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

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.

Counterfactual inference with latent variable and its application in mental health care

This paper deals with the problem of modeling counterfactual reasoning in scenarios where, apart from the observed endogenous variables, we have a latent variable that affects the outcomes and, consequently, the results of counterfactuals queries. This is a common setup in healthcare problems, including mental health. We propose a new framework where the aforementioned problem is modeled as a multivariate regression and the counterfactual model accounts for both observed and a latent variable, where the latter represents what we call the patient individuality factor (\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\upvarphi $$\end{document}φ). In mental health, focusing on individuals is paramount, as past experiences can change how people see or deal with situations, but individuality cannot be directly measured. To the best of our knowledge, this is the first counterfactual approach that considers both observational and latent variables to provide deterministic answers to counterfactual queries, such as: what if I change the social support of a patient, to what extent can I change his/her anxiety? The framework combines concepts from deep representation learning and causal inference to infer the value of \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\upvarphi $$\end{document}φ and capture both non-linear and multiplicative effects of causal variables. Experiments are performed with both synthetic and real-world datasets, where we predict how changes in people’s actions may lead to different outcomes in terms of symptoms of mental illness and quality of life. Results show the model learns the individually factor with errors lower than 0.05 and answers counterfactual queries that are supported by the medical literature. The model has the potential to recommend small changes in people’s lives that may completely change their relationship with mental illness.

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.

Disrupted Rhythmicity and Vegetative Functions Relate to PTSD and Gender in Earthquake Survivors

Background: Increasing evidence indicates that survivors to traumatic events may show disruption of sleep pattern, eating and sexual behaviors, and somatic symptoms suggestive of alterations of biorhythmicity and vegetative functions. Therefore, the aim of this study was to investigate these possible alterations in a sample of survivors in the aftermath of earthquake exposure, with particular attention to gender differences and impact of post-traumatic stress disorder (PTSD). Methods: High school senior students, who had been exposed to the 2009 L'Aquila earthquake, were enrolled 21 months after the traumatic event and evaluated by the Trauma and Loss Spectrum Self-Report to investigate PTSD rates and by a domain of the Mood Spectrum Self-Report-Lifetime Version (MOODS-SR), to explore alterations in circadian/seasonal rhythms and vegetative functions. Results: The rates of endorsement of MOODS-SR rhythmicity and vegetative functions domain and subdomain scores were significantly higher in survivors with PTSD with respect to those without it. Among all earthquake survivors, women reported higher scores than men on the rhythmicity and vegetative functions domain and subdomain scores, except for the rhythmicity and sexual functions ones. Female survivors without PTSD showed significantly higher scores than men in the rhythmicity and vegetative functions total scores and the sleep and weight and appetite subdomains. Potentially traumatic events burden predicted rhythmicity and vegetative functions impairment, with a moderation effect of re-experiencing symptoms. Conclusions: We report impairments in rhythmicity, sleep, eating, and sexual and somatic health in survivors to a massive earthquake, particularly among subjects with PTSD and higher re-experiencing symptoms, with specific gender-related differences. Evaluating symptoms of impaired rhythmicity and vegetative functions seems essential for a more accurate assessment and clinical management of survivors to a mass trauma.