Examining differences in brain metabolism associated with childhood maltreatment and suicidal attempts in euthymic patients with bipolar disorder: a PET and machine learning study
Braz. J. Psychiatry (São Paulo, 1999, Impr.)
; 45(2): 127-131, Mar.-Apr. 2023. tab, graf
Artículo
en Inglés
|
LILACS-Express
| LILACS
| ID: biblio-1439551
Biblioteca responsable:
BR1.1
ABSTRACT
Objective:
Childhood maltreatment (CM) is a significant risk factor for the development and severity of bipolar disorder (BD) with increased risk of suicide attempts (SA). This study evaluated whether a machine learning algorithm could be trained to predict if a patient with BD has a history of CM or previous SA based on brain metabolism measured by positron emission tomography.Methods:
Thirty-six euthymic patients diagnosed with BD type I, with and without a history of CM were assessed using the Childhood Trauma Questionnaire. Suicide attempts were assessed through the Mini International Neuropsychiatric Interview (MINI-Plus) and a semi-structured interview. Resting-state positron emission tomography with 18F-fluorodeoxyglucose was conducted, electing only grey matter voxels through the Statistical Parametric Mapping toolbox. Imaging analysis was performed using a supervised machine learning approach following Gaussian Process Classification.Results:
Patients were divided into 18 participants with a history of CM and 18 participants without it, along with 18 individuals with previous SA and 18 individuals without such history. The predictions for CM and SA were not significant (accuracy = 41.67%; p = 0.879).Conclusion:
Further investigation is needed to improve the accuracy of machine learning, as its predictive qualities could potentially be highly useful in determining histories and possible outcomes of high-risk psychiatric patients.
Texto completo:
Disponible
Colección:
Bases de datos internacionales
Base de datos:
LILACS
Tipo de estudio:
Estudio pronóstico
/
Investigación cualitativa
/
Factores de riesgo
Idioma:
Inglés
Revista:
Braz. J. Psychiatry (São Paulo, 1999, Impr.)
Asunto de la revista:
Psiquiatria
Año:
2023
Tipo del documento:
Artículo
País de afiliación:
Brasil
/
Canadá
Institución/País de afiliación:
McMaster University/CA
/
Programa de Pós-Graduação em Medicina Molecular/BR
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Universidade Federal de Minas Gerais (UFMG)/BR