Evidence map›Paper›PMID 37568475›Full record

ArticleJournal of clinical medicine2023

Metabolic Syndrome Rather Than Other Phenotypes in PCOS as a Predictive Indicator for Clinical Outcomes in IVF: Comprehensive Phenotypic Assessment across All PCOS Classifications.

Manfei Si, Wanxue Xu, Xinyu Qi, Huahua Jiang, Yue Zhao, Rong Li, Xiaoyu Long, Jie Qiao

Open access · goldAbstract read
In one paragraph

Article in Journal of clinical medicine, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
9citing papers in PubMed, 1 pooled it
4.1field-weighted citation impact, top 6% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

9 citing papers in PubMed, 1 synthesis or guideline pooled it, 15 citations in OpenAlex.

  1. Pooled it
  2. Trial
  3. Review
  4. Observational
  5. Article
  6. Article
  7. Article
  8. Article
  9. Review
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

8 authors at 1 institution in 1 country.

Manfei SiCenter for Reproductive Medicine, Department of Obstetrics and Gynecology, Peking University Third Hospital, Beijing 100191, China.
Wanxue XuCenter for Reproductive Medicine, Department of Obstetrics and Gynecology, Peking University Third Hospital, Beijing 100191, China.ORCID 0000-0003-4720-2841
Xinyu QiCenter for Reproductive Medicine, Department of Obstetrics and Gynecology, Peking University Third Hospital, Beijing 100191, China.
Huahua JiangCenter for Reproductive Medicine, Department of Obstetrics and Gynecology, Peking University Third Hospital, Beijing 100191, China.
Yue ZhaoCenter for Reproductive Medicine, Department of Obstetrics and Gynecology, Peking University Third Hospital, Beijing 100191, China.
Rong LiCenter for Reproductive Medicine, Department of Obstetrics and Gynecology, Peking University Third Hospital, Beijing 100191, China.
Xiaoyu LongCenter for Reproductive Medicine, Department of Obstetrics and Gynecology, Peking University Third Hospital, Beijing 100191, China.
Jie QiaoCenter for Reproductive Medicine, Department of Obstetrics and Gynecology, Peking University Third Hospital, Beijing 100191, China.
Peking University · CN

Funding

China Postdoctoral Science Foundation 2021M690256National Key Research and Development Program of China 2022YFC2702901National Natural Science Foundation of China 81701407
6 · The paper itself

Abstract

Polycystic ovary syndrome (PCOS) is a well-recognized, multi-system metabolic disorder affecting fertility. Although various classification methods have been proposed to assess the phenotypic heterogeneity of PCOS, there is currently no reliable phenotype for predicting clinical IVF outcomes. This retrospective study, as a comprehensive phenotypic assessment across all PCOS classifications, aimed to identify dependable phenotypes that can serve as predictors for IVF and pregnancy outcomes. The study included 1313 PCOS patients who received their initial IVF treatment between January 2019 and December 2021. The phenotypes reflect the diverse metabolic and hormonal characteristics in this study. Phenotype A, within the Rotterdam criteria classification, exhibited the highest anti-Müllerian hormone levels (AMH), while phenotype D displayed the lowest Homeostasis Model Assessment of Insulin Resistance (HOMA-IR) values. Both the hyperandrogenism (HA) phenotype within HA-based classification and the overweight phenotype within the body-mass-index-based classification showed increased HOMA-IR and metabolic syndrome (MetS). The MetS phenotype had higher free androgen index and a lower AMH. Notably, the MetS-based classification system demonstrated an independent association of MetS with cumulative live birth, preterm birth, and gestational diabetes mellitus as a contributing risk factor for PCOS patients undergoing IVF (

Indexed as

clinical outcomesin vitro fertilizationmetabolic syndromephenotypespolycystic ovary syndrome

Identifiers

PMID37568475
PMCPMC10420246
OpenAlexW4385498029

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.