Evidence map›Paper›PMID 35029919›Full record

ArticleMedicine2022

Global and regional prevalence and burden for premenstrual syndrome and premenstrual dysphoric disorder: A study protocol for systematic review and meta-analysis.

Mingzhou Gao, Hao Zhang, Zhan Gao, Xunshu Cheng, Ya Sun, Mingqi Qiao, Dongmei Gao

Open access · goldAbstract read
In one paragraph

Article in Medicine, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
11citing papers in PubMed, 2 pooled it
4.0field-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

11 citing papers in PubMed, 2 syntheses or guidelines pooled it, 23 citations in OpenAlex.

  1. Pooled it
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  5. Review
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  10. Emerging Perspectives on the Impact of Diabetes Mellitus and Anti-Diabetic Drugs on Premenstrual Syndrome. A Narrative Review.Diabetes therapy : research, treatment and education of diabetes and related disorders · 2024
    Review
  11. 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

7 authors at 1 institution in 1 country.

Mingzhou GaoInnovation Research Institute of Traditional Chinese Medicine, Shandong University of Traditional Chinese Medicine, Jinan, Shandong Province, China.ORCID 0000-0003-1805-0754
Hao ZhangExperimental Center, Shandong University of Traditional Chinese Medicine, Jinan, Shandong Province, China.
Zhan GaoCollege of Traditional Chinese Medicine, Shandong University of Traditional Chinese Medicine, Jinan, Shandong Province, China.
Xunshu ChengCollege of Traditional Chinese Medicine, Shandong University of Traditional Chinese Medicine, Jinan, Shandong Province, China.
Ya SunInnovation Research Institute of Traditional Chinese Medicine, Shandong University of Traditional Chinese Medicine, Jinan, Shandong Province, China.
Mingqi QiaoCollege of Traditional Chinese Medicine, Shandong University of Traditional Chinese Medicine, Jinan, Shandong Province, China.
Dongmei GaoCollege of Traditional Chinese Medicine, Shandong University of Traditional Chinese Medicine, Jinan, Shandong Province, China.
Shandong University of Traditional Chinese Medicine · CN

Funding

20 articles for colleges and universities funded project in Jinan 2020GXRC002Key project of Natural Science Foundation of Shandong Province ZR2020ZD17National Natural Science Foundation of China 81001484; 81473558Natural Science Foundation of Shandong Province ZR202102270167Shandong Medical and Health Science and Technology Development Plan Project 202105010467
6 · The paper itself

Abstract

introductionPremenstrual syndrome (PMS) and premenstrual dysphoric disorder (PMDD) are becoming common mental diseases in women impairing daily functioning. Estimation of the epidemiological burden of PMS/PMDD can serve as scientific basis for prevention and management of premenstrual disorders. Herein, we firstly provide a protocol to perform estimation on the prevalence and risk factors for PMS/PMDD in the general population globally and regionally. METHODS/

designThe PubMed, Web of Science, Chinese National Knowledge Infrastructure, the Cochrane Central Register of Controlled Trials (Cochrane Library), Chinese VIP Information, EMBASE, Wanfang Database, as well as the Chinese Biomedical Literature Database will be queried to find related studies containing information on the prevalence of PMDD (2011-2021). Two independent reviewers will comb the literature and abstract the data characteristics. Disparities will be reconciled via consents. The primary outcome will be the global prevalence. The random-effect model will be employed to pool the assessments. The standard χ2 tests, as well as the I2 statistic will be used to determine heterogeneity. Furthermore, the meta-regression analysis will be employed to estimate the differences in study-level characteristics. All the statistical analyses will be carried out in the software Stata v 15.0 (Stata Corporation, College Station, TX), as well as the R (v R 3.5.1, R Foundation for Statistical Computing, Vienna, Austria) software. DISCUSSION: Based on existing evidence, our study will offer a high-quality synthesis for global and regional prevalence, burden, and risk factors of PMS/PMDD. Effective strategies will be made for prevention and management of epidemiological burden on the PMS/PMDD, even premenstrual disorders. ETHICS AND DISSEMINATION: This study does not involve the specific patients, and all research data comes from publicly available professional literature, so an ethics committee is not required to conduct an ethical review and approval of the study. INPLASY REGISTRATION NUMBER: INPLASY2021120065.

Indexed as

FemaleHumansMeta-Analysis as TopicPremenstrual Dysphoric DisorderPremenstrual SyndromePrevalenceSystematic Reviews as Topic

Identifiers

PMID35029919
PMCPMC8735714
OpenAlexW4206815462

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.