MARCELO CAMARGO BATISTUZZO
Projetos de Pesquisa
Unidades Organizacionais
Instituto de Psiquiatria, Hospital das Clínicas, Faculdade de Medicina
LIM/23 - Laboratório de Psicopatologia e Terapêutica Psiquiátrica, Hospital das Clínicas, Faculdade de Medicina
LIM/23 - Laboratório de Psicopatologia e Terapêutica Psiquiátrica, Hospital das Clínicas, Faculdade de Medicina
9 resultados
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Agora exibindo 1 - 9 de 9
bookPart Transtornos obsessivo-compulsivo na infância e adolescência(2021) FATORI, Daniel; BATISTUZZO, Marcelo Camargo; MORIKAWA, Márcia; SAWADA, Julio Renó; ASBAHR, Fernando RamosconferenceObject Treatment Response Prediction in Pediatric Patients With OCD Using Structural Neuroimaging Correlates: Simple Linear Regression Versus Support Vector Regression(2017) VATTIMO, Edoardo; BARROS, Vivian; BATISTUZZO, Marcelo; REQUENA, Guaraci; SATO, Joao; FATORI, Daniel; SHAVITT, Roseli; MIGUEL, Euripedes; HOEXTER, MarceloconferenceObject Cortico-Basal Ganglia-Thalamo-Cortical Circuitry Structural Correlates of Treatment Response in Children with Obsessive-Compulsive Disorder(2016) VATTIMO, Edoardo F. Q.; BATISTUZZO, Marcelo C.; SATO, Joao R.; SA, Daniel G. F. de; SHAVITT, Roseli G.; MIGUEL, Euripedes C.; HOEXTER, Marcelo Q.- Influence of Treatment on Visual Information Planning and Nonverbal Memory Performance in Children and Adolescents with Obsessive Compulsive Disorder(2014) SHAVITT, Roseli G.; MARCO, Marina de; BATISTUZZO, Marcelo C.; OKI, Fabio H.; BERNARDES, Elisa; MONTI, Camilla; MORAIS, Ivanil; BORCATO, Sonia R.; FATORI, Daniel
- Is it time to change the gold standard of obsessive-compulsive disorder severity assessment? Factor structure of the Yale-Brown Obsessive-Compulsive Scale(2020) FATORI, Daniel; COSTA, Daniel L. C.; ASBAHR, Fernando R.; FERRAO, Ygor A.; ROSARIO, Maria Conceicao; MIGUEL, Euripedes C.; SHAVITT, Roseli G.; BATISTUZZO, Marcelo C.Objectives: The Yale-Brown Obsessive-Compulsive Scale has been considered the gold standard scale to assess obsessive-compulsive disorder severity. Previous studies using exploratory factor analysis and confirmatory factor analysis with this scale showed mixed findings in terms of factor structure and fit of models. Therefore, we used confirmatory factor analysis to compare different Yale-Brown Obsessive-Compulsive Scale models in a large sample aiming to identify the best model fit. Methods: We assessed adult obsessive-compulsive disorder patients (n = 955) using three measures: Yale-Brown Obsessive-Compulsive Scale severity ratings, the Dimensional Yale-Brown Obsessive-Compulsive Scale and the clinical global impression scale. We tested all factor structures reported by previous studies to investigate which model best fitted the data: one-factor, two-factor, three-factor and their equivalent high-order solutions. We also investigated Yale-Brown Obsessive-Compulsive Scale items correlations with scores from the other measures of obsessive-compulsive disorder severity. Results: Confirmatory factor analysis models presented mediocre to fair goodness-of-fit indexes. Severity items related to resistance to obsessions and compulsions presented low factor loadings. The model with the best fit indexes was a high-order model without obsessive-compulsive disorder resistance items. These items also presented small correlations with other obsessive-compulsive disorder severity measures. Conclusion: The obsessive-compulsive disorder field needs to discuss further improvements in the Yale-Brown Obsessive-Compulsive Scale and/or continue to search for better measures of obsessive-compulsive disorder severity.
- Factor structure of the Dimensional Yale-Brown Obsessive-Compulsive Scale in a large sample of adults with obsessive-compulsive disorder(2022) BATISTUZZO, Marcelo C.; FONTENELLE, Leonardo; FERRAO, Ygor A.; ROSARIO, Maria C.; MIGUEL, Euripedes C.; FATORI, DanielObjectives: Although the Dimensional Yale-Brown Obsessive-Compulsive Scale (DY-BOCS) is a widely used instrument for assessing different obsessive-compulsive symptom dimensions, its factor structure has never been studied in a Brazilian population. Thus, we aimed to assess the goodness-of fit indexes and factor loadings of two higher-order models of the DY-BOCS using confirmatory factor analysis (CFA) in a large obsessive-compulsive disorder (OCD) sample. Methods: We tested two CFA models in a sample of 955 adults with OCD who had been assessed with the DY-BOCS in a cross-sectional multi-site study. The first model encompassed the symptom checklist (present or absent), whereas the second focused on items related to severity scores. Results: Both models presented adequate goodness-of-fit indexes. The comparative fit index, Tucker Lewis index, and omega were 4 0.9, while the root mean square error of approximation was p 0.06 for both models. Factor loadings for each item of each dimension are presented and discussed. Conclusion: Higher-order factor models showed adequate goodness-of-fit indexes, indicating that they appropriately measured OCD dimensions in this Brazilian population.
- Caudate volume differences among treatment responders, non-responders and controls in children with obsessive-compulsive disorder(2019) VATTIMO, Edoardo F. Q.; BARROS, Vivian B.; REQUENA, Guaraci; SATO, Joao R.; FATORI, Daniel; MIGUEL, Euripedes C.; SHAVITT, Roseli G.; HOEXTER, Marcelo Q.; BATISTUZZO, Marcelo C.Treatment response in obsessive-compulsive disorder (OCD) is heterogeneous and the neurobiological underpinnings of such variability are unknown. To investigate this issue, we looked for differences in brain structures possibly associated with treatment response in children with OCD. 29 children with OCD (7-17 years) and 28 age-matched controls underwent structural magnetic resonance imaging. Patients then received treatment with fluoxetine or group cognitive-behavioral therapy during 14 weeks, and were classified as treatment responders or non-responders. The caudate nucleus, thalamus and orbitofrontal cortex were selected a priori, according to previous evidence of their association with OCD and its treatment. Gray matter (GM) volume comparisons between responders, non-responders and controls were performed, controlling for total GM volume. 17 patients were classified as responders. Differences among responders, non-responders and controls were found in both caudate nuclei (both p-values=0.041), but after Bonferroni correction for multiple comparisons, these findings were non-significant. However, after excluding the effect of an outlier, findings were significant for the right caudate (p=0.004). Pairwise comparisons showed larger caudate GM volume in responders versus non-responders and controls, bilaterally. The right caudate accounted for 20.2% of the variance in Y-BOCS changes after treatment in a linear regression model, with a positive correlation (p=0.016). We present a possible neural substrate for treatment response in pediatric OCD, which is in line with previous evidence regarding the caudate nucleus. Considering the limitations, further research is needed to replicate this finding and elucidate the heterogeneity of treatment response in children with OCD.
- PREDICTING OBSESSIVE-COMPULSIVE DISORDER TREATMENT RESPONSE IN PEDIATRIC PATIENTS USING STRUCTURAL NEUROIMAGING CORRELATES: A COMPARISON BETWEEN SIMPLE LINEAR REGRESSION AND SUPPORT VECTOR REGRESSION(2016) VATTIMO, Edoardo F.; BARROS, Vivian B.; REQUENA, Guaraci; SATO, Joao R.; BATISTUZZO, Marcelo Camargo; SHAVITT, Roseli G.; FATORI, Daniel; MIGUEL, Euripedes; HOEXTER, Marcelo Q.
- Risk factors for obsessive-compulsive symptoms. Follow-up of a community-based youth cohort(2021) BARROS, Pedro Macul Ferreira de; ROSARIO, Maria Conceicao do; SZEJKO, Natalia; POLGA, Natalia; REQUENA, Guaraci de Lima; RAVAGNANI, Beatriz; FATORI, Daniel; BATISTUZZO, Marcelo Camargo; HOEXTER, Marcelo Queiroz; ROHDE, Luis Augusto; POLANCZYK, Guilherme Vanoni; LECKMAN, James Frederick; MIGUEL, Euripedes Constantino; ALVARENGA, Pedro Gomes deEnvironmental factors are at least as important as genetic factors for the development of obsessive-compulsive symptoms (OCS), but the identification of such factors remain a research priority. Our study aimed to investigate the association between a broad scope of potential risk factors and OCS in a large community cohort of children and adolescents. We evaluated 1877 participants and their caregivers at baseline and after 3 years to assess various demographic, prenatal, perinatal, childhood adversity, and psychopathological factors. Mean age at baseline was 10.2 years (SD 1.9) and mean age at follow-up was 13.4 years (SD 1.9). Reports of OCS at baseline and follow-up were analyzed using latent variable models. At preliminary regression analysis, 15 parameters were significantly associated with higher OCS scores at follow-up. At subsequent regression analysis, we found that eight of these parameters remained significantly associated with higher follow-up OCS scores while being controlled by each other and by baseline OCS scores. The significant predictors of follow-up OCS were: lower socioeconomic status (p = 0.033); lower intelligence quotient (p = 0.013); lower age (p < 0.001); higher maternal stress level during pregnancy (p = 0.028); absence of breastfeeding (p = 0.017); parental baseline OCS (p = 0.038); youth baseline anxiety disorder (p = 0.023); and youth baseline OCS scores (p < 0.001). These findings may better inform clinicians and policymakers engaged in the mental health assessment and prevention in children and adolescents.