Publicação
Insight in obsessive-compulsive disorder : clinical and neuropsychopathological correlations
| datacite.subject.fos | Ciências Médicas::Medicina Clínica | pt_PT |
| dc.contributor.advisor | Sampaio, Daniel José Branco | |
| dc.contributor.advisor | Filipe, Maria Luísa Caruana Canessa Figueira Cruz | |
| dc.contributor.advisor | Sahakian, Barbara Jacquelyn | |
| dc.contributor.author | Manarte, Lucas | |
| dc.date.accessioned | 2024-03-21T16:38:49Z | |
| dc.date.available | 2025-03-01T01:30:30Z | |
| dc.date.issued | 2021-09 | |
| dc.date.submitted | 2021-05 | |
| dc.description.abstract | Introduction: OCD affects 2% of the world adult population. The proposed treatments, CBT and SSRIs, have significantly high failure rates, leading to an insufficient treatment response (around 20-40%). Different studies have shown that poor insight has a significant influence on the absence of response to the treatments proposed for OCD. Most studies report that 15-36% of OCD patients have poor insight. The development of homogeneous subgroups of patients is a fundamental step for understanding OCD’s clinical heterogeneity, finding physiopathological mechanisms and structuring efficient therapeutic approaches. Some studies show that poor insight is the best predictor of a poor response to serotonergic agents. However, the results are still controversial, with data showing both that the response to SSRIs is good in patients with poor insight and that it is unsatisfactory. The compliance to medication is better in patients with better insight. According to some authors, insight is the best predictor of treatment response. The differences between the various studies (especially regarding treatment response) suggest that OCD patients with poor insight constitute a specific patient subtype with a different biological profile, including differences in neurotransmission channels other than the serotonergic ones. Insight is seen as a predictor of treatment response not only with regard to the severity and functioning of OCD, but also in relation to other characteristics of the disease. Materials and Methods: The sample included 57 OCD patients, 20 of which with poor insight and 37 patients with good insight. The control group comprised 53 medical students and blood donors, who best matched the clinical sample. The study’s participants were evaluated in two different phases: first, by the coordinator of the study, who collected the clinical data, and afterwards by two neuropsychologists, who conducted the neuropsychological assessment. Plasma samples were also collected and the BDNF was quantified using ELISA. The statistical analysis was done using SPSS and a two-tailed significance level was set at p < 0.05. The demographic and clinical characteristics of the two groups were compared using the Chi-Squared and the t-student statistical tests. Categorical variables were described as absolute values (n). The normal distribution was assessed by the Kolmogorov–Smirnov test. Two groups of OCD patients were defined based on their BABS score: poor insight (BABS score >= 12) and good insight (BABS score < 12). The Chi-Squared statistical test was used to test the independence between the symptom profile (current obsessions and current compulsions and associated subtypes) and insight. The associations between insight and other variables were also tested using the Chi-Squared statistical independence test and ANOVA. There were no significant differences between the OCD group and the control group, except for the variable “education years”, “antidepressive use” and “antipsychotic use,” which were controlled using ANCOVA, for that reason and when considered appropriate. An exploratory analysis was conducted in order to relate the BABS score (insight) with those variables, using linear regression and the Pearson correlation coefficient. In order to control the false discovery rate, a correction for multiple comparisons according to Benjamini and Hochberg was conducted. Results: The poor-insight group differed significantly (95%) regarding emotional awareness (negative emotion recognition; empathic concern) (p = 0.046) and hoarding (p = 0.006). Also, our analysis revealed that the poor insight group differed significantly regarding the executive function tests, and particularly in the Wisconsin Card Sorting Test (p 0.001), trail-making-test (A/B) (p = 0.002) and Toulouse-Piérron (work-efficiency, p 0.001). After controlling for haemolysis and the use of antidepressants, patients with poor insight were found to have a lower plasma BDNF concentration than that of good-insight patients and controls (p = 0.0286). Discussion and Conclusions: Insight is a crucial factor for the evaluation and treatment of psychiatric patients in general, and OCD patients in particular. Clinically speaking, the link between poor insight and hoarding is a significant one, with important clinical implications for treatment and management. Moreover, OCD patients with poor insight show deficits in forms of hot cognition, such as emotional awareness. To what concerns executive functions, our findings emphasize the role played by the frontal lobe in insight and suggest that the neuropsychological profile of poor-insight patients is different from their good-insight counterparts. To what plasma analysis concerns, patients with poor insight seem to have a less favourable molecular profile, of which the plasma BDNF concentration is only one sign. In the future, BDNF may become a therapeutic target. Patients with poor insight display clinical, neuropsychological and biological differences when compared to the others, and these differences may contribute to the development of new lines of treatment for at least a third of OCD patients. In our opinion, further research should investigate the extent to which poor insight and impaired emotional awareness can be modified by psychological or pharmacological therapies. More research is needed on these topics, especially including a larger sample, fMRI data and other characteristics often found in patients with poor insight, such as treatment resistance and psychopathology severity. Moreover, future work focusing on other therapeutic targets and a wider array of prognostic tools may broaden our understanding of OCD pathophysiology. | pt_PT |
| dc.identifier.tid | 101518897 | pt_PT |
| dc.identifier.uri | http://hdl.handle.net/10451/63662 | |
| dc.language.iso | eng | pt_PT |
| dc.title | Insight in obsessive-compulsive disorder : clinical and neuropsychopathological correlations | pt_PT |
| dc.type | doctoral thesis | |
| dspace.entity.type | Publication | |
| person.familyName | Manarte | |
| person.givenName | Lucas | |
| person.identifier.ciencia-id | 9A14-43A4-EDC4 | |
| person.identifier.orcid | 0000-0002-9771-8179 | |
| rcaap.rights | openAccess | pt_PT |
| rcaap.type | doctoralThesis | pt_PT |
| relation.isAuthorOfPublication | 524d6deb-d469-41d2-a793-de40c53cbebc | |
| relation.isAuthorOfPublication.latestForDiscovery | 524d6deb-d469-41d2-a793-de40c53cbebc | |
| thesis.degree.name | Tese de doutoramento, Medicina (Psiquiatria e Saúde Mental), Universidade de Lisboa, Faculdade de Medicina, 2021 | pt_PT |