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昼夜节律紊乱与多囊卵巢综合征:一项系统评价与荟萃分析。

Circadian rhythm disruption and polycystic ovary syndrome: a systematic review and meta-analysis.

作者信息

Heydari Tara, Ramdass Prakash V A K

机构信息

Department of Public Health and Preventive Medicine (Heydari, and Ramdass), School of Medicine, St. George's University, St. George's, Grenada.

出版信息

AJOG Glob Rep. 2025 Mar 20;5(2):100479. doi: 10.1016/j.xagr.2025.100479. eCollection 2025 May.

DOI:10.1016/j.xagr.2025.100479
PMID:40292350
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC12032313/
Abstract

OBJECTIVE

The aim of our systematic review and meta-analysis was to determine if circadian rhythm disruption (CRD) is associated with polycystic ovary syndrome (PCOS). Our objective was to pool the overall mean differences in biomarkers of CRD (including melatonin levels, morning and evening cortisol levels, and sleep efficiency) between PCOS patients and controls. We hypothesized that CRD will be more prominent in patients with PCOS.

DATA SOURCES

A systematic search of PubMed, Scopus, Embase, ClinicalTrials.Gov, and the Cochrane Database of Systematic Reviews was conducted from inception until 2024 using the following MeSH terms "circadian rhythm" OR "sleep disturbance" OR "melatonin" AND "polycystic ovary syndrome." Citation search supplemented the systematic database search.

STUDY ELIGIBILITY CRITERIA

Inclusion criteria were women with PCOS, original case-control, cross-sectional, and cohort studies that identify parameters of CRD (melatonin, cortisol, and sleep disturbance). Exclusion criteria were women with endocrine and metabolic co-morbidities, menopausal women, case reports, review studies, animal studies, abstracts, and conference presentations. There was no time restriction for year of publication.

STUDY APPRAISAL AND SYNTHESIS METHODS

Two investigators (T.H. and P.R.) assessed the quality of the studies included using the Newcastle-Ottawa Scale. Forest plots were created using the Open Meta Analyst software. Publication bias was assessed in Egger's and Begg's tests.

RESULTS

A total of 16 studies were included in the systematic review and 12 studies were included in the meta-analysis (N=1,100 women [531 PCOS patients and 569 controls]). Pooled analysis showed that the mean difference in melatonin levels between PCOS patients and controls was 14.294 pg/mL, 95% CI [6.895, 21.693]. The overall mean difference in morning and evening cortisol between PCOS patients and controls was 1.103 pg/mL, 95% CI [-1.058, 3.265], and 3.574 pg/mL, 95% CI [1.741, 5.407], respectively. Pooled difference in mean sleep efficiency scores between PCOS patients and controls was -4.059, 95% CI [-6.752, -1.366]. Risk of bias assessment showed that NOS scores ranged from 7 to 9.

CONCLUSIONS

Our meta-analysis provides evidence that circadian rhythm disruption is positively associated with polycystic ovary syndrome. This is substantiated by differences in parameters indicative of circadian rhythm disruption, including melatonin levels, evening cortisol, and sleep efficiency.

摘要

目的

我们进行系统评价和荟萃分析的目的是确定昼夜节律紊乱(CRD)是否与多囊卵巢综合征(PCOS)相关。我们的目标是汇总PCOS患者与对照组之间CRD生物标志物(包括褪黑素水平、早晚皮质醇水平和睡眠效率)的总体平均差异。我们假设CRD在PCOS患者中会更明显。

数据来源

从数据库建立至2024年,使用以下医学主题词在PubMed、Scopus、Embase、ClinicalTrials.Gov和Cochrane系统评价数据库中进行了系统检索:“昼夜节律”或“睡眠障碍”或“褪黑素”以及“多囊卵巢综合征”。引用文献检索对系统数据库检索起到了补充作用。

研究纳入标准

纳入标准为患有PCOS的女性、确定CRD参数(褪黑素、皮质醇和睡眠障碍)的原始病例对照研究、横断面研究和队列研究。排除标准为患有内分泌和代谢合并症的女性、绝经后女性、病例报告、综述研究、动物研究、摘要和会议报告。对发表年份没有时间限制。

研究评估与综合方法

两名研究人员(T.H.和P.R.)使用纽卡斯尔-渥太华量表评估纳入研究的质量。使用Open Meta Analyst软件绘制森林图。在Egger检验和Begg检验中评估发表偏倚。

结果

系统评价共纳入16项研究,荟萃分析纳入12项研究(N = 1100名女性[531名PCOS患者和569名对照])。汇总分析显示,PCOS患者与对照组之间褪黑素水平的平均差异为14.294 pg/mL,95%可信区间[6.895, 21.693]。PCOS患者与对照组之间早晨和晚上皮质醇的总体平均差异分别为1.103 pg/mL,95%可信区间[-1.058, 3.265],以及3.574 pg/mL,95%可信区间[1.741, 5.407]。PCOS患者与对照组之间平均睡眠效率得分的汇总差异为-4.059,95%可信区间[-6.752, -1.366]。偏倚风险评估显示,NOS评分范围为7至9。

结论

我们的荟萃分析提供了证据,表明昼夜节律紊乱与多囊卵巢综合征呈正相关。这通过指示昼夜节律紊乱的参数差异得到证实,这些参数包括褪黑素水平、晚上皮质醇和睡眠效率。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/28aa/12032313/aaecb7270184/gr6.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/28aa/12032313/ce58955f866c/gr1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/28aa/12032313/0b9b878296e3/gr2.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/28aa/12032313/3b380c9531f5/gr3.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/28aa/12032313/1b0e625fa87a/gr4.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/28aa/12032313/533ebecf161b/gr5.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/28aa/12032313/aaecb7270184/gr6.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/28aa/12032313/ce58955f866c/gr1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/28aa/12032313/0b9b878296e3/gr2.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/28aa/12032313/3b380c9531f5/gr3.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/28aa/12032313/1b0e625fa87a/gr4.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/28aa/12032313/533ebecf161b/gr5.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/28aa/12032313/aaecb7270184/gr6.jpg

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