ArticleFrontiers in public health2025
Depression symptoms in perimenopausal women with somatic pain: nomogram construction based on a logistic regression model.
Article in Frontiers in public health, 2025. 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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4 citing papers in PubMed.
- Construction and validation of a machine learning model for predicting urine culture positivity in children with suspected urinary tract infections.Annals of medicine · 2026Article
- Proactive health management and psychological distress among perimenopausal women: A cross-sectional latent profile and mediation analysis.Scientific reports · 2026Article
- Multimodal machine learning for menopause status prediction using LLM-extracted ultrasound features.Frontiers in endocrinology · 2026Article
- Predicting ICU Readmission in Patients With Cerebral Infarction: A Machine Learning Approach Using Neurophysiological and Clinical Data.Brain and behavior · 2025Article
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Abstract
Objective: This study investigated the factors influencing depressive symptoms in women with somatic pain during the perimenopausal period in China and established and validated a nomogram prediction model. Methods: The predictive model is based on data from the China Health and Retirement Longitudinal Study (CHARLS), which focused on individuals aged 45-59 years with somatic pain during the perimenopausal period. The study utilized participants from the CHARLS 2018 wave, 30 factors including individual characteristics, health behaviors, living environment, family economic status, and social participation, were analyzed in this study. To ensure the model's reliability, the study cohort was randomly split into a training set (80%) and a validation set (20%). The Results: In total, 2,265 perimenopausal women were included in the final analysis, of whom 1,402 (61.90%) experienced somatic pain. Multifactorial logistic regression identified marital status, pain distress, self-perceived general health, activities of daily living (ADL), sleep deprivation, life satisfaction, and air quality satisfaction, as predictive risk factors for perimenopausal women with somatic pain. The predictive model achieved an AUC of 0.7010 (95% Conclusion: The nomogram constructed in this study can be used to identify the factors related to depression in women with perimenopausal somatic pain.
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