Dataset Information

Altered Low Frequency Heart Rate Variability Associated with Agoraphobia in Panic Disorder: A Retrospective Study.

ABSTRACT:

Purpose

This study aimed to compare the clinical features of panic disorder (PD) with comorbid agoraphobia to those of PD alone. We focused on autonomic nervous system (ANS) alterations reflected in heart rate variability (HRV) and executive function deficits reflected in the Stroop test.

Materials and methods

We retrospectively compared psychometric features, Stroop test results, and resting-state HRV across three groups: a subclinical group with anxiety attack history, a PD group without agoraphobia, and a PD group with agoraphobia. The subclinical group included 10 male and 34 female, the PD without agoraphobia group included 17 male and 19 female, and the PD with agoraphobia group included 11 male and 18 female.

Results

The PD with agoraphobia group had higher Symptom Checklist-95 scores than the other groups. Both PD groups had longer reaction times in the Stroop test than the subclinical group. There were no significant differences in HRV parameters between the PD groups with and without agoraphobia. Compared with the subclinical group, the PD with agoraphobia group showed significantly lower values of the natural logarithm of low-frequency HRV.

Conclusion

Our results do not support that executive function deficits and ANS alterations are more pronounced with comorbid agoraphobia among PD groups. However, PD with agoraphobia patients showed more complex and severe clinical symptoms in their self-reports. Compared with the subclinical group, PD patients with agoraphobia showed specific features in the natural logarithm of low-frequency HRV. Our findings suggest that agoraphobia comorbidity should be considered when evaluating or treating patients with PD.

SUBMITTER: Kim M

PROVIDER: S-EPMC10613766 | biostudies-literature | 2023 Nov

REPOSITORIES: biostudies-literature

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Publications

Altered Low Frequency Heart Rate Variability Associated with Agoraphobia in Panic Disorder: A Retrospective Study.

Kim Minjung M Kim Jihye J Park Haein H Park Jin Young JY Lee Deokjong D

Yonsei medical journal 20231101 11

<h4>Purpose</h4>This study aimed to compare the clinical features of panic disorder (PD) with comorbid agoraphobia to those of PD alone. We focused on autonomic nervous system (ANS) alterations reflected in heart rate variability (HRV) and executive function deficits reflected in the Stroop test.<h4>Materials and methods</h4>We retrospectively compared psychometric features, Stroop test results, and resting-state HRV across three groups: a subclinical group with anxiety attack history, a PD grou ...[more]

PMID: 37880848

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Project description:BackgroundStress is a significant risk factor for psychiatric disorders such as major depressive disorder (MDD) and panic disorder (PD). This highlights the need for advanced stress-monitoring technologies to improve treatment. Stress affects the autonomic nervous system, which can be evaluated via heart rate variability (HRV). While machine learning has enabled automated stress detection via HRV in healthy individuals, its application in psychiatric patients remains underexplored. This study evaluated the feasibility of using machine-learning algorithms to detect stress automatically in MDD and PD patients, as well as healthy controls (HCs), based on HRV features.MethodsThe study included 147 participants (MDD: 41, PD: 47, HC: 59) who visited the laboratory up to five times over 12 weeks. HRV data were collected during stress and relaxation tasks, with 20 HRV features extracted. Random forest and multilayer perceptron classifiers were applied to distinguish between the stress and relaxation tasks. Feature importance was analyzed using SHapley Additive exPlanations, and differences in HRV between the tasks (ΔHRV) were compared across groups. The impact of personalized longitudinal scaling on classification accuracy was also assessed.ResultsRandom forest classification accuracies were 0.67 for MDD, 0.69 for PD, and 0.73 for HCs, indicating higher accuracy in the HC group. Longitudinal scaling improved accuracies to 0.94 for MDD, 0.90 for PD, and 0.96 for HCs, suggesting its potential in monitoring patients' conditions using HRV. The HC group demonstrated greater ΔHRV fluctuation in a larger number of and more significant features than the patient groups, potentially contributing to higher accuracy. Multilayer perceptron models provided consistent results with random forest, confirming the robustness of the findings.ConclusionThis study demonstrated that differentiating between stress and relaxation was more challenging in the PD and MDD groups than in the HC group, underscoring the potential of HRV metrics as stress biomarkers. Psychiatric patients exhibited altered autonomic responses, which may influence their stress reactivity. This indicates the need for a tailored approach to stress monitoring in these patient groups. Additionally, we emphasized the significance of longitudinal scaling in enhancing classification accuracy, which can be utilized to develop personalized monitoring technologies for psychiatric patients.

Dataset Information

Altered Low Frequency Heart Rate Variability Associated with Agoraphobia in Panic Disorder: A Retrospective Study.

Purpose

Materials and methods

Results

Conclusion

Publications

Altered Low Frequency Heart Rate Variability Associated with Agoraphobia in Panic Disorder: A Retrospective Study.

Similar Datasets

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