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ORIGINAL RESEARCH article
Front. Neurol.
Sec. Headache and Neurogenic Pain
Volume 16 - 2025 |
doi: 10.3389/fneur.2025.1511252
Development and Validation of a Diagnostic Model for Migraine Without Aura in Inpatients
Provisionally accepted- Air Force Medical University, Xi'an, China
Objectives: This study aimed to develop and validate a robust predictive model for accurately identifying migraine without aura (MWoA) individuals from migraine patients.We recruited 637 migraine patients, randomizing them into training and validation cohorts. Participant's medical data were collected such as demographic data (age, gender, selfreported headache characteristics) and clinical details including symptoms, triggers, and comorbidities. The model stability, which was developed using multivariable logistic regression, was tested by the internal validation cohort. Model efficacy was evaluated using the area under the receiver operating characteristic curve (AUC), alongside with nomogram, calibration curve, and decision curve analysis (DCA).The study included 477 females (average age 46.62 ± 15.64) and 160 males (average age 39.78 ± 19.53). A total of 397 individuals met the criteria for MWoA. Key predictors in the regression model included patent foramen ovale (PFO) (OR=2.30, P=0.01), blurred vision (OR=0.40, P=0.001), dizziness (OR=0.16, P<0.01), and anxiety/depression (OR=0.41, P=0.02).Common symptoms like nausea (OR=0.79, P=0.43) and vomiting (OR=0.64, P=0.17) were not statistically significant predictors for MWoA. The AUC values were 79.1% and 82.8% in the training and validation cohorts, respectively, with good calibration in both.The predictive model developed and validated in this study demonstrates significant efficacy in identifying MWoA. Our findings highlight PFO as a potential key risk factor, underscoring its importance for early prevention, screening, and diagnosis of MWoA.
Keywords: Migraine, Migraine without Aura, logistic regression model, diagnosis, patent foramen ovale
Received: 22 Oct 2024; Accepted: 06 Jan 2025.
Copyright: © 2025 Chen, Yang, Zhang, Su, Li, Shang, Zhang and Wang. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
* Correspondence:
Chi Zhang, Air Force Medical University, Xi'an, China
Dan Su, Air Force Medical University, Xi'an, China
Yuxuan Shang, Air Force Medical University, Xi'an, China
Wei Zhang, Air Force Medical University, Xi'an, China
Wen Wang, Air Force Medical University, Xi'an, China
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