Depressive Symptoms and Risk for Sudden Cardiac Death in Stable Coronary Artery Disease

Machine learning models for assessing risk factors affecting health care costs: 12-month exercise-based cardiac rehabilitation

Introduction

Exercise-based cardiac rehabilitation (ECR) has proven to be effective and cost-effective dominant treatment option in health care. However, the contribution of well-known risk factors for prognosis of coronary artery disease (CAD) to predict health care costs is not well recognized. Since machine learning (ML) applications are rapidly giving new opportunities to assist health care professionals' work, we used selected ML tools to assess the predictive value of defined risk factors for health care costs during 12-month ECR in patients with CAD.

Methods

The data for analysis was available from a total of 71 patients referred to Oulu University Hospital, Finland, due to an acute coronary syndrome (ACS) event (75% men, age 61 ± 12 years, BMI 27 ± 4 kg/m2, ejection fraction 62 ± 8, 89% have beta-blocker medication). Risk factors were assessed at the hospital immediately after the cardiac event, and health care costs for all reasons were collected from patient registers over a year. ECR was programmed in accordance with international guidelines. Risk analysis algorithms (cross-decomposition algorithms) were employed to rank risk factors based on variances in their effects. Regression analysis was used to determine the accounting value of risk factors by entering first the risk factor with the highest degree of explanation into the model. After that, the next most potent risk factor explaining costs was added to the model one by one (13 forecast models in total).

Results

The ECR group used health care services during the year at an average of 1,624 ± 2,139€ per patient. Diabetes exhibited the strongest correlation with health care expenses (r = 0.406), accounting for 16% of the total costs (p < 0.001). When the next two ranked markers (body mass index; r = 0.171 and systolic blood pressure; r = - 0.162, respectively) were added to the model, the predictive value was 18% for the costs (p = 0.004). The depression scale had the weakest independent explanation rate of all 13 risk factors (explanation value 0.1%, r = 0.029, p = 0.811).

Discussion

Presence of diabetes is the primary reason forecasting health care costs in 12-month ECR intervention among ACS patients. The ML tools may help decision-making when planning the optimal allocation of health care resources.

Canadian Cardiovascular Society 2023 Guidelines on the Fitness to Drive

Cardiovascular conditions are among the most frequent causes of impairment to drive, because they might induce unpredictable mental state alterations via diverse mechanisms like myocardial ischemia, cardiac arrhythmias, and vascular dysfunction. Accordingly, health professionals are often asked to assess patients' fitness to drive (FTD). The Canadian Cardiovascular Society previously published FTD guidelines in 2003-2004; herein, we present updated FTD guidelines. Because there are no randomized trials on FTD, observational studies were used to estimate the risk of driving impairment in each situation, and recommendations made on the basis of Canadian Cardiovascular Society Risk of Harm formula. More restrictive recommendations were made for commercial drivers, who spend longer average times behind the wheel, use larger vehicles, and might transport a larger number of passengers. We provide guidance for individuals with: (1) active coronary artery disease; (2) various forms of valvular heart disease; (3) heart failure, heart transplant, and left ventricular assist device situations; (4) arrhythmia syndromes; (5) implantable devices; (6) syncope history; and (7) congenital heart disease. We suggest appropriate waiting times after cardiac interventions or acute illnesses before driving resumption. When short-term driving cessation is recommended, recommendations are on the basis of expert consensus rather than the Risk of Harm formula because risk elevation is expected to be transient. These recommendations, although not a substitute for clinical judgement or governmental regulations, provide specialists, primary care providers, and allied health professionals with a comprehensive list of a wide range of cardiac conditions, with guidance provided on the basis of the level of risk of impairment, along with recommendations about ability to drive and the suggested duration of restrictions.

Machine learning models in predicting health care costs in patients with a recent acute coronary syndrome: A prospective pilot study

Background

Health care budgets are limited, requiring the optimal use of resources. Machine learning (ML) methods may have an enormous potential for effective use of health care resources.

Objective

We assessed the applicability of selected ML tools to evaluate the contribution of known risk markers for prognosis of coronary artery disease to predict health care costs for all reasons in patients with a recent acute coronary syndrome (n = 65, aged 65 ± 9 years) for 1-year follow-up.

Methods

Risk markers were assessed at baseline, and health care costs were collected from electronic health registries. The Cross-decomposition algorithms were used to rank the considered risk markers based on their impacts on variances. Then regression analysis was performed to predict costs by entering the first top-ranking risk marker and adding the next-best markers, one by one, to build up altogether 13 predictive models.

Results

The average annual health care costs were €2601 ± €5378 per patient. The Depression Scale showed the highest predictive value (r = 0.395), accounting for 16% of the costs (P = .001). When the next 2 ranked markers (LDL cholesterol, r = 0.230; and left ventricular ejection fraction, r = -0.227, respectively) were added to the model, the predictive value was 24% for the costs (P = .001).

Conclusion

Higher depression score is the primary variable forecasting health care costs in 1-year follow-up among acute coronary syndrome patients. The ML tools may help decision-making when planning optimal utilization of treatment strategies.

The quality of long-term counselling for percutaneous coronary intervention patients: A cross-sectional study

AIM

To compare the long-term counselling quality among the patients visited and not visited at cardiac nurse after percutaneous coronary intervention (PCI) and related factors one to two years after PCI.

DESIGN

An explorative, register-based cross-sectional study.

METHODOLOGY METHODS

A sample was drawn from the one university hospital's procedure register consisted of the patients undergone a PCI (n = 977). The data was collected by Counselling Quality Instrument (CQI) questionnaire by mail, and analysed by basic and multivariate methods.

FINDINGS RESULTS

Of the respondents (n = 459), less than half the patients (48.4%) visited at cardiac nurse one to two years after PCI as instructed in the national current care guidelines. Patients, who visited the nurse (n = 194) had higher satisfaction for counselling than the ones not visited (n = 70). Nevertheless, patients, especially those who had no dyslipidemia, had Unstable Angina Pectoris or Non-ST-elevated myocardial infarction or were out of the workforce, were unsatisfied with counselling, and needed more social support, patient-centred counselling and goal orientating implementation from the cardiac nurse. A half of the PCI patients (51.6%) did not visit the cardiac nurse at the primary health care.

PATIENT OR PUBLIC CONTRIBUTION

Cardiac nurses assisted the members of research group by assessing the questionnaire prior sending it to the patients and patients contributed by completing the questionnaires. We thank both parties for their contribution.

IMPLICATION FOR PROFESSION AND PATIENT CARE

This study demonstrated, that patients out of the workforce and having emergency PCI are in need for better quality counselling, concentrating on social support, patient-centred counselling and goal orientating implementation from the cardiac nurse. Those patients, who did not visit the cardiac nurse, should be offered easier access to cardiac nurse for example, by novel digital solutions.

Coronary Heart Disease and Depression or Anxiety: A Bibliometric Analysis

This study aimed to conduct a bibliometric analysis of published studies on the association between coronary heart disease (CHD) and depression or anxiety. The study also aimed to identify leading authors, institutions, and countries to determine research hotspots and obtain some hints from the speculated future frontiers. Publications about CHD and depression or anxiety between 2004 and 2020 were collected from the Web of Science Core Collection (WOSCC) database. Bibliographic information, such as authorship, country, citation frequency, and interactive visualization, was generated using VOSviewer1.6.16 and CiteSpace5.6.R5. In total, 8,073 articles were identified in the WOSCC database. The United States (2,953 publications), Duke University and Harvard University (214 publications), Psychosomatic Medicine (297 publications), and Denollet Johan. (99 publications) were the most productive country, institutions, journal, and author, respectively. The three hotspots of the research were “The relationship between depression and CHD,” “depression and myocardial infarction,” and “The characteristic of women suffering depression after MI.” The four future research frontiers are predicted to be “treating depression in CHD patients with multimorbidity,” “psychometric properties of instruments for assessing depression and anxiety in CHD patients,” “depression or anxiety in post-PCI patients,” and “other mental diseases in CHD patients.” Bibliometric analysis of the association between CHD and depressive disorders might identify new directions for future research.

Association Between Depression and Clinical Outcomes in Patients With Hypertrophic Cardiomyopathy

Background

Hypertrophic cardiomyopathy (HCM) is considered to be the most common cause of sudden death in young people and is associated with an elevated risk of mood disorders. Depression has emerged as a critical risk factor for development and progression of coronary artery disease; however, the association between depression and HCM outcomes is less clear. We sought to examine the impact of depression on clinical outcomes in patients with HCM.

Methods and Results

Between January 2014 and December 2017, 820 patients with HCM were recruited and followed for an average of 4.2 years. End points were defined as sudden cardiac death (SCD) events and HCM‐related heart failure events. A Chinese version of the Structured Clinical Interview followed the Diagnostic and Statistical Manual of Mental Disorders,Fifth Edition and was used to diagnose depression. During the follow‐up period, SCD events occurred in 75 individuals (21.8 per 1000 person‐years), and HCM‐related heart failure events developed in 149 individuals (43.3 per 1000 person‐years). Kaplan–Meier cumulative incidence curves showed a significant association of depression disorders with SCD events (log‐rank P=0.001) and HCM‐related heart failure events (log‐rank P=0.005). A multivariate Cox regression analysis indicated that depression was an independent predictor of SCD events and HCM‐related heart failure events (41.9 versus 21.7 per 1000 person‐years; adjusted hazard ratio [HR], 1.9; 95% CI, 1.6–2.3; P<0.001; and 69.9 versus 38.6 per 1000 person‐years; HR, 1.8; 95% CI, 1.6–2.1; P<0.001, respectively).

Conclusions

Depression is common among patients with HCM. The diagnosis of depression is significantly and independently associated with an increased risk of SCD events and heart failure events in patients with HCM.

Prevalence and predisposing factors of depressive symptoms in patients with stable coronary artery disease: a cross-sectional single-center study

The incidence of depressive symptoms in patients with stable coronary artery disease (SCAD) has significantly increased. However, its pathogenesis and treatment mechanisms are still incompletely understood. In this study, 144 patients with SCAD were recruited. Depressive symptoms of patients with SCAD were evaluated using Zung Self-Rating Depression Scale during hospitalization, and the patients were categorized into two subgroups: the non-depressive and depressive groups (further divided into mild and moderate/severe depressive groups). The rate of moderate/severe depressive symptoms in patients with SCAD was 18.8%. The mean age of patients in the depressive and mild depressive groups was older than that of those in the non-depressive group, and patients in the moderate/severe depressive group had higher high-density lipoprotein (HDL) and lower creatinine (Cr) levels. Binary logistic regression analysis showed that lower low-density lipoprotein (LDL) levels were significantly associated with increased risks of mild depressive symptoms, whereas higher HDL and lower Cr levels were significantly associated with moderate/severe depressive symptoms, suggesting that patients with SCAD were prone to experience depressive symptoms, especially in the elderly. Abnormality in LDL, HDL, and Cr levels might contribute to the depressive symptoms.

Serum Levels of FGF21, β-Klotho, and BDNF in Stable Coronary Artery Disease Patients With Depressive Symptoms: A Cross-Sectional Single-Center Study

Background: The incidence of depressive symptoms (DS) in patients with stable coronary artery disease (SCAD) is significantly higher than those in healthy population, and that DS are independent risk factors for cardiovascular events. Previous studies have reported that fibroblast growth factor 21 (FGF21), β-klotho, mature brain-derived neurotrophic factor (mBDNF), and BDNF precursor (proBDNF) play important roles in the pathogenesis and treatment of coronary heart disease and depression. With this in mind, the present study aimed to clarify the relationship between FGF21, β-klotho, mBDNF, and proBDNF and SCAD with comorbid depression, in addition to also exploring the underlying mechanisms of these disease processes. Methods: A total of 116 patients with SCAD and 45 healthy controls were recruited. Patients with SCAD were further divided into two subgroups based on the Zung Self-Rating Depression Scale (SDS), which were characterized as those with no DS (NDS) and those with DS. Baseline data were collected, and serum levels of FGF21, β-klotho, mBDNF, and proBDNF were determined. Results: In SCAD patients, Gensini scores-denoting the degree of coronary arteriostenosis-were significantly greater in the DS group than in the NDS group. There was also a positive correlation between the Gensini scores and the SDS scores. Patients in the SCAD group demonstrated a lower serum FGF21. Serum β-klotho, mBDNF, and mBDNF/proBDNF were also significantly lower in the DS group than in the NDS group. Furthermore, β-klotho and mBDNF were negatively correlated with the SDS scores. Additionally, SCAD patients were divided into lower- and higher-level groups using hierarchical cluster analysis, with the results highlighting that patients in the lower mBDNF group had a higher incidence of DS. Conclusions: The depression score was positively correlated with the severity of coronary artery stenosis, and serum FGF21, β-klotho, mBDNF, and proBDNF were closely related to the development of DS in patients with SCAD. These observations suggest FGF21, β-klotho, mBDNF, and proBDNF as potential diagnostic and/or therapeutic targets for SCAD with co-morbid depression.

Psychosocial Stress and Cardiovascular Disease

PURPOSE OF REVIEW

This manuscript reviews the epidemiological data linking psychosocial stress to cardiovascular disease (CVD), describes recent advances in understanding the biological pathway between them, discusses potential therapies against stress-related CVD, and identifies future research directions.

RECENT FINDINGS

Metabolic activity of the amygdala (a neural center that is critically involved in the response to stress) can be measured on ¹⁸F-fluorodeoxyglucose positron emission tomography/computed tomography (¹⁸F-FDG-PET/CT) yielding a neurobiological signal that independently predicts subsequent CVD events. Furthermore, a serial pathway from ↑amygdalar activity → ↑hematopoietic tissue activity → ↑arterial inflammation → ↑CVD events has been elucidated, providing new insights into the mechanism linking stress to CVD. Psychosocial stress and stress conditions are independently associated with CVD in a manner that depends on the degree and duration of stress as well as the individual response to a stressor. Nevertheless, the fundamental biology remains incompletely defined, and stress is often confounded by adverse health behaviors. Thus, most clinical guidelines do not yet recognize psychosocial stress as an independent CVD risk factor or advocate for its treatment in CVD prevention. Clarification of this neurobiological pathway provides a better understanding of the underlying pathophysiology and suggests opportunities to develop novel preventive strategies and therapies.