Psychological Distress and Arrhythmia: Risk Prediction and Potential Modifiers

The connection between the heart and the brain has long been anecdotally recognized but has systematically been studied only relatively recently. Cardiac arrhythmias, especially ventricular arrhythmias that can lead to sudden cardiac death, remain a major public health concern and there is mounting evidence that psychological distress plays a critical role both as a predictor of high-risk cardiac substrate and as an inciting trigger. The transient, unpredictable nature of emotions and cardiac arrhythmias has made their study challenging, but evolving technologies in monitoring and imaging along with larger epidemiological data sets have encouraged more sophisticated studies examining this relationship. Here we review the research on psychological distress including anger, depression and anxiety on cardiac arrhythmias, insights into proposed mechanisms, and potential avenues for future research

Antipsychotic medications and sudden cardiac arrest: More than meets the eye?

Sudden cardiac arrest (SCA) remains an important public health problem and is stubbornly difficult to predict or prevent. A growing literature has emerged studying psychiatric conditions, such as depression and schizophrenia, and risk of arrhythmia and SCA.1–3 This field is challenging from an epidemiologic perspective, partly because of the rarity of SCA events in the general population without known heart disease and the potential confounding factors that may influence findings.4 For instance, there is increased recognition that treatments for mental illness may themselves raise cardiac risk

Don't worry, be happy: positive affect and reduced 10-year incident coronary heart disease: The Canadian Nova Scotia Health Survey

AIMS: Positive affect is believed to predict cardiovascular health independent of negative affect. We examined whether higher levels of positive affect are associated with a lower risk of coronary heart disease (CHD) in a large prospective study with 10 years of follow-up. METHODS AND RESULTS: We examined the association between positive affect and cardiovascular events in 1739 adults (862 men and 877 women) in the 1995 Nova Scotia Health Survey. Trained nurses conducted Type A Structured Interviews, and coders rated the degree of outwardly displayed positive affect on a five-point scale. To test that positive affect predicts incident CHD when controlling for depressive symptoms and other negative affects, we used as covariates: Center for Epidemiological Studies Depressive symptoms Scale, the Cook Medley Hostility scale, and the Spielberger Trait Anxiety Inventory. There were 145 (8.3%) acute non-fatal or fatal ischaemic heart disease events during the 14 916 person-years of observation. In a proportional hazards model controlling for age, sex, and cardiovascular risk factors, positive affect predicted CHD (adjusted HR, 0.78; 95% CI 0.63-0.96 per point; P = 0.02), the covariate depressive symptoms continued to predict CHD as had been published previously in the same patients (HR, 1.04; 95% CI 1.01-1.07 per point; P = 0.004) and hostility and anxiety did not (both P > 0.05). CONCLUSION: In this large, population-based study, increased positive affect was protective against 10-year incident CHD, suggesting that preventive strategies may be enhanced not only by reducing depressive symptoms but also by increasing positive affect

Ibutilide Increases the Variability and Complexity of Atrial Fibrillation Electrograms: Antiarrhythmic Insights Using Signal Analyses

Introduction Intravenous ibutilide is used to convert atrial fibrillation (AF) to sinus rhythm (SR) due to its Class III antiarrhythmic mechanisms. However, the effects of ibutilide on local electrograms (EGMs) during AF have not been elucidated. Methods and Results We used EGM analysis techniques to characterize how ibutilide administration changes the frequency, morphology, and repeatability of AF EGM signals, thereby providing insight into ibutilide's antiarrhythmic mechanism of action. AF recordings were collected from 21 patients with AF, both before and after ibutilide administration. The effects of ibutilide on the following AF EGM parameters were assessed: (1) dominant frequency (DF), (2) variations in EGM amplitude and overall morphology, (3) repetition of EGM patterns, and (4) complexity of the AF frequency spectra. When comparing pre- versus post-ibutilide administration EGMs, DF decreased from 5.45 Hz to 4.02 Hz (P < 0.0001). There was an increase in the variability of both AF EGM amplitudes (P = 0.003) and overall AF EGM morphologies (P = 0.003). AF EGM pattern repetitiveness decreased (P = 0.01), and the AF frequency spectral profile manifested greater complexity (P = 0.02). Conclusions Novel EGM signal analysis techniques reveal that ibutilide administration causes increased complexity in the atrial electrical activation pattern with decreasing rate. These findings may be explained by the progressive destabilization of higher frequency, more homogeneous primary drivers of AF over the course of ibutilide administration, and/or less uniform propagation of atrial activation, until AF maintenance becomes more difficult and either transforms to atrial tachycardia or terminates to SR

Exposure to tricyclic antidepressants is associated with an increased risk of incident CHD events in a population-based study

Purpose The purpose of this study was to assess the association between antidepressant use and incident coronary heart disease (CHD) events in a sample of individuals without known baseline heart disease. Participants and methods We studied a group of 970 randomly selected community-dwelling adults in the 1995 Nova Scotia Health Survey, who were followed for up to 10 years. Antidepressant usage was classified according to class. Primary outcomes were acute coronary syndrome hospitalizations or cardiac death, determined by centralized, standardized ratings. Results During a follow-up period of 10 years, there were 147 incident CHD events (139 acute coronary syndromes and 8 cardiac deaths) during the 8129 person-years of observation (incidence rate=18.1 events/1000 person-years). In a model controlling for age, sex, Framingham risk score, time to last annual exam, aspirin exposure, and depressive symptoms, an increased risk of CHD events was associated with tricyclic antidepressant exposure (adjusted hazard ratio, 2.10; 95% confidence interval, 1.09–4.06; p =0.027). Conclusion In this prospective population-based study, exposure to tricyclic antidepressants was associated with higher risk of first CHD events

Global Psychological Distress and Risk of Atrial Fibrillation Among Women: The Women's Health Study

Background Symptoms of psychological distress and depression have been associated with risk of ventricular arrhythmias and sudden cardiac death. Their relationship with atrial arrhythmias, however, is less well studied. Methods and Results We sought to assess the long-term relations between psychological distress and risk of atrial fibrillation (AF) in the Women's Health Study of female health professionals. We measured psychological symptoms with the Mental Health Inventory-5. Incident AF was assessed annually and verified through medical records. Among 30 746 women without history of cardiovascular disease or AF, 771 cases of AF occurred during a median follow-up of 125 months (interquartile range, 117–130 months). Global psychological distress was not associated with AF risk in age-stratified (P=0.61 for linear trend) or multivariable proportional-hazards models that included antidepressant use (P=0.34). A proxy measure for depression, consisting of Mental Health Inventory-5 score <53, antidepressant use, or both, was also not associated with AF risk in multivariable models (hazard ratio=0.99; 95% confidence interval, 0.78–1.25; P=0.93). In post hoc analyses of individual symptoms from the Mental Health Inventory-5, positive affect, “feeling happy some/a good bit of the time,” was associated with reduced risk of AF (hazard ratio=0.69; 95% confidence interval, 0.49–0.99; P=0.04); other depressive and anxious symptoms were not. Conclusions In this prospective study of women without known cardiovascular disease, global psychological distress and specific depressive symptoms were unrelated to AF risk

Relations Between QRS|T Angle, Cardiac Risk Factors, and Mortality in the Third National Health and Nutrition Examination Survey (NHANES III)

On the surface electrocardiogram, an abnormally wide QRS|T angle reflects changes in the regional action potential duration profiles and in the direction of the repolarization sequence, which is thought to increase the risk of ventricular arrhythmia. We investigated the relation between an abnormal QRS|T angle and mortality in a nationally representative sample of subjects without clinically evident heart disease. We studied 7,052 participants ≥40 years old in the third National Health and Nutrition Examination Survey with 12-lead electrocardiograms. Those with self-reported or electrocardiographic evidence of a previous myocardial infarction, QRS duration of ≥120 ms, or history of heart failure were excluded. Borderline and abnormal spatial QRS|T angles were defined according to gender-specific 75th and 95th percentiles of frequency distributions. All-cause (1,093 women and 1,191 men) and cardiovascular (462 women and 455 men) mortality during the 14-year period was assessed through linkage with the National Death Index. On multivariate analyses, an abnormal spatial QRS|T angle was associated with an increased hazard ratio (HR) for cardiovascular mortality in women (HR 1.82, 95% confidence interval 1.05 to 3.14) and men (HR 2.21, 95% confidence interval 1.32 to 3.68). Also, the multivariate adjusted HR for all-cause mortality associated with an abnormal QRS|T angle was 1.30 (95% confidence interval 0.95 to 1.78) for women and 1.87 (95% confidence interval 1.29 to 2.7) for men. A borderline QRS|T angle was not associated with an increased risk of all-cause or cardiovascular mortality. In conclusion, an abnormal QRS|T angle, as measured on a 12-lead electrocardiogram, was associated with an increased risk of cardiovascular and all-cause mortality in this population-based sample without known heart disease

Relationship between premature ventricular complexes and depressive symptoms in non-ST-elevation acute coronary syndrome

Aims: Depression is a recognized risk marker for mortality among acute coronary syndrome (ACS) patients. We hypothesized that ventricular arrhythmia detected by inpatient telemetry monitoring is more frequent among ACS patients with elevated depressive symptoms compared to those without depressive symptoms. Methods and results: We analysed data from patients enrolled in a prospective observational study of depression in ACS. Telemetry recordings during the index admission (average recording 21.3±3.0 hours) were analysed for frequent premature ventricular complexes (PVCs), defined as ≥10 per hour. The self-report Beck Depression Inventory (BDI) was used to assess depressive symptoms. Among 200 ACS patients, frequent PVCs were observed in 29% of patients with moderate depressive symptoms (BDI ≥10), 27% of those with mild symptoms (BDI 5–9), and only 11% of those with no/minimal symptoms (p=0.02). Log-transformed PVCs per hour were associated with depressive symptom category (p=0.008). In a multivariable logistic regression model that included age, gender, left ventricular ejection fraction, cardiovascular risk score, heart rate, and QT interval, mild symptoms (OR 3.02, 95% 0.97–9.43, p=0.058) and moderate-severe symptoms (OR 3.94, 95% CI 1.27–12.22, p=0.018) were associated with frequent PVCs. Conclusions: In this sample of ACS patients, depressive symptoms were independently associated with frequent PVCs during inpatient telemetry monitoring

Improved frequency resolution for characterization of complex fractionated atrial electrograms

Background: The dominant frequency of the Fourier power spectrum is useful to analyze complex fractionated atrial electrograms (CFAE), but spectral resolution is limited and uniform from DC to the Nyquist frequency. Herein the spectral resolution of a recently described and relatively new spectral estimation technique is compared to the Fourier radix-2 implementation. Methods: In 10 paroxysmal and 10 persistent atrial fibrillation patients, 216 CFAE were acquired from the pulmonary vein ostia and left atrial free wall (977 Hz sampling rate, 8192 sample points, 8.4 s duration). With these parameter values, in the physiologic range of 3–10 Hz, two frequency components can theoretically be resolved at 0.24 Hz using Fourier analysis and at 0.10 Hz on average using the new technique. For testing, two closely-spaced periodic components were synthesized from two different CFAE recordings, and combined with two other CFAE recordings magnified 2×, that served as interference signals. The ability to resolve synthesized frequency components in the range 3–4 Hz, 4–5 Hz, …, 9–10 Hz was determined for 15 trials each (105 total). Results: With the added interference, frequency resolution averaged 0.29 ± 0.22 Hz for Fourier versus 0.16 ± 0.10 Hz for the new method (p < 0.001). The misalignment error of spectral peaks versus actual values was ±0.023 Hz for Fourier and ±0.009 Hz for the new method (p < 0.001). One or both synthesized peaks were lost in the noise floor 13/105 times using Fourier versus 4/105 times using the new method. Conclusions: Within the physiologically relevant frequency range for characterization of CFAE, the new method has approximately twice the spectral resolution of Fourier analysis, there is less error in estimating frequencies, and peaks appear more readily above the noise floor. Theoretically, when interference is not present, to resolve frequency components separated by 0.10 Hz using Fourier analysis would require an 18.2 s sequence duration, versus 8.4 s with the new method

A new LMS algorithm for analysis of atrial fibrillation signals

Background A biomedical signal can be defined by its extrinsic features (x-axis and y-axis shift and scale) and intrinsic features (shape after normalization of extrinsic features). In this study, an LMS algorithm utilizing the method of differential steepest descent is developed, and is tested by normalization of extrinsic features in complex fractionated atrial electrograms (CFAE). Method Equations for normalization of x-axis and y-axis shift and scale are first derived. The algorithm is implemented for real-time analysis of CFAE acquired during atrial fibrillation (AF). Data was acquired at a 977 Hz sampling rate from 10 paroxysmal and 10 persistent AF patients undergoing clinical electrophysiologic study and catheter ablation therapy. Over 24 trials, normalization characteristics using the new algorithm with four weights were compared to the Widrow-Hoff LMS algorithm with four tapped delays. The time for convergence, and the mean squared error (MSE) after convergence, were compared. The new LMS algorithm was also applied to lead aVF of the electrocardiogram in one patient with longstanding persistent AF, to enhance the F wave and to monitor extrinsic changes in signal shape. The average waveform over a 25 s interval was used as a prototypical reference signal for matching with the aVF lead. Results Based on the derivation equations, the y-shift and y-scale adjustments of the new LMS algorithm were shown to be equivalent to the scalar form of the Widrow-Hoff LMS algorithm. For x-shift and x-scale adjustments, rather than implementing a long tapped delay as in Widrow-Hoff LMS, the new method uses only two weights. After convergence, the MSE for matching paroxysmal CFAE averaged 0.46 ± 0.49μV2/sample for the new LMS algorithm versus 0.72 ± 0.35μV2/sample for Widrow-Hoff LMS. The MSE for matching persistent CFAE averaged 0.55 ± 0.95μV2/sample for the new LMS algorithm versus 0.62 ± 0.55μV2/sample for Widrow-Hoff LMS. There were no significant differences in estimation error for paroxysmal versus persistent data. From all trials, the mean convergence time was approximately 1 second for both algorithms. The new LMS algorithm was useful to enhance the electrocardiogram F wave by subtraction of an adaptively weighted prototypical reference signal from the aVF lead. The extrinsic weighting over 25 s demonstrated that time-varying functions such as patient respiration could be identified and monitored. Conclusions A new LMS algorithm was derived and used for normalization of the extrinsic features in CFAE and for electrocardiogram monitoring. The weighting at convergence provides an estimate of the degree of similarity between two signals in terms of x-axis and y-axis shift and scale. The algorithm is computationally efficient with low estimation error. Based on the results, proposed applications include monitoring of extrinsic and intrinsic features of repetitive patterns in CFAE, enhancement of the electrocardiogram F wave and monitoring of time-varying signal properties, and to quantitatively characterize mechanistic differences in paroxysmal versus persistent AF