose Production in a Polycystic Ovary Syndrome Mouse Model

Evaluation of Hepatic Glucose Production in a Polycystic Ovary Syndrome Mouse Model

Published on: March 5, 2022

相关概念视频

Receiver Operating Characteristic Plot

Receiver Operating Characteristic Plot

A ROC (Receiver Operating Characteristic) plot is a graphical tool used to assess the performance of a binary classification model by illustrating the trade-off between sensitivity (true positive rate) and specificity (false positive rate). By plotting sensitivity against 1 - specificity across various threshold settings, the ROC curve shows how well the model distinguishes between classes, with a curve closer to the top-left corner indicating a more accurate model. The area under the ROC curve...