Evidence map›Paper›PMID 38317119›Full record

ArticleBMC public health2024

Dysmenorrhea pattern in adolescences informing adult endometriosis.

Yu Dai, Huangjin Luo, Litong Zhu, Weichun Yang, Haishan Xiang, Qiuling Shi, Ping Jin

Abstract read
In one paragraph

Article in BMC public health, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
13citing papers in PubMed, 1 pooled it
–field-weighted citation impact
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

13 citing papers in PubMed, 1 synthesis or guideline pooled it.

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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.

Yu DaiDepartment of Gynecology, Shenzhen Maternity and Child Healthcare Hospital, Shenzhen, Guangdong, People's Republic of China.
Huangjin LuoDepartment of Gynecology, Shengli Clinical Medical College of Fujian Medical University, Fujian Provincial Hospital, Fuzhou, Fujian, People's Republic of China.
Litong ZhuDepartment of Gynecology, Shenzhen Maternity and Child Healthcare Hospital, Shenzhen, Guangdong, People's Republic of China.
Weichun YangDepartment of Gynecology, Shenzhen Maternity and Child Healthcare Hospital, Shenzhen, Guangdong, People's Republic of China.
Haishan XiangDepartment of Gynecology, Shenzhen Maternity and Child Healthcare Hospital, Shenzhen, Guangdong, People's Republic of China.
Qiuling ShiState Key Laboratory of Ultrasound in Medicine and Engineering, College of Biomedical Engineering, Chongqing Medical University, Chongqing, People's Republic of China. qshi@cqmu.edu.cn.
Ping JinDepartment of Gynecology, Shenzhen Maternity and Child Healthcare Hospital, Shenzhen, Guangdong, People's Republic of China. pingjin66@126.com.

Funding

Chongqing science and Technology Bureau 2021KFKT030Medical Scientific Research Foundation of Guangdong Province, China A2023223
6 · The paper itself

Abstract

backgroundEndometriosis (EMs) is a chronic and progressive disease that, if diagnosed late, can lead to infertility and deep infiltrating endometriosis (DIE). Dysmenorrhea is the most prominent symptom of EMs. However, limited research exists on the specific correlation between dysmenorrhea patterns and EMs. Early prevention of EMs is essential to effectively manage the progression of the disease, and is best detected during adolescence. Our objective was to associate the development of EMs with dysmenorrhea patterns during adolescence and quantify the risk of adult EMs for adolescent girls, with the aim of supporting primary intervention strategy planning.

methodsThis case-control study examined predictors for adult EMs based on dysmenorrhea patterns in adolescents. We collected 1,287 cases of 641 EMs and 646 healthy females regarding their basic demographic information, adolescent menstrual characteristics, adolescent dysmenorrheal patterns, and adolescent lifestyles. Age-matching (1-to-1) was employed to control for the confounding effect of age between the groups. Least Absolute Shrinkage and Selection Operator (LASSO) and logistic regression models were utilized to identify predictors for adult EMs. The predictive value of the model was evaluated using the area under the receiver operating characteristic curve (AUC) and the C-index, while Hosmer-Lemeshow Test assessed the goodness of fit of the model. Data from one additional cohort in Shenzhen hospitalized with EMs were used to external validation were analyzed.

resultsIndividuals who always experienced dysmenorrhea had a risk of adult endometriosis 18.874 (OR = 18.874; 95%CI = 10.309-34.555) times higher than those occasional dysmenorrhea, The risk of developing EMs was 5.257 times higher in those who experienced dysmenorrhea more than 12 months after menarche than in those who experienced dysmenorrhea less than 6 months after menarche (OR = 5.257, 95% CI = 3.343-8.266), AUC in the external validation cohort was 0.794(95%CI: 0.741-0.847). We further found that high-intensity physical activity and sun-sensitive skin of burning were influential factors in high-frequency dysmenorrhea. The AUC value for the internal evaluation of the model was 0.812 and the AUC value for the external validation was 0.794.

conclusionOur findings revealed that the frequency of dysmenorrhea during adolescence contributed to the development of adult endometriosis. The frequency and onset of dysmenorrhea in adolescence were promising predictors for adult EMs. Both internal and external validation proved the model's good predictive ability.

trial registrationhttp://www.chictr.org.cn/ , TRN: ChicTR2200060429, date of registration: 2022/06/01, retrospectively registered.

Indexed as

EndometriosisAdolescentAdultCase-Control StudiesDysmenorrheaFemaleHumansMenarcheMenstruationAdolescenceDysmenorrhea patternEndometriosisPredictor

Identifiers

PMID38317119
PMCPMC10840152

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Registered trials

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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.