Dimensional structure of bodily panic attack symptoms and their specific connections to panic cognitions, anxiety sensitivity and claustrophobic fears

A Systematic Review of Thermosensation and Thermoregulation in Anxiety Disorders

Objectives: Sweating, hot flushes, and blushing are symptoms frequently reported by individuals with anxiety disorders. They represent important reinforcers of anxiogenic cognitions and behaviours. One system that may be involved in the manifestation of these symptoms is the thermosensory/thermoregulatory system. The aim of the present study was to investigate to what extent individuals with anxiety disorders are characterised by alterations in this system.

Methods: PubMed and PsycINFO were systematically searched. Studies were eligible if they (i) assessed individuals with anxiety disorders, (ii) thermosensation or thermoregulatory effectors/outcomes, and (iii) used a case-control design.

Results:N = 86 studies were identified. There was no evidence of altered thermosensation in individuals with anxiety disorders. Regarding thermoregulatory effectors, individuals with social anxiety disorder exhibited altered cutaneous vasodilation upon pharmacological challenge; individuals with specific phobia showed increased sweating upon confrontation with phobic stimuli; individuals with panic disorder showed increased daily sweating as well as increased sweating in response to non-phobic and phobic stimuli. Regarding thermoregulatory outcomes, there was evidence for altered skin temperature in all subtypes of anxiety.

Conclusion: Whereas there was no evidence of altered thermoregulation in specific phobia, a subgroup of individuals with social anxiety and panic disorder appears to exhibit altered vasodilation and sweating, respectively. Longitudinal research is warranted to investigate whether this represents a vulnerability to anxiety/panic.

A fog assisted intelligent framework based on cyber physical system for safe evacuation in panic situations

In the current scenario of the COVID-19 pandemic and worldwide health emergency, one of the major challenges is to identify and predict the panic health of persons. The management of panic health and on-time evacuation prevents COVID-19 infection incidences in educational institutions and public places. Therefore, a system is required to predict the infection and suggests a safe evacuation path to people that control panic scenarios with mortality. In this paper, a fog-assisted cyber physical system is introduced to control panic attacks and COVID-19 infection risk in public places. The proposed model uses the concept of physical and cyber space. The physical space helps in real time data collection and transmission of the alert generation to the stakeholders. Cyberspace consists of two spaces, fog space, and cloud-space. The fog-space facilitates panic health and COVID-19 symptoms determination with alert generation for risk-affected areas. Cloud space monitors and predicts the person's panic health and symptoms using the SARIMA model. Furthermore, it also identifies risk-prone regions in the affected place using Geographical Population Analysis. The performance evaluation acknowledges the efficiency related to panic health determination and prediction based on the SARIMA with risks mapping accuracy. The proposed system provides an efficient on time evacuation with priority from risk-affected places that protect people from attacks due to panic and infection caused by COVID-19.

Fog-assisted Energy Efficient Cyber Physical System for Panic-based Evacuation during Disasters

Disasters around the world have adversely affected every aspect of life and panic-health of stranded persons is one such category. An effective and on-time evacuation from disaster-affected areas can avoid any panic-related health problems of the stranded persons. Although the nature of disasters differ in terms of how they occur, the evacuation of stranded persons faces approximately same set of issues related to the communication, time-sensitive computation and energy efficiency of the devices operated in the disaster-affected areas. In this paper, a cyber physical system (CPS) is proposed that takes into account various challenges of the disaster evacuation, so an efficient on-time and orderly evacuation of stranded panicked persons could be realized. The system employs fog-assisted mobile and UAV devices for time-sensitive computation services, data relaying and energy-aware computation. The system uses a fog-assisted two-factor energy-aware computation approach using data reduction, which enables the energy-efficient data reception and transmission (DRecTrans) operations at the fog nodes and compensates to extend the period for other functionalities. The data reduction at fog devices employs Novel Events Identification (NEI) and Principal Component Analysis (PCA) for detecting consecutive duplicate traffic and data summarization of high dimensional data, respectively. The proposed system operates in two spaces: physical and cyber. Physical space facilitates real-world data acquisition and information sharing with the concerned stakeholders (stranded persons, evacuation teams and medical professionals). The cyber space houses various data-analytics layers and comprises of two subspaces: fog and cloud. The fog space helps in providing real-time panic-health diagnostic and alert services and enables the optimized energy consumption of devices operate in disaster-affected areas, whereas the cloud space facilitates the monitoring and prediction of panic severity of the stranded persons, using a conditional probabilistic model and seasonal auto regression integrated moving average (SARIMA), respectively. Cloud space also facilitates the disaster mapping for converging the evacuation map to the actual situation of the disaster-affected area, and geographical population analysis (GPA) for the identification of the panic severity-based critical regions. The performance evaluation of the proposed CPS acknowledges its Logistic Regression-based panic-well being determination and real-time alert generation efficiency. The simulated implementation of NEI and PCA depicts the fog-assisted energy efficiency of the DRecTrans operations of the fog nodes. The performance evaluation of the proposed CPS also acknowledges the prediction efficiency of the SARIMA and disaster mapping accuracy through GPA. The proposed system also discusses a case study related to the pandemic disaster of coronavirus disease 2019 (COVID-19), where the system can help in panic-based selective testing of the persons, and preventing panic due to distressing period of COVID-19 outbreak.

A 3-Month Naturalistic Follow-Up Treatment With Selective Serotonin Reuptake Inhibitors in Frequent Attenders of General Medical Practice: What Correlates With a Good Response?

ABSTRACT

Frequent attenders (FAs), defined as patients repeatedly attending general practitioners, frequently exhibit underdiagnosed psychiatric comorbidities, leading to the hypothesis that frequent attendance may be related to an undetected psychiatric burden. This study explores the role of psychiatric comorbidities and psychopharmacological treatment on the clinical outcomes of a cohort of FAs of the general medical practice in Italy. The study included 75 FAs assessed by the Structured Clinical Interview for DSM-5, Clinical Global Impression, Global Assessment Functioning, and Illness Behavior Inventory, administered at baseline (T0) and after 3 months (T1). Data were analyzed on the bases of the presence of any mental disorder and selective serotonin reuptake inhibitor (SSRI) treatment, with respect to other psychopharmacological treatments. Results showed better outcomes among patients with a mental disorder, particularly anxiety, depression, and somatic symptoms disorders, and when under SSRI treatment. Our findings corroborate the role of psychiatric comorbidity on frequent attendance in the context of general clinical practice with a positive outcome when receiving appropriate treatment with SSRI.

Recognition and Treatment of Psychiatric Emergencies for Health Care Providers in the Emergency Department: Panic Attack, Panic Disorder, and Adverse Drug Reactions

Mental health disorders are common in the United States and may cause significant disturbances in all aspects of a person's life. Individuals with mental health disorders often present to emergency departments for health care. Recognizing and managing common psychiatric emergencies may be challenging for non-mental health providers. The Diagnostic Statistical Manual-5 diagnostic criteria will be discussed and reviewed for panic attack and panic disorder. Both pharmacologic and nonpharmacologic treatment strategies will also be addressed. Adverse drug reactions associated with antipsychotics and selective serotonin reuptake inhibitors are another common psychiatric emergency that will be examined, offering potential management strategies. The objective of this clinical manuscript is to educate emergency health care providers about specific psychiatric emergencies, including panic attack, panic disorder, and adverse drug reactions associated with mental health treatment medications.

A comprehensive model of predictors of suicide attempt in individuals with panic disorder: Results from a national 3-year prospective study

OBJECTIVE

People with panic disorder are at increased risk of suicide. Multiple factors influence their risk suggesting a need to combine them into an integrative model to develop more effective suicide prevention strategies for this population. In this report, we sought to build a comprehensive model of the 3-year risk of suicide attempt in individuals with panic disorder using a longitudinal nationally representative study, the National Epidemiologic Survey on Alcohol and Related Conditions (NESARC; wave 1, 2001-2002; wave 2, 2004-2005).

METHOD

We used structural equation modeling to simultaneously examine effects of six broad groups of clinical factors previously identified as potential predictors of suicide attempt in adults with panic disorder: 1) severity of panic disorder, 2) severity of comorbidity, 3) prior history of suicide attempt, 4) family history of psychiatric disorders, 5) sociodemographic characteristics and 6) treatment-seeking behavior.

RESULTS

The 3-year prevalence rate of suicide attempt was 4.6%. A general psychopathology factor, lower physical health-related quality of life, prior suicide attempt and a greater number of stressful life events at baseline significantly and independently predicted suicide attempt between the two waves (p < .05). R-square of the models ranged from 0.47 to 0.50.

CONCLUSION

This model may help inform future research and identify high-risk individuals among adults with panic disorder.

Relationships Between Somatic Symptoms and Panic-Agoraphobic Spectrum Among Frequent Attenders of the General Practice in Italy

Frequent attenders (FAs) of general practitioners (GPs) often complain of nonspecific physical symptoms that are difficult to define according to typical medical syndromes criteria but could be acknowledged as atypical manifestations of mental disorders. We investigated the possible correlation between somatic symptoms and panic-agoraphobic spectrum symptoms in a sample of 75 FAs of GPs in Italy, with particular attention to the impact on functional impairment. Assessments included the Patient Health Questionnaire, Panic-Agoraphobic Spectrum-Self-Report (PAS-SR) lifetime version, Global Assessment of Functioning, and Clinical Global Impression. The PAS-SR total and domains scores were significantly higher among low-functioning FAs, especially anxious somatizations, hypochondriasis, anxious expectation, and reassurance orientation domains, suggesting this undetected symptom may determine the selective attention to the physical symptoms, illness-phobic/hypochondriac elaboration, and GP frequent attendance, often aimed at searching for reassurance, leading to severe impact on overall functioning and often inefficacious treatments.

Panic disorder respiratory subtype: psychopathology and challenge tests - an update

Panic disorder (PD) pathophysiology is very heterogeneous, and the discrimination of distinct subtypes could be very useful. A subtype based on respiratory symptoms is known to constitute a specific subgroup. However, evidence to support the respiratory subtype (RS) as a distinct subgroup of PD with a well-defined phenotype remains controversial. Studies have focused on characterization of the RS based on symptoms and response to CO2. In this line, we described clinical and biological aspects focused on symptomatology and CO2 challenge tests in PD RS. The main symptoms that characterize RS are dyspnea (shortness of breath) and a choking sensation. Moreover, patients with the RS tended to be more responsive to CO2 challenge tests, which triggered more panic attacks in this subgroup. Future studies should focus on discriminating respiratory-related clusters and exploring psychophysiological and neuroimaging outcomes in order to provide robust evidence to confirm RS as a distinct subtype of PD.

Does Personality Matter? Temperament and Character Dimensions in Panic Subtypes

Introduction

Symptomatic heterogeneity in the clinical presentation of Panic Disorder (PD) has lead to several attempts to identify PD subtypes; however, no studies investigated the association between temperament and character dimensions and PD subtypes. The study was aimed to verify whether personality traits were differentially related to distinct symptom dimensions.

Methods

Seventy-four patients with PD were assessed by the Mini-International Neuropsychiatric Interview (M.I.N.I.), and the Temperament and Character Inventory (T.C.I.). Thirteen panic symptoms from the M.I.N.I. were included in a factor analysis with varimax rotation. A correlation analysis (Pearson's correlation), a linear regression analysis, and a forward stepwise regression analysis between the identified factors and T.C.I. variables were performed for evaluating the association between panic subtypes and personality features.

Results

Three factors were obtained: "Somato-dissociative", "Respiratory", and "Cardiologic" explaining respectively 18.31%, 13.71%, and 12.78% of the total variance. Correlations analyses showed that only "Somato-dissociative" factor was significantly correlated with T.C.I. "Self-directedness" (p<0.0001) and "Cooperativeness" (p=0.009) variables. Results from the regression analysis indicate that the predictor models account for 33.3% and 24.7% of the total variance respectively in "Somatic-dissociative" (p<0.0001) and "Cardiologic" (p=0.007) factors, while they do not show statistically significant effects on "Respiratory" factor (p=0.222). After performing stepwise regression analysis, "Self-directedness" resulted the unique predictor of "Somato-dissociative" factor (R²=0.186; β=-0.432; t=-4.061; p<0.0001).

Conclusion

Current results, although preliminary, suggest the importance of assessing personality and temperament features that may be potentially related to poor treatment response for a better understanding and characterization of PD subtypes.

Identifying Patterns in Complex Field Data

Abstract. Ambulatory assessment methods are well suited to examine how patients with panic disorder and agoraphobia (PD/A) undertake situational exposure. But under complex field conditions of a complex treatment protocol, the variability of data can be so high that conventional analytic approaches based on group averages inadequately describe individual variability. To understand how fear responses change throughout exposure, we aimed to demonstrate the incremental value of sorting HR responses (an index of fear) prior to applying averaging procedures. As part of their panic treatment, 85 patients with PD/A completed a total of 233 bus exposure exercises. Heart rate (HR), global positioning system (GPS) location, and self-report data were collected. Patients were randomized to one of two active treatment conditions (standard exposure or fear-augmented exposure) and completed multiple exposures in four consecutive exposure sessions. We used latent class cluster analysis (CA) to cluster heart rate (HR) responses collected at the start of bus exposure exercises (5 min long, centered on bus boarding). Intra-individual patterns of assignment across exposure repetitions were examined to explore the relative influence of individual and situational factors on HR responses. The association between response types and panic disorder symptoms was determined by examining how clusters were related to self-reported anxiety, concordance between HR and self-report measures, and bodily symptom tolerance. These analyses were contrasted with a conventional analysis based on averages across experimental conditions. HR responses were sorted according to form and level criteria and yielded nine clusters, seven of which were interpretable. Cluster assignment was not stable across sessions or treatment condition. Clusters characterized by a low absolute HR level that slowly decayed corresponded with low self-reported anxiety and greater self-rated tolerance of bodily symptoms. Inconsistent individual factors influenced HR responses less than situational factors. Applying clustering can help to extend the conventional analysis of highly variable data collected in the field. We discuss the merits of this approach and reasons for the non-stereotypical pattern of cluster assignment across exposures.