Combining selective serotonin reuptake inhibitors and cognitive behavioral therapy in youth with depression and anxiety

Mills, Jeffrey A.; Suresh, Vikram; Peris, Tara S.; Walkup, John T.; Croarkin, Paul E.

doi:10.1016/j.jad.2021.10.047

Cited by 25 publications

(9 citation statements)

References 36 publications

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“…It is noteworthy that age, sex, and race did not impact prognostic symptom criteria thresholds nor prediction accuracy our model in patients treated with fluoxetine or duloxetine. This finding contrasts with prior work ( Mayes et al, 2007 ; Strawn et al, 2021 ). Future research should focus on this finding to develop the current predictive model as neurobiological biomarkers are incorporated.…”

Section: Discussioncontrasting

confidence: 99%

Evidence for machine learning guided early prediction of acute outcomes in the treatment of depressed children and adolescents with antidepressants

Athreya

Voort

Shekunov

et al. 2022

Child Psychology Psychiatry

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Background The treatment of depression in children and adolescents is a substantial public health challenge. This study examined artificial intelligence tools for the prediction of early outcomes in depressed children and adolescents treated with fluoxetine, duloxetine, or placebo. Methods The study samples included training datasets (N = 271) from patients with major depressive disorder (MDD) treated with fluoxetine and testing datasets from patients with MDD treated with duloxetine (N = 255) or placebo (N = 265). Treatment trajectories were generated using probabilistic graphical models (PGMs). Unsupervised machine learning identified specific depressive symptom profiles and related thresholds of improvement during acute treatment. Results Variation in six depressive symptoms (difficulty having fun, social withdrawal, excessive fatigue, irritability, low self‐esteem, and depressed feelings) assessed with the Children’s Depression Rating Scale‐Revised at 4–6 weeks predicted treatment outcomes with fluoxetine at 10–12 weeks with an average accuracy of 73% in the training dataset. The same six symptoms predicted 10–12 week outcomes at 4–6 weeks in (a) duloxetine testing datasets with an average accuracy of 76% and (b) placebo‐treated patients with accuracies of 67%. In placebo‐treated patients, the accuracies of predicting response and remission were similar to antidepressants. Accuracies for predicting nonresponse to placebo treatment were significantly lower than antidepressants. Conclusions PGMs provided clinically meaningful predictions in samples of depressed children and adolescents treated with fluoxetine or duloxetine. Future work should augment PGMs with biological data for refined predictions to guide the selection of pharmacological and psychotherapeutic treatment in children and adolescents with depression.

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Section: Discussioncontrasting

confidence: 99%

Evidence for machine learning guided early prediction of acute outcomes in the treatment of depressed children and adolescents with antidepressants

Athreya

Voort

Shekunov

et al. 2022

Child Psychology Psychiatry

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“…For example, it has been reported that using ketamine can help upregulate BDNF expression, and it may be interesting to see if it also can reduce brain ventricle volume over time. 78 Other future studies of interest may be to study the effects seen here with SRIs when used in combination with another form of therapy, such as combining cognitive behavioral therapy with SRI treatment 79 versus another form of therapy (eg, a meditation program) in combination with SRI treatment, 80 all the while also looking at changes in the brain ventricles over time. Finally, a follow up study would be needed to link SRI-induced ventricle volume decrease to clinically relevant measures, which our limited sample size did not allow.…”

Section: Discussionmentioning

confidence: 99%

Decreased Brain Ventricular Volume in Psychiatric Inpatients with Serotonin Reuptake Inhibitor Treatment

et al. 2022

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Background Brain ventricles have been reported to be enlarged in several neuropsychiatric disorders and in aging. Whether human cerebral ventricular volume can decrease over time with psychiatric treatment is not well-studied. The aim of this study was to examine whether inpatients taking serotonin reuptake inhibitors (SRI) exhibited reductions in cerebral ventricular volume. Methods Psychiatric inpatients, diagnosed mainly with depression, substance use, anxiety, and personality disorders, underwent two imaging sessions (Time 1 and Time 2, approximately 4 weeks apart). FreeSurfer was used to quantify volumetric features of the brain, and ANOVA was used to analyze ventricular volume differences between Time 1 and Time 2. Inpatients’ brain ventricle volumes were normalized by dividing by estimated total intracranial volume (eTIV). Clinical features such as depression and anxiety levels were collected at Time 1, Time 1.5 (approximately 2 weeks apart), and Time 2. Results Inpatients consistently taking SRIs (SRI + , n = 44) showed statistically significant reductions of brain ventricular volumes particularly for their left and right lateral ventricular volumes. Reductions in their third ventricular volume were close to significance ( p = .068). The inpatients that did not take SRIs (SRI-, n = 25) showed no statistically significant changes in brain ventricular volumes. The SRI + group also exhibited similar brain structural features to the healthy control group based on the 90% confidence interval comparsions on brain ventricular volume parameters, whereas the SRI- group still exhibited relatively enlarged brain ventricular volumes after treatment. Conclusions SRI treatment was associated with decreased brain ventricle volume over treatment.

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“…Анализ современных клинических рекомендаций, опубликованных как в нашей стране, так и за рубежном указывает на то, что тревожные расстройства эффективно поддаются как психофармакотерапии, так и психотерапии 2 [27,28]. Кроме того, было убедительно доказано, что комбинирование психофармакотерапии и психотерапии способствует существенному улучшению прогноза у пациентов с основными формами тревожных расстройств [29].…”

Section: терапия тревожных расстройствunclassified

Anxiety disorders in general medical practice – clinical picture, diagnosis, optimized approaches to therapy

et al. 2023

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Anxiety disorders are widespread in the population and in general medical practice and have a pronounced negative impact on the quality of life and functioning of patients. Currently, the prerequisites for the diagnosis and treatment of anxiety disorders outside the psychiatric network are accumulating by therapists, general practitioners and other non-psychiatric doctors. A review of the most significant factors contributing to a wider diagnosis and treatment of anxiety disorders in general medical practice is given. This review presents modern ideas about the pathogenesis of anxiety disorders, substantiates the modern idea of their multifactorial nature, the contribution of genetic and epigenetic, psychological and social factors, outlines the concepts of the neurobiological basis of pathological anxiety based on neuroimaging studies. In the future, information is provided on the general manifestations of anxiety disorders, the main clusters of anxiety, the systematics of anxiety disorders according to ICD-10. Modern ideas about the diagnosis of anxiety disorders using both scales and a clinical approach are given, a detailed review of currently available diagnostic scales validated for clinical practice is presented. The main approaches to conducting a clinical conversation are also presented, recommendations are given for the most successful collection of information about the clinical condition of patients. At the end of the review, information is given on existing approaches to psychopharmacotherapy and psychotherapy of anxiety disorders. Taking into account pharmacological and clinical studies, the place of drugs tofisopam (an atypical allosteric modulator of GABA receptors) and buspirone (a partial agonist of serotonin 1A receptors) in the treatment of anxiety disorders in general medical practice has been argued.

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Combining selective serotonin reuptake inhibitors and cognitive behavioral therapy in youth with depression and anxiety

Cited by 25 publications

References 36 publications

Evidence for machine learning guided early prediction of acute outcomes in the treatment of depressed children and adolescents with antidepressants

Evidence for machine learning guided early prediction of acute outcomes in the treatment of depressed children and adolescents with antidepressants

Decreased Brain Ventricular Volume in Psychiatric Inpatients with Serotonin Reuptake Inhibitor Treatment

Anxiety disorders in general medical practice – clinical picture, diagnosis, optimized approaches to therapy

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