ArticleTrials2020
Improving the accuracy and efficacy of diagnosing polycystic ovary syndrome by integrating metabolomics with clinical characteristics: study protocol for a randomized controlled trial.
Article in Trials, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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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.
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.
Who cites it
4 citing papers in PubMed.
- Exploring the Intersection of Artificial Intelligence and Clinical Healthcare: A Multidisciplinary Review.Diagnostics (Basel, Switzerland) · 2023Review
- Article
- Metabolomic Biomarkers in Gestational Diabetes Mellitus: A Review of the Evidence.International journal of molecular sciences · 2021Review
- Prediction of Gut Microbial Community Structure and Function in Polycystic Ovary Syndrome With High Low-Density Lipoprotein Cholesterol.Frontiers in cellular and infection microbiology · 2021Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
13 authors.
Funding
Abstract
backgroundPolycystic ovary syndrome (PCOS) is a complex endocrine syndrome with poorly understood mechanisms. To provide patients with PCOS with individualized therapy, it is critical to precisely diagnose the phenotypes of the disease. However, the criteria for diagnosing the different phenotypes are mostly based on symptoms, physical examination and laboratory results. This study aims to compare the accuracy and efficacy of diagnosing PCOS by integrating metabolomic markers with common clinical characteristics.
methodsThis is a prospective, multicenter, analyst-blinded, randomized controlled trial. Participants will be grouped into (1) people without PCOS (healthy control group), (2) patients diagnosed with PCOS based on clinical indices (experimental group 1), and (3) patients diagnosed with PCOS based on metabolomic indices (experimental group 2). A total of 276 participants, including 60 healthy people and 216 patients with PCOS, will be recruited. The 216 patients with PCOS will be randomly assigned to the two experimental groups in a 1:1 ratio, and each group will receive a different 6-month treatment. The primary outcome for the experimental groups will be the effect of PCOS treatment. DISCUSSION: The results of this trial should help to determine whether using metabolomic indices is more accurate and effective than using clinical characteristics in diagnosing the phenotypes of PCOS. The results could provide a solid foundation for the accurate diagnosis of different PCOS subgroups and for future research on individualized PCOS therapy.
trial registrationChinese Clinical Trial Registry, ID: ChiCTR-INR-1800016346. Registered 26 May 2018.
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