Identification and medical utilization of newly diagnosed panic disorder: A Nationwide case-control study

Prevalence and Predictive Factors of Panic Disorder among Adults in Saudi Arabia: A Cross-Sectional Study

Panic disorder (PD) is a severe anxiety disorder characterized by recurrent and unexpected panic attacks that cause intense distress. Despite the high prevalence of panic disorder and its significant impact on life, limited research has been conducted on its prevalence and their associated factors in Saudi Arabia. This study seeks to contribute to the understanding of PD among adults in Saudi Arabia by examining its prevalence and associated factors, using an online survey method. A validated questionnaire-based cross-sectional study was conducted targeting 1276 Saudi adults. Data were collected electronically via Google Forms from the eligible participants. The questionnaire comprised three sections: sociodemographic information, medical history, and a validated diagnostic tool for PD. The prevalence of PD among Saudi adults was 13.1%. Most individuals with PD experienced their first panic attack before the age of 18. Only 38.3% individuals with PD sought medical attention, and approximately one-third of those who sought help did not receive a diagnosis. Multiple logistic regression analysis revealed that significant risk factors for PD included being female; having chronic health problems, a comorbid psychiatric disorder, a high body mass index; and experiencing suicidal ideation (P < 0.05). The highest risk was associated with chronic diseases (adjusted odds ratio = 3.1, 95% confidence interval: 2.1-4.6). This study demonstrates that PD is a prevalent and debilitating mental health condition among Saudi Arabian adults. Non-mental health physicians should be aware of PD, as many cases remain undiagnosed.

Serum BDNF levels and state anxiety are associated with somatic symptoms in patients with panic disorder

Background

We aimed to explore the predictive role of serum BDNF and anxiety-related variables in changes in somatic symptoms post-escitalopram treatment in panic disorder (PD) patients.

Methods

Ninety PD patients and 99 healthy controls (HCs) were enrolled. PD patients received an 8-week escitalopram treatment. All patients were administered the Panic Disorder Severity Scale-Chinese Version (PDSS-CV) and State-Trait Anxiety Inventory (STAI) to assess panic and anxiety-related symptoms, respectively. Patient Health Questionnaire 15-item scale (PHQ-15) was performed to measure somatic symptoms, and the blood sample was collected to detect serum BDNF levels in all participants. We performed partial correlation analysis and multiple linear regression to explore correlates of PHQ-15 and predictors of PHQ-15 changes post-escitalopram treatment after controlling for age, gender, education levels (set as a dummy variable), the current duration, comorbid AP, and/or GAD.

Results

Compared to HCs, PD patients had lower serum BDNF levels and higher PHQ-15 scores that could be improved post-escitalopram treatment. Lower baseline STAI state (b = -0.07, p = 0.004), and PDSS-CV scores (b = -0.25, p = 0.007), but higher baseline serum BDNF levels (b = 0.35, p = 0.007) contributed to the prediction of PHQ-15 changes post-escitalopram treatment.

Conclusion

State anxiety, serum BDNF levels, and panic severity could predict changes in somatic symptoms post-escitalopram treatment, our results highlighted that serum BDNF could serve as a biological indicator for improving somatic symptoms in PD patients.

Premature death and causes of death among patients with panic disorder and comorbid psychiatric disorders: A nationwide cohort study

OBJECTIVES

Panic disorder (PD) is associated with high psychiatric and physical comorbidity, but the cause of mortality has not been well studied. This study investigated mortality rates and causes of death in an Asian cohort with PD.

METHODS

We enrolled a nationwide retrospective cohort of 298,466 persons diagnosed with PD from January 1, 2001, to December 31, 2016. Each cohort member was matched with a comparison one randomly selected from the general population with the same sex, age at entry, and birth year. The data of both the PD cohort and the comparison group were linked with the national mortality database to obtain each individual's mortality status. We used mortality rate ratios (MRRs) to compare mortality risks between the patients with PD and the general population. Stratified analysis of mortality risks was performed based on sex and psychiatric comorbidities.

RESULTS

PD was associated with a slightly increased mortality risk (MRR, 1.14 [99% CI, 1.11-1.17]). The risk of unnatural death (MRR, 2.83 [99% CI, 2.59-3.10]) was significantly higher among the individuals with PD than among the general population, whereas the risk of overall natural death across all categories was not (MRR, 1.01 [99% CI, 0.98-1.04]). The mortality risk was the highest for suicide (MRR, 4.94 [99% CI, 4.32-5.72]) and was higher in women (MRR, 6.37 [99% CI, 5.25-7.96]) than in men (MRR, 3.77 [99% CI, 3.14-4.64]). Comorbid substance use disorders increased the risk of mortality from natural (MRR, 3.23 [99% CI, 2.59-4.14]) and unnatural (MRR, 9.45 [99% CI, 6.29-17.85]) causes.

CONCLUSION

PD was associated with increased all-cause mortality, especially suicide. Substance use further increased mortality risk in persons with PD. Targeted treatment for substance use and suicide prevention are essential among persons with PD.

Panic disorder in general medical practice- A narrative review

The under-or misdiagnosis, and symptomatic treatment of the panic disorder (PD), despite high prevalent medical illness, is common among non-psychiatric physicians. The non-psychiatrist physician’s role is vital in the care of PD as most patients initially approach general medical settings for medical help, including primary care. However, a significant proportion is undiagnosed and undergoes either unnecessary investigation, misdiagnosed, or mismanaged even among post-Coronary Artery Bypass Grafting patients, which profoundly affects the patients functioning and quality of life. This article aims to provide overviews of relevant epidemiological aspects, presenting features across medical specialties with respective diagnostic dilemmas, assessment, and management of the PD in their general medical settings, including emergency visits. Apart from psychiatrists, this will also assist non-psychiatrist physicians across all medical specialties, including general practitioners, to understand, identify, and provide the first line evidence-based pharmacotherapy and address the unmet need of patients with PD in their day-to-day busy clinical practice. This paper also provides a referral guide for non-psychiatrist physicians to refer to psychiatrists for further management after their first-line management.

Panic attack prediction using wearable devices and machine learning: Development and cohort study (Preprint)

Background

A panic attack (PA) is an intense form of anxiety accompanied by multiple somatic presentations, leading to frequent emergency department visits and impairing the quality of life. A prediction model for PAs could help clinicians and patients monitor, control, and carry out early intervention for recurrent PAs, enabling more personalized treatment for panic disorder (PD).

Objective

This study aims to provide a 7-day PA prediction model and determine the relationship between a future PA and various features, including physiological factors, anxiety and depressive factors, and the air quality index (AQI).

Methods

We enrolled 59 participants with PD (Diagnostic and Statistical Manual of Mental Disorders, 5th edition, and the Mini International Neuropsychiatric Interview). Participants used smartwatches (Garmin Vívosmart 4) and mobile apps to collect their sleep, heart rate (HR), activity level, anxiety, and depression scores (Beck Depression Inventory [BDI], Beck Anxiety Inventory [BAI], State-Trait Anxiety Inventory state anxiety [STAI-S], State-Trait Anxiety Inventory trait anxiety [STAI-T], and Panic Disorder Severity Scale Self-Report) in their real life for a duration of 1 year. We also included AQIs from open data. To analyze these data, our team used 6 machine learning methods: random forests, decision trees, linear discriminant analysis, adaptive boosting, extreme gradient boosting, and regularized greedy forests.

Results

For 7-day PA predictions, the random forest produced the best prediction rate. Overall, the accuracy of the test set was 67.4%-81.3% for different machine learning algorithms. The most critical variables in the model were questionnaire and physiological features, such as the BAI, BDI, STAI, MINI, average HR, resting HR, and deep sleep duration.

Conclusions

It is possible to predict PAs using a combination of data from questionnaires and physiological and environmental data.

Associations between brain-derived neurotrophic factor and cognitive impairment in panic disorder

INTRODUCTION

Our study was designed to examine the relationship between Brain-Derived Neurotrophic Factor (BDNF) genotypes (rs6265, Val66Met), BDNF plasma levels, and cognitive impairment in Chinese patients with panic disorder (PD).

METHODS

Total 85 patients with PD and 91 healthy controls finally completed all assessments. The severity of panic symptoms and whole anxiety of PD was measured by Panic Disorder Severity Scale-Chinese Version (PDSS-CV) and Hamilton Anxiety Scale (HAMA-14). Montreal Cognitive Assessment (MoCA) and some neurocognitive measures were conducted to evaluate the cognitive performance. All participants were detected for the plasma BDNF levels and BDNF Val66Met polymorphism before assessment and treatment.

RESULTS

No significant differences were found in the BDNF allele frequencies and the BDNF genotype distributions between healthy controls and PD patients. BDNF Met/Met genotype was associated with lower BDNF plasma levels in PD patients, and PD patients with BDNF Met/Met genotype had the lower scores in the attention and speed of processing domains compared to those with Val/Val and Met/Val genotype (p's < .05). Among PD patients, the BDNF plasma levels showed moderate positive correlations with Stroop interference (r = .60, p < .001). Using the MoCA data, the BDNF plasma levels were correlated with delayed memory (r = .50, p < .001), verbal learning (r = .45, p < .001), and total scores of MoCA (r = .51, p < .001).

CONCLUSIONS

The BDNF Met/Met genotype may be associated with lower BDNF plasma levels and cognitive impairments in PD patients.

Videoconferencing Psychotherapy for Panic Disorder and Agoraphobia: Outcome and Treatment Processes From a Non-randomized Non-inferiority Trial

BACKGROUND

In the context of the COVID-19 pandemic, legislations are being modified around the world to allow patients to receive mental health services through telehealth. Unfortunately, there are no large clinical trial available to reliably document the efficacy of delivering videoconferencing psychotherapy (VCP) for people with panic disorder and agoraphobia (PDA) and whether basic psychotherapeutic processes are altered.

METHODS

This 2-arm intent-to-treat non-inferiority study reports on a clinical trial on VCP and documents how therapeutic working alliance and motivation toward psychotherapy are associated to treatment outcome. We hypothesized that VCP would not be inferior to standard face-to-face (FF) cognitive behavior therapy for PDA. No specific hypothesis was stated to address working alliance and treatment mechanisms. VCP was compared to a gold-standard psychotherapy treatment for PDA, which was delivered either in person or in videoconference, with a strict tolerance criterion of about 2 points on the primary outcome measure. Seventy one adult patients were recruited. Measures of working alliance were collected after the first, fifth, and last session. Motivation toward therapy at pre-treatment and working alliance after the fifth therapy session were used as predictors of treatment outcome and compared with change in dysfunctional beliefs toward bodily sensations.

RESULTS

Panic disorder, agoraphobia, fear of sensations and depressed mood all showed significant improvements and large effect-sizes from pre to post-treatment. Gains were maintained at follow-up. No significant differences were found between VCP and FF, and effect sizes were trivial for three of the four outcome measures. Non-inferiority tests confirmed that VCP was no less effective than FF therapy on the primary outcome measure and two of the three secondary outcome measures. Working alliance was very strong in VCP and did not statistically differ from FF. Working alliance and motivation did not predict treatment outcome, which was significantly predicted by the reduction in dysfunctional beliefs. The strength of the therapeutic bond was correlated with change in dysfunctional beliefs.

CONCLUSION

Mental health professionals can use VCP to provide services to patients with PDA. Building and maintaining a sound working alliance should not be a source concern. Practical recommendations are formulated.

ISRCTN TRIAL REGISTRATION NUMBER

ISRCTN76456442.