Analysis of dysmenorrhea-related factors in adenomyosis and development of a risk prediction model

被引:0
|
作者
Fu, Yudan [1 ]
Wang, Xin [1 ]
Yang, Xinchun [1 ]
Zhao, Ruihua [1 ]
机构
[1] Chinese Acad Chinese Med Sci, Guang Anmen Hosp, Dept Gynecol, 5 North Line Ge St, Beijing 10053, Peoples R China
关键词
Adenomyosis; Dysmenorrhea; Related factors; Logistic; Clinical prediction model; ENDOMETRIOSIS; SYMPTOMS; SEVERITY; STRESS; WOMEN;
D O I
10.1007/s00404-025-07967-y
中图分类号
R71 [妇产科学];
学科分类号
100211 ;
摘要
Objective To explore factors related to dysmenorrhea in adenomyosis and construct a risk prediction model. Methods A cross-sectional survey involving 1636 adenomyosis patients from 37 hospitals nationwide (November 2019-February 2022) was conducted. Data on demographics, disease history, menstrual and reproductive history, and treatment history was collected. Patients were categorized into dysmenorrhea and non-dysmenorrhea groups. Multivariate logistic regression analyzed factors influencing dysmenorrhea, and a risk prediction model was created using a nomogram. The model's performance was evaluated through ROC curve analysis, C-index, Hosmer-Lemeshow test, and bootstrap method The nomogram function was used to establish a nomogram model. The model was evaluated using the area under the ROC curve (AUC), C-index, Hosmer-Lemeshow goodness-of-fit test, and bootstrap method. Patients were scored based on the nomogram, and high-risk groups were delineated. Results Dysmenorrhea was present in 61.31% (1003/1636) of the patients. Univariate analysis showed significant differences (P < 0.05) between groups in age at onset, course of disease, oligomenorrhea, menorrhagia, number of deliveries, pelvic inflammatory disease, family history of adenomyosis, exercise, and excessive menstrual fatigue. Significant factors included menorrhagia, multiple deliveries, pelvic inflammatory disease, and family history of adenomyosis as risk factors. Older age at onset, oligomenorrhea, and exercise were identified as protective factors. The model's accuracy, discrimination, and reliability were acceptable, and a risk score > 88.5 points indicated a high-risk group. Conclusion Dysmenorrhea is prevalent among adenomyosis patients. Identifying and mitigating risk factors, while leveraging protective factors, can aid in prevention and management. The developed model effectively predicts dysmenorrhea risk, facilitating early intervention and treatment.
引用
收藏
页码:1081 / 1089
页数:9
相关论文
共 50 条
  • [1] Development of a clinical prediction model for diagnosing adenomyosis
    Tellum, Tina
    Nygaard, Staale
    Skovholt, Else K.
    Qvigstad, Erik
    Lieng, Marit
    FERTILITY AND STERILITY, 2018, 110 (05) : 957 - +
  • [2] Dysmenorrhea-Related Impact on Functioning Scale: Development and Measurement Properties for Cisgender Women and Transgender Men
    Arruda, Guilherme T.
    Silva, Maria Eduarda C. B. da
    da Silva, Barbara I.
    Driusso, Patricia
    Avila, Mariana A.
    VALUE IN HEALTH, 2025, 28 (01) : 99 - 107
  • [3] Breast cancer-related lymphoedema: Risk factors and prediction model
    Martinez-Jaimez, Patricia
    Armora Verdu, Miriam
    Forero, Carlos G.
    Alvarez Salazar, Samantha
    Fuster Linares, Pilar
    Monforte-Royo, Cristina
    Masia, Jaume
    JOURNAL OF ADVANCED NURSING, 2022, 78 (03) : 765 - 775
  • [4] Analysis of related factors influencing postoperative recurrence of adenomyosis treated with HIFU
    Fan, Ling-xiu
    Zhang, Ying
    Yang, Lei-lei
    Ji, Xiao-li
    Wang, Yan
    Huang, Ye-fang
    Shi, Ling
    Wen, Yi
    ARCHIVES OF GYNECOLOGY AND OBSTETRICS, 2024, 309 (05) : 1765 - 1773
  • [5] Analysis of related factors influencing postoperative recurrence of adenomyosis treated with HIFU
    Ling-xiu Fan
    Ying Zhang
    Lei-lei Yang
    Xiao-li Ji
    Yan Wang
    Ye-fang Huang
    Ling Shi
    Yi Wen
    Archives of Gynecology and Obstetrics, 2024, 309 : 1765 - 1773
  • [6] Assessment of Risk Factors Associated with Severe Endometriosis and Establishment of Preoperative Prediction Model
    Yang, Yanhua
    Li, Jing
    Chen, Hui
    Feng, Weiwei
    DIAGNOSTICS, 2022, 12 (10)
  • [7] Prevalence and Risk Factors of Primary Dysmenorrhea in Students: A Meta-Analysis
    Wang, Liwen
    Yan, Yuhan
    Qiu, Huiyu
    Xu, Datong
    Zhu, Jiaqi
    Liu, Jing
    Li, Hui
    VALUE IN HEALTH, 2022, 25 (10) : 1678 - 1684
  • [8] Development of a Risk Prediction Model to Individualize Risk Factors for Surgical Site Infection After Mastectomy
    Olsen, Margaret A.
    Nickel, Katelin B.
    Margenthaler, Julie A.
    Fox, Ida K.
    Ball, Kelly E.
    Mines, Daniel
    Wallace, Anna E.
    Colditz, Graham A.
    Fraser, Victoria J.
    ANNALS OF SURGICAL ONCOLOGY, 2016, 23 (08) : 2471 - 2479
  • [9] Factors Related to Primary Dysmenorrhea in Turkish Women: a Multiple Multinomial Logistic Regression Analysis
    Cinar, Gamze Nalan
    Akbayrak, Turkan
    Gursen, Ceren
    Baran, Emine
    Uzelpasaci, Esra
    Nakip, Gulbala
    Bozdag, Gurkan
    Beksac, Mehmet Sinan
    Ozgul, Serap
    REPRODUCTIVE SCIENCES, 2021, 28 (02) : 381 - 392
  • [10] Factors Related to Primary Dysmenorrhea in Turkish Women: a Multiple Multinomial Logistic Regression Analysis
    Gamze Nalan Çinar
    Türkan Akbayrak
    Ceren Gürşen
    Emine Baran
    Esra Üzelpasacı
    Gülbala Nakip
    Gürkan Bozdağ
    Mehmet Sinan Beksaç
    Serap Özgül
    Reproductive Sciences, 2021, 28 : 381 - 392