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Abnormal functional connectivity (FC) within the fear network model (FNM) has been identified in panic disorder (PD) patients, but the specific local structural and functional properties, as well as effective connectivity (EC), remain poorly understood in PD. The purpose of this study was to investigate the structural and functional patterns of the FNM in PD. Magnetic resonance imaging data were collected from 33 PD patients and 35 healthy controls (HCs). Gray matter volume (GMV), degree centrality (DC), regional homogeneity (ReHo), and amplitude of low-frequency fluctuation (ALFF) were used to identify the structural and functional characteristics of brain regions within the FNM in PD. Subsequently, FC and EC of abnormal regions, based on local structural and functional features, and their correlation with clinical features were further examined. PD patients exhibited preserved GMV, ReHo, and ALFF in the brain regions of the FNM compared with HCs. However, increased DC in the bilateral amygdala was observed in PD patients. The amygdala and its subnuclei exhibited altered EC with rolandic operculum, insula, medial superior frontal gyrus, supramarginal gyrus, opercular part of inferior frontal gyrus, and superior temporal gyrus. Additionally, Hamilton Anxiety Scale score was positively correlated with EC from left lateral nuclei (dorsal portion) of amygdala to right rolandic operculum and left superior temporal gyrus. Our findings revealed a reorganized functional network in PD involving brain regions regulating exteroceptive-interoceptive signals, mood, and somatic symptoms. These results enhance our understanding of the neurobiological underpinnings of PD, suggesting potential biomarkers for diagnosis and targets for therapeutic intervention. [ABSTRACT FROM AUTHOR]

Panic disorder (PD) affects family members and can be influenced by familial factors. Adverse family events may contribute to anxiety and PD. We examined a family therapy case of a client with PD in South Korea. We used a thematic analysis to analyze therapy transcripts and video recordings and displayed our findings using a network. We identified five stages of the psychological process in the development of PD: (1) formation of anxiety, (2) sheltered life, (3) crisis, (4) loss of haven, and (5) inner breakdown. External situations, family dynamics, and psychological experiences at each stage are examined. Family dynamics that occurred as the family coped with external situations contributed to the client's psychological experiences, which triggered anxiety that led to PD. This study suggests family dynamics can be associated with one's internal experiences that could lead to PD, highlighting the importance of functional family dynamics and coping when facing crises. [ABSTRACT FROM AUTHOR]

BackgroundMethodsResultsDiscussionIndividuals with panic disorder (PD) often exhibit a proclivity to conclude that an imminent catastrophe looms, drawing such conclusions from limited physical information. Reflection impulsivity, characterized by decision-making without adequate information, likely affects this bias. This study examines the relationship between reflection impulsivity and self-report impulsive features in individuals with PD.Fifty patients with PD and 50 healthy controls (HC) participated to this study. Reflection impulsivity was assessed using the Information Sampling Task (IST), while trait impulsivity was measured using the Barratt Impulsiveness Scale (BIS). Participants also completed the Beck Anxiety Inventory, Panic and Agoraphobia Scale (P&A), and Anxiety Sensitivity Index-3 (ASI-3).Individuals with PD exhibited higher reflection impulsivity compared to HC. Increased reflection impulsivity correlated positively with PD severity as assessed by the P&A and cognitive concerns measured by ASI-3. No significant correlations were found with physical or social concerns. PD patients had higher BIS scores than HC. Higher trait impulsivity was linked to recurrent emergency department visits among PD patients.The findings of this study reveal the notion of increased impulsivity among individuals with PD and its relationship with cognitive concerns, as well as recurrent visits to the emergency department stemming from panic attacks. [ABSTRACT FROM AUTHOR]

In panic disorder (PD), functional disturbance of the hypothalamus–pituitary–adrenal (HPA) axis has been considered. However, in neuroimaging studies of PD, the hypothalamus and pituitary gland are poorly studied. We investigated the volume of PD patients' hypothalamus and pituitary gland, enrolling 38 PD patients and 38 healthy controls. Severity of PD was mild to moderate according to the Panic Disorder Severity Scale, and the illness duration was relatively short (median = 2.8 years). The hypothalamus' gray matter was automatically extracted and segmented, whereas the pituitary gland was manually traced. Regarding the hypothalamus, the paraventricular nucleus (PVH), which produces the corticotropin-releasing hormone, was of interest. The volumes of the pituitary and the bilateral anterior-superior hypothalamic subunits, where the PVH would be located, were compared by the multiple regression analyses controlling for age and intracranial content volume. To compensate for limitation in the abovementioned segmentation and analyses, the voxel-based morphometry with small volume correction (VBM–SVC) targeting the whole hypothalamus was also performed. The multiple regression analyses did not find significant effect of PD diagnosis on the volumes. However, in the VBM–SVC analysis, volume reduction of the PVH was suggested in PD even when patients who experienced PD for ≥ 3 years were excluded [peak coordinate (x, y, z = -2, 3, -8), FWE-corrected P =.022 (cluster-level) and 0.003 (peak-level), voxel size = 63]. Our results suggested structural alteration of the PVH in PD patients for the first time, indicating importance of the HPA-axis in PD pathology. [ABSTRACT FROM AUTHOR]

The aim of this study is to investigate the effectiveness of Eye Movement Desensitization and Reprocessing (EMDR) treatment in adolescents with panic disorder (PD). This follow-up study consists of 30 adolescents with PD without agoraphobia, aged 14–17 (15.53 ±.97). They were evaluated with Kiddie Schedule for Affective Disorders and Schizophrenia for School-Age Children Present, also the Panic and Agoraphobia Scale (PAS) and Beck Anxiety Inventory (BAI) were administered at baseline, at the end of the 4th and 12th weeks of treatment. EMDR therapy which is an eight-phase treatment approach composed of standardized protocols and procedures was applied for 12 weeks, one session per week. The baseline mean of the total PAS score decreased from 40.06 to 13.13 at fourth week and 1.2 at the end of 12th week of treatment. In addition, BAI score decreased significantly from 33.67 to 13.83 at 4 weeks and 5.31 at the end of 12th week of treatment. Overall, our results underscore the effectiveness of EMDR in adolescents with PD. Moreover, the current study suggests that EMDR may represent an effective intervention technique for PD in adolescents to protect against relapses and to overcome a fear of future attacks. [ABSTRACT FROM AUTHOR]

Objective: Panic disorder is a modestly heritable condition. Currently, diagnosis is based only on clinical symptoms; identifying objective biomarkers and a more reliable diagnostic procedure is desirable. We investigated whether people with panic disorder can be reliably diagnosed utilizing combinations of multiple polygenic scores for psychiatric disorders and their intermediate phenotypes, compared with single polygenic score approaches, by applying specific machine learning techniques. Methods: Polygenic scores for 48 psychiatric disorders and intermediate phenotypes based on large-scale genome-wide association studies (n = 7556–1,131,881) were calculated for people with panic disorder (n = 718) and healthy controls (n = 1717). Discrimination between people with panic disorder and healthy controls was based on the 48 polygenic scores using five methods for classification: logistic regression, neural networks, quadratic discriminant analysis, random forests and a support vector machine. Differences in discrimination accuracy (area under the curve) due to an increased number of polygenic score combinations and differences in the accuracy across five classifiers were investigated. Results: All five classifiers performed relatively well for distinguishing people with panic disorder from healthy controls by increasing the number of polygenic scores. Of the 48 polygenic scores, the polygenic score for anxiety UK Biobank was the most useful for discrimination by the classifiers. In combinations of two or three polygenic scores, the polygenic score for anxiety UK Biobank was included as one of polygenic scores in all classifiers. When all 48 polygenic scores were used in combination, the greatest areas under the curve significantly differed among the five classifiers. Support vector machine and logistic regression had higher accuracy than quadratic discriminant analysis and random forests. For each classifier, the greatest area under the curve was 0.600 ± 0.030 for logistic regression (polygenic score combinations N = 14), 0.591 ± 0.039 for neural networks (N = 9), 0.603 ± 0.033 for quadratic discriminant analysis (N = 10), 0.572 ± 0.039 for random forests (N = 25) and 0.617 ± 0.041 for support vector machine (N = 11). The greatest areas under the curve at the best polygenic score combination significantly differed among the five classifiers. Random forests had the lowest accuracy among classifiers. Support vector machine had higher accuracy than neural networks. Conclusions: These findings suggest that increasing the number of polygenic score combinations up to approximately 10 effectively improved the discrimination accuracy and that support vector machine exhibited greater accuracy among classifiers. However, the discrimination accuracy for panic disorder, when based solely on polygenic score combinations, was found to be modest. [ABSTRACT FROM AUTHOR]

Background: Non-cardiac chest pain, a term that serves as a broad canvas, has a multitude of potential causes in which panic disorder emerges as a prevailing cause. The recognition and accurate diagnosis of panic disorder among patients with non-cardiac chest pain is important. Hence a study was conducted to understand the prevalence of panic disorder among patients with non-cardiac chest pain in a tertiary care center in Kerala. Methods: A hospital-based, cross-sectional study was done among 118 patients who were diagnosed with non-cardiac chest pain by a cardiologist. The study was conducted in the cardiology OPD in a tertiary care center in Kerala. Mini-International Neuropsychiatric Interview Panic disorder – Version 6.0.0 (M.I.N.I.) was used to diagnose panic disorder among these patients. Results: It was found that panic disorder was present in 39.8% (95% Confidence Interval - 30.9-49.3%). Conclusion: The prevalence of panic disorder in patients diagnosed with non-cardiac chest pain was 39.8%. Consultation liaison treatment using pharmacotherapy and/or psychotherapy with the help of a psychiatrist may benefit such patients.