Stress-Induced Autonomic Dysfunction is Associated With Mental Stress-Induced Myocardial Ischemia in Patients With Coronary Artery Disease.

BACKGROUND: Mental stress-induced myocardial ischemia (MSIMI) is associated with adverse cardiovascular outcomes in individuals with coronary artery disease, but the mechanisms underlying this phenomenon are unknown. We examined the relationship between stress-induced autonomic dysfunction, measured by low heart rate variability (HRV) in response to stress, and MSIMI in patients with stable coronary artery disease. We hypothesized that stress-induced autonomic dysfunction is associated with higher odds of MSIMI. METHODS: In 735 participants with stable coronary artery disease, we measured high- and low-frequency HRV in 5-minute intervals before and during a standardized laboratory-based speech stressor using Holter monitoring. HRV at rest and stress were categorized into low HRV (first quartile) versus high HRV (second to fourth quartiles); the low category was used as an indicator of autonomic dysfunction. Multivariable logistic regression models were used to examine the association of autonomic dysfunction with MSIMI. RESULTS: The mean age was 58 (SD, ±10) years, 35% were women, 44% were Black participants, and 16% developed MSIMI. Compared with high HRV during stress, low HRV during stress (both high and low frequencies) was associated with higher odds of MSIMI after adjusting for demographic and clinical factors (odds ratio for high-frequency HRV, 2.1 [95% CI, 1.3-3.3]; odds ratio for low-frequency HRV, 2.1 [95% CI, 1.3-3.3]). Low-frequency HRV at rest was also associated with MSIMI but with slightly reduced effect estimates. CONCLUSIONS: In individuals with coronary artery disease, mental stress-induced autonomic dysfunction may be a mechanism implicated in the causal pathway of MSIMI.

Quantifying Posttraumatic Stress Disorder Symptoms During Traumatic Memories Using Interpretable Markers of Respiratory Variability.

BACKGROUND: Posttraumatic stress disorder (PTSD) causes heightened fight-or-flight responses to traumatic memories (i.e., hyperarousal). Although hyperarousal is hypothesized to cause irregular breathing (i.e., respiratory variability), no quantitative markers of respiratory variability have been shown to correspond with PTSD symptoms in humans. OBJECTIVE: In this study, we define interpretable markers of respiration pattern variability (RPV) and investigate whether these markers respond during traumatic memories, correlate with PTSD symptoms, and differ in patients with PTSD. METHODS: We recruited 156 veterans from the Vietnam-Era Twin Registry to participate in a trauma recall protocol. From respiratory effort and electrocardiogram measurements, we extracted respiratory timings and rate using a robust quality assessment and fusion approach. We then quantified RPV using the interquartile range and compared RPV between baseline and trauma recall conditions, correlated PTSD symptoms to the difference between trauma recall and baseline RPV (i.e., ∆RPV), and compared ∆RPV between patients with PTSD and trauma-exposed controls. Leveraging a subset of 116 paired twins, we then uniquely controlled for factors shared by co-twins via within-pair analysis for further validation. RESULTS: We found RPV was increased during traumatic memories (p .001), ∆ RPV was positively correlated with PTSD symptoms (p .05), and patients with PTSD exhibited higher ∆ RPV than trauma-exposed controls (p . 05). CONCLUSIONS: This paper is the first to elucidate RPV markers that respond during traumatic memories, especially in patients with PTSD, and correlate with PTSD symptoms. SIGNIFICANCE: These findings encourage future studies outside the clinic, where interpretable markers of respiratory variability are used to track hyperarousal.

Towards Quantifying Stress in Patients with a History of Myocardial Infarction: Validating ECG-Derived Patch Features.

Patients with prior myocardial infarction (MI) have an increased risk of experiencing a secondary event which is exacerbated by mental stress. Our team has developed a miniaturized patch with the capability to capture electrocardiogram (ECG), seismocardiogram (SCG) and photoplethysmogram (PPG) signals which may provide multimodal information to characterize stress responses within the post-MI population in ambulatory settings. As ECG-derived features have been shown to be informative in assessing the risk of MI, a critical first step is to ensure that the patch ECG features agree with gold-standard devices, such as the Biopac. However, this is yet to be done in this population. We, thus, performed a comparative analysis between ECG-derived features (heart rate (HR) and heart rate variability (HRV)) of the patch and Biopac in the context of stress. Our dataset contained post-MI and healthy control subjects who participated in a public speaking challenge. Regression analyses for patch and Biopac HR and HRV features (RMSSD, pNN50, SD1/SD2, and LF/HF) were all significant (p<0.001) and had strong positive correlations (r>0.9). Additionally, Bland-Altman analyses for most features showed tight limits of agreement: 0.999 bpm (HR), 11.341 ms (RMSSD), 0.07% (pNN50), 0.146 ratio difference (SD1/SD2), 0.750 ratio difference (LF/HF).Clinical relevance- This work demonstrates that ECG-derived features obtained from the patch and Biopac are in agreement, suggesting the clinical utility of the patch in deriving quantitative metrics of physiology during stress in post-MI patients. This has the potential to improve post-MI patients' outcomes, but needs to be further evaluated.