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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.

Abstract Background Coronary artery disease (CAD) is known as the leading cause of disability and death globally. Anxiety disorders are also recognized as common types of mental disorders that substantially impact global health. Iran ranks among the countries with a high incidence of CAD and anxiety disorders. Therefore, the present study aims to determine the potential association and epidemiological aspects of anxiety and CAD within the population of Mashhad, the second most popoulos city in Iran. Methods The present study is based on extracted data from the Mashhad stroke and heart atherosclerotic disorder (MASHAD) study which is a 10-year prospective cohort study intended to assess the effects of various CAD risk factors among Mashhad city residents. Anxiety scores were assessed at the baseline using Beck Anxiety Inventory and individuals were classified based on the BAI 4-factor structure model which included autonomic, cognitive, panic, and neuromotor components. Accordingly, the association between baseline anxiety scores and the BAI four-factor model with the risk of CAD events was analyzed using SPSS software version 21. Results Based on the results, 60.4% of the sample were female, and 5.6% were classified as having severe forms of anxiety. Moreover, severe anxiety was more prevalent in females. Results showed a 1.7% risk of CAD (p-value

Abstract Objective The purpose of this study was to investigate the effects of escitalopram on the peripheral expression of hypothalamic-pituitary-adrenal (HPA) axis-related genes (FKBP51, HSP90, NR3C1 and POMC) and HPA-axis hormones in patients with panic disorder (PD). Methods Seventy-seven patients with PD were treated with escitalopram for 12 weeks. All participants were assessed for the severity of panic symptoms using the Panic Disorder Severity Scale (PDSS). The expression of HPA-axis genes was measured using real-time quantitative fluorescent PCR, and ACTH and cortisol levels were measured using chemiluminescence at baseline and after 12 weeks of treatment. Results At baseline, patients with PD had elevated levels of ACTH and cortisol, and FKBP51 expression in comparison to healthy controls (all p

Background: Individuals with anxiety disorders (ADs) often display hypervigilance to threat information, although this response may be less pronounced following psychotherapy. This study aims to investigate the unconscious recognition performance of facial expressions in patients with panic disorder (PD) posttreatment, shedding light on alterations in their emotional processing biases. Methods: Patients with PD (n=34) after (exposure-based) cognitive behavior therapy and healthy controls (n=43) performed a subliminal affective recognition task. Emotional facial expressions (fearful, happy, or mirrored) were displayed for 33 ms and backwardly masked by a neutral face. Participants completed a forced choice task to discriminate the briefly presented facial stimulus and an uncovered condition where only the neutral mask was shown. We conducted a secondary analysis to compare groups based on their four possible response types under the four stimulus conditions and examined the correlation of the false alarm rate for fear responses to non-fearful (happy, mirrored, and uncovered) stimuli with clinical anxiety symptoms. Results: The patient group showed a unique selection pattern in response to happy expressions, with significantly more correct "happy" responses compared to controls. Additionally, lower severity of anxiety symptoms after psychotherapy was associated with a decreased false fear response rate with nonthreat presentations. Conclusion: These data suggest that patients with PD exhibited a "happy-face recognition advantage" after psychotherapy. Less symptoms after treatment were related to a reduced fear bias. Thus, a differential facial emotion detection task could be a suitable tool to monitor response patterns and biases in individuals with ADs in the context of psychotherapy. [ABSTRACT FROM AUTHOR]

Panic disorder is a psychiatric disorder characterized by recurrent panic attacks, with a prevalence of ~ 4% in the general population, causing heavy personal and socioeconomic burdens. The similarities of animal defense responses to clinical panic attack symptoms in humans make it possible to translate neuroanatomical pathways identified in animal studies to panic disorder in humans. Therefore, in this review we first present a basic overview of panic disorder in humans including the main subtypes, models commonly used to trigger panic attacks, related hypotheses, the neurotransmitter systems that may be involved, and the current clinical treatments to give the reader a comprehensive understanding of panic disorder. The animal section introduces the models that trigger panic-like behavior in animals and the brain regions that may be involved, providing insights for future elucidation of the neural circuit mechanisms behind panic attacks. [ABSTRACT FROM AUTHOR]

ObjectiveMethodResultsConclusions\nKey PointsThe Panic Disorder Dimensional Scale (PD-D) was developed to provide a dimensional rating of panic disorder (PD) symptom severity alongside the traditional categorical Diagnostic and Statistical Manual of Mental Disorders (DSM) diagnosis. The aim of the present study was to evaluate the psychometric properties of the PD-D in an Australian community sample.Two-hundred and eighty-eight participants (72.9% female) aged 18–76 years (M = 28.28; SD = 12.08) completed the study.Confirmatory factor analysis indicated that PD-D demonstrates a unidimensional factor (comparative fit index [CFI] = 0.95; Tucker-Lewis index (TLI) = 0.94; standardised root mean square residual [SRMR] = 0.04). The scale also demonstrated excellent internal consistency [α = .96 (95% CI: .95–.97); ω = 0.96 (95% CI: .95–.97)], and evidence of convergent and divergent validity. A good test–retest reliability was evident for the total PD-D score (ICC = .76, p < .001).The PD-D appears to be a reliable and valid measure which can be used to support diagnosis of PD in Australia. Limitations are discussed, including the use of a predominantly female sample and lack of clinician-informed data regarding current diagnoses.What is already known about this topic: Panic disorder is a chronic disorder with high symptomatic variability over time.A dimensional approach to the assessment of panic disorder has the benefit of capturing changes in severity and symptomology over time.The Panic Disorder Dimensional Scale (PD-D) was developed by the DSM-5 Anxiety, Obsessive-Compulsive Spectrum, Posttraumatic and Dissociative Disorder workgroup to aid in the dimensional assessment of panic disorder.Panic disorder is a chronic disorder with high symptomatic variability over time.A dimensional approach to the assessment of panic disorder has the benefit of capturing changes in severity and symptomology over time.The Panic Disorder Dimensional Scale (PD-D) was developed by the DSM-5 Anxiety, Obsessive-Compulsive Spectrum, Posttraumatic and Dissociative Disorder workgroup to aid in the dimensional assessment of panic disorder.What this topic adds: The current study offers support for the psychometric properties of the Panic Disorder Dimensional Scale (PD-D) in an Australian sample.The scale demonstrates a unidimensional factor structure, convergent and divergent validity, excellent internal consistency and good total score test-retest reliability.The PD-D holds promise for both clinical practice and future research into the dimensional conceptualisation of anxiety disorder symptoms.The current study offers support for the psychometric properties of the Panic Disorder Dimensional Scale (PD-D) in an Australian sample.The scale demonstrates a unidimensional factor structure, convergent and divergent validity, excellent internal consistency and good total score test-retest reliability.The PD-D holds promise for both clinical practice and future research into the dimensional conceptualisation of anxiety disorder symptoms. [ABSTRACT FROM AUTHOR]