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Differential Diagnostic Models Between Vasovagal Syncope and Psychogenic Pseudosyncope in Children

Objective: We aimed to establish useful models for the clinical differential diagnosis between vasovagal syncope (VVS) and psychogenic pseudosyncope (PPS). Methods: This bicentric study included 176 patients (150 VVS and 26 PPS cases) for model development. Based on the results of univariate and mul...

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Detalles Bibliográficos
Autores principales: Zhang, Zhening, Jiang, Xingyuan, Han, Lu, Chen, Selena, Tao, Ling, Tao, Chunyan, Tian, Hong, Du, Junbao
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6989585/
https://www.ncbi.nlm.nih.gov/pubmed/32038462
http://dx.doi.org/10.3389/fneur.2019.01392
Descripción
Sumario:Objective: We aimed to establish useful models for the clinical differential diagnosis between vasovagal syncope (VVS) and psychogenic pseudosyncope (PPS). Methods: This bicentric study included 176 patients (150 VVS and 26 PPS cases) for model development. Based on the results of univariate and multivariate analyses, a logistic regression model and a scoring model were established and their abilities to differentiate VVS from PPS were tested. Another 78 patients (53 VVS and 25 PPS) were used for external validation. Results: In the logistic regression model, the outcome indicated that the QT-dispersion (QTd) (P < 0.001), syncope duration (P < 0.001), and upright posture (P < 0.001) acted as independent factors for the differentiation of VVS from PPS, which generated an area under the curve (AUC) of 0.892. A cutoff value of 0.234 yielded a sensitivity and specificity of 89.3 and 80.8%, respectively, for the differentiation between VVS and PPS in the logistic regression model. In the scoring model which consists of three variables, a cutoff score of three points yielded a sensitivity and specificity of 91.3 and 76.9%, respectively, with an AUC of 0.909. The external validation test indicated that the negative and positive predictive values of the scoring model were 78.8 and 91.7%, respectively, and the accuracy was 80.8%. Conclusion: The scoring model consisting of three variables is an easy-to-perform, inexpensive, and non-invasive measure for initial differential diagnosis between VVS and PPS.