The effects of advanced factor analysis approaches on outcomes in randomised trials for depression: protocol for secondary analysis of individual participant data.

BACKGROUND: Modern psychometric methods make it possible to eliminate nonperforming items and reduce measurement error. Application of these methods to existing outcome measures can reduce variability in scores, and may increase treatment effect sizes in depression treatment trials. AIMS: We aim to determine whether using confirmatory factor analysis techniques can provide better estimates of the true effects of treatments, by conducting secondary analyses of individual patient data from randomised trials of antidepressant therapies. METHOD: We will access individual patient data from antidepressant treatment trials through Clinicalstudydatarequest.com and Vivli.org, specifically targeting studies that used the Hamilton Rating Scale for Depression (HRSD) as the outcome measure. Exploratory and confirmatory factor analytic approaches will be used to determine pre-treatment (baseline) and post-treatment models of depression, in terms of the number of factors and weighted scores of each item. Differences in the derived factor scores between baseline and outcome measurements will yield an effect size for factor-informed depression change. The difference between the factor-informed effect size and each original trial effect size, calculated with total HRSD-17 scores, will be determined, and the differences modelled with meta-analytic approaches. Risk differences for proportions of patients who achieved remission will also be evaluated. Furthermore, measurement invariance methods will be used to assess potential gender differences. CONCLUSIONS: Our approach will determine whether adopting advanced psychometric analyses can improve precision and better estimate effect sizes in antidepressant treatment trials. The proposed methods could have implications for future trials and other types of studies that use patient-reported outcome measures.

Outcomes of a tailored self-care intervention for patients with heart failure and major depression: A secondary analysis of a randomized controlled trial.

BACKGROUND: Depression is a recognized barrier to heart failure self-care, but there has been little research on interventions to improve heart failure self-care in depressed patients. OBJECTIVES: To investigate the outcomes of an individually tailored self-care intervention for patients with heart failure and major depression, and to determine whether the adequacy of self-care at baseline, the severity of depression or anxiety, or other factors affect the outcomes of this intervention. DESIGN: Secondary analysis of data from a pre-registered randomized controlled trial (NCT02997865). METHODS: Outpatients with heart failure and comorbid major depression (n = 139) were randomly assigned to cognitive behavior therapy or usual care for depression. In addition, an experienced cardiac nurse provided the tailored self-care intervention to all patients in both arms of the trial starting eight weeks after randomization. Weekly self-care intervention sessions were held between Weeks 8 and 16; the frequency was tapered to biweekly or monthly between Weeks 17 and 32. The Self-Care of Heart Failure Index (v6.2) was used to assess self-care outcomes, with scores ≥70 on each of its three scales (Maintenance, Management, and Confidence) being consistent with adequate self-care. The Week 16 Maintenance scale score was the primary outcome for this analysis. RESULTS: At baseline, 107 (77%) of the patients scored in the inadequate self-care range on the Maintenance scale. Between Weeks 8 and 16, Maintenance scores improved more in patients with initially inadequate than initially adequate self-care (11.9 vs. 3.2 points, p = .003). Sixty-six (48%) of the patients with initially inadequate Maintenance scores achieved scores in the adequate range by Week 32 (p < .0001). Covariate-adjusted predictors of better Maintenance outcomes included adequate Maintenance at baseline (p < .0001), higher anxiety at baseline (p < .05), and higher dosages of the self-care intervention (p < .0001). Neither treatment with cognitive behavior therapy nor less severe major depression predicted better self-care outcomes. CONCLUSIONS: Depressed patients with inadequate heart failure self-care are able to achieve clinically significant improvements in self-care with the help of an individually tailored self-care intervention. Further refinement and testing are needed to increase the intervention's potential for clinical implementation.

Treatment of depression and inadequate self-care in patients with heart failure: One-year outcomes of a randomized controlled trial.

OBJECTIVE: Both depression and inadequate self-care are common in patients with heart failure. This secondary analysis examines the one-year outcomes of a randomized controlled trial of a sequential approach to treating these problems. METHODS: Patients with heart failure and major depression were randomly assigned to usual care (n = 70) or to cognitive behavior therapy (n = 69). All patients received a heart failure self-care intervention starting 8 weeks after randomization. Patient-reported outcomes were assessed at Weeks 8, 16, 32, and 52. Data on hospital admissions and deaths were also obtained. RESULTS: One year after randomization, Beck Depression Inventory (BDI-II) scores were - 4.9 (95% C.I., -8.9 to -0.9; p < .05) points lower in the cognitive therapy than the usual care arm, and Kansas City Cardiomyopathy scores were 8.3 (95% C.I., 1.9 to 14.7; p < .05) points higher. There were no differences on the Self-Care of Heart Failure Index or in hospitalizations or deaths. CONCLUSIONS: The superiority of cognitive behavior therapy relative to usual care for major depression in patients with heart failure persisted for at least one year. Cognitive behavior therapy did not increase patients' ability to benefit from a heart failure self-care intervention, but it did improve HF-related quality of life during the follow-up period. TRIAL REGISTRATION: ClinicalTrials.gov Identifier NCT02997865.

New Perspectives on Treatment of Depression in Coronary Heart Disease.

ABSTRACT: It has been 35 years since we published a study in Psychosomatic Medicine showing that patients with coronary heart disease (CHD) and major depression were at twice the risk of having a cardiac event as were nondepressed patients (Carney et al. Psychosom Med. 1988;50:627-33). This small study was followed a few years later by a larger, more convincing report from Frasure-Smith et al. (JAMA. 1993;270:1819-25) showing that depression increased the rate of mortality in patients with a recent acute myocardial infarction. Since the 1990s, there have been many more studies of depression as a risk factor for cardiac events and cardiac-related mortality from all over the world, and many clinical trials designed to determine whether treating depression improves medical outcomes in these patients. Unfortunately, the effects of depression treatment in patients with CHD remain unclear. This article considers why it has been difficult to determine whether treatment of depression improves survival in these patients. It also proposes several lines of research to address this question, with the goal of definitively establishing whether treating depression can extend cardiac event-free survival and enhance quality of life in patients with CHD.

Symptoms that remain after depression treatment in patients with coronary heart disease.

OBJECTIVE: Symptoms which commonly remain after treatment for major depression increase the risk of relapse and recurrence in medically well patients. The same symptoms predict major adverse cardiac events in observational studies of patients with coronary heart disease (CHD). The purpose of this study was to determine the prevalence and predictors of residual depression symptoms in depressed patients with CHD-. METHODS: Beck Depression Inventory-II data from two randomized clinical trials and an uncontrolled treatment study of depression in patients with CHD were combined to determine the prevalence and predictors of residual symptoms. RESULTS: Loss of energy, loss of pleasure, loss of interest, fatigue, and difficulty concentrating were the five most common residual symptoms in all three studies. They are also among the most common residual symptoms in medically well patients who are treated for depression. The severity of pre-treatment anxiety predicted the post-treatment persistence of all these symptoms except for loss of energy. CONCLUSIONS: The most common post-treatment residual symptoms found in this study of patients with coronary heart disease and comorbid major depression are the same as those that have been reported in previous studies of medically-well depressed patients. This suggests that they may be resistant to standard depression treatments across diverse patient populations. More effective treatments for these symptoms are needed.

Sequential Interventions for Major Depression and Heart Failure Self-Care: A Randomized Clinical Trial.

BACKGROUND: Major depression and inadequate self-care are common in patients with heart failure (HF). Little is known about how to intervene when both problems are present. This study examined the efficacy of a sequential approach to treating these problems. METHODS: Stepped Care for Depression in HF was a single-site, single-blind, randomized controlled trial of cognitive behavior therapy (CBT) versus usual care (UC) for major depression in patients with HF. The intensive phase of the CBT intervention lasted between 8 and 16 weeks, depending upon the rate of improvement in depression. All participants received a tailored HF self-care intervention that began 8 weeks after randomization. The intensive phase of the self-care intervention ended at 16 weeks post-randomization. The coprimary outcome measures were the Beck Depression Inventory (version 2) and the Maintenance scale of the Self-Care of HF Index (v6.2) at week 16. RESULTS: One hundred thirty-nine patients with HF and major depression were enrolled; 70 were randomized to UC and 69 to CBT. At week 16, the patients in the CBT arm scored 4.0 points ([95% CI, -7.3 to -0.8]; P=0.02) lower on the Beck Depression Inventory, version 2 than those in the usual care arm. Mean scores on the Self-Care of HF Index Maintenance scale were not significantly different between the groups ([95% CI, -6.5 to 1.5]; P=0.22). CONCLUSIONS: CBT is more effective than usual care for major depression in patients with HF. However, initiating CBT before starting a tailored HF self-care intervention does not increase the benefit of the self-care intervention. REGISTRATION: URL: https://www. CLINICALTRIALS: gov; Unique identifier: NCT02997865.

Influence of Neighborhood Conditions on Recurrent Hospital Readmissions in Patients with Heart Failure: A Cohort Study.

PURPOSE: This study examined how certain aspects of residential neighborhood conditions (ie, observed built environment, census-based area-level poverty, and perceived disorder) affect readmission in urban patients with heart failure. METHODS: A total of 400 patients with heart failure who were discharged alive from an urban-university teaching hospital were enrolled. Data were collected about readmissions during a 2-year follow-up. The impact of residential neighborhood conditions on readmissions was examined with adjustment for 7 blocks of covariates: 1) patient demographic characteristics; 2) comorbidities; 3) clinical characteristics; 4) depression; 5) perceived stress; 6) health behaviors; and 7) hospitalization characteristics. RESULTS: A total of 83.3% of participants were readmitted. Participants from high-poverty census tracts (≥20%) were at increased risk of readmission compared with those from census tracts with <10% poverty (hazard ratio [HR]: 1.53; 95% confidence interval: 1.03-2.27; P < .05) when adjusted for demographic characteristics. None of the built environmental or perceived neighborhood conditions were associated with the risk of readmission. The poverty-related risk of readmission was reduced to nonsignificance after including diabetes (HR: 1.33) and hypertension (HR: 1.35) in the models. CONCLUSIONS: The effect of high poverty is partly explained by high rates of hypertension and diabetes in these areas. Improving diabetes and blood pressure control or structural aspects of impoverished areas may help reduce hospital readmissions.

Depression interventions for individuals with coronary artery disease - Cost-effectiveness calculations from an Irish perspective.

BACKGROUND: A substantial proportion of individuals with coronary artery disease experience moderate or severe acute depression that requires treatment. We assessed the cost-effectiveness of four interventions for depression in individuals with coronary artery disease. METHODS: We assessed effectiveness of pharmacotherapy, psychotherapy, collaborative care and exercise as remission rate after 8 and 26 weeks using estimates from a recent network meta-analysis. The cost assessment included standard doses of antidepressants, contact frequency, and staff time per contact. Unit costs were calculated as health services' purchase price for pharmaceuticals and mid-point staff salaries obtained from the Irish Health Service Executive and validated by clinical staff. Incremental cost-effectiveness ratios were calculated as the incremental costs over incremental remissions compared to usual care. High- and low-cost scenarios and sensitivity analysis were performed with changed contact frequencies, and assuming individual vs. group psychotherapy or exercise. RESULTS: After 8 weeks, the estimated incremental cost-effectiveness ratio was lowest for group exercise (€526 per remission), followed by pharmacotherapy (€589), individual psychotherapy (€3117) and collaborative care (€4964). After 26 weeks, pharmacotherapy was more cost-effective (€591) than collaborative care (€7203) and individual psychotherapy (€9387); no 26-week assessment for exercise was possible. Sensitivity analysis showed that group psychotherapy could be most cost-effective after 8 weeks (€519) and cost-effective after 26 weeks (€1565); however no group psychotherapy trials were available investigating its effectiveness. DISCUSSION: Large variation in incremental cost-effectiveness ratios was seen. With the current assumptions, the most cost-effective depression intervention for individuals with coronary artery disease after 8 weeks was group exercise.

The Promise of Polygenic Risk Prediction in Smoking Cessation: Evidence From Two Treatment Trials.

INTRODUCTION: Tobacco use disorder is a complex behavior with a strong genetic component. Genome-wide association studies (GWAS) on smoking behaviors allow for the creation of polygenic risk scores (PRSs) to approximate genetic vulnerability. However, the utility of smoking-related PRSs in predicting smoking cessation in clinical trials remains unknown. AIMS AND METHODS: We evaluated the association between polygenic risk scores and bioverified smoking abstinence in a meta-analysis of two randomized, placebo-controlled smoking cessation trials. PRSs of smoking behaviors were created using the GWAS and Sequencing Consortium of Alcohol and Nicotine use (GSCAN) consortium summary statistics. We evaluated the utility of using individual PRS of specific smoking behavior versus a combined genetic risk that combines PRS of all four smoking behaviors. Study participants came from the Transdisciplinary Tobacco Use Research Centers (TTURCs) Study (1091 smokers of European descent), and the Genetically Informed Smoking Cessation Trial (GISC) Study (501 smokers of European descent). RESULTS: PRS of later age of smoking initiation (OR [95% CI]: 1.20, [1.04-1.37], p = .0097) was significantly associated with bioverified smoking abstinence at end of treatment. In addition, the combined PRS of smoking behaviors also significantly predicted bioverified smoking abstinence (OR [95% CI] 0.71 [0.51-0.99], p = .045). CONCLUSIONS: PRS of later age at smoking initiation may be useful in predicting smoking cessation at the end of treatment. A combined PRS may be a useful predictor for smoking abstinence by capturing the genetic propensity for multiple smoking behaviors. IMPLICATIONS: There is a potential for polygenic risk scores to inform future clinical medicine, and a great need for evidence on whether these scores predict clinically meaningful outcomes. Our meta-analysis provides early evidence for potential utility of using polygenic risk scores to predict smoking cessation amongst smokers undergoing quit attempts, informing further work to optimize the use of polygenic risk scores in clinical care.

Depression and Hospital Readmissions in Patients with Heart Failure.

Depression increases the risk of mortality in patients with heart failure (HF). Less is known about whether depression predicts multiple readmissions or whether multiple hospitalizations worsen depression in patients with HF. This study aimed to test the hypotheses that depression predicts multiple readmissions in patients hospitalized with HF, and conversely that multiple readmissions predict persistent or worsening depression. All-cause readmissions were ascertained over a 2-year follow-up of a cohort of 400 patients hospitalized with HF. The Patient Health Questionnaire-9 was used to assess depression at index and 3-month intervals. At enrollment in the study, 21% of the patients were mildly depressed and 22% were severely depressed. Higher Patient Health Questionnaire-9 depression scores predicted a higher rate of readmissions (adjusted hazard ratio 1.02, 95% confidence interval 1.00 to 1.04, p = 0.03). The readmission rate was higher in those who were severely depressed than in those without depression (p = 0.0003), but it did not differ between patients who were mildly depressed and patients without depression. Multiple readmissions did not predict persistent or worsening depression, but younger patients in higher New York Heart Association classes were more depressed than other patients. Depression is an independent risk factor for multiple all-cause readmissions in patients hospitalized with HF. Severe depression is a treatable psychiatric co-morbidity that warrants ongoing clinical attention in patients with HF.

Does inflammation mediate the effects of depression on heart disease? That may depend on the symptoms.

Preparation of this manuscript was supported in part by grant number R01HL089336 from the National Heart, Lung, and Blood Institute of the National Institutes of Health, Bethesda, Maryland USA, Robert M. Carney.

Improving Quality of Life in Heart Failure.

PURPOSE OF REVIEW: Heart failure has substantial effects on health-related quality of life. Maintaining or improving quality of life is an important goal of heart failure therapy, and many patients value better quality of life over greater longevity. RECENT FINDINGS: The symptoms and functional severity of heart failure, medical comorbidities, and depression are the strongest predictors of poor quality of life. Guideline-recommended medical and behavioral interventions for HF, including exercise training and cardiac rehabilitation, self-care interventions, and treatment of depression, can help to improve quality of life. Heart failure is, in most cases, a progressive condition with a poor prognosis. However, poor quality of life is not inevitable, and a variety of medical, surgical, and nonpharmacological interventions can help to maintain or improve quality of life in patients with heart failure.

Hybrid Systematic Review and Network Meta-Analysis of Randomized Controlled Trials of Interventions for Depressive Symptoms in Patients With Coronary Artery Disease.

OBJECTIVE: Depression is common in patients with coronary artery disease (CAD) and is associated with poor outcomes. Although different treatments are available, it is unclear which are best or most acceptable to patients, so we conducted a network meta-analysis of evidence from randomized controlled trials (RCTs) of different depression treatments to ascertain relative efficacy. METHODS: We searched for systematic reviews of RCTs of depression treatments in CAD and updated these with a comprehensive search for recent individual RCTs. RCTs comparing depression treatments (pharmacological, psychotherapeutic, combined pharmacological/psychotherapeutic, exercise, collaborative care) were included. Primary outcomes were acceptability (dropout rate) and change in depressive symptoms 8 week after treatment commencement. Change in 26-week depression and mortality were secondary outcomes. Frequentist, random-effects network meta-analysis was used to synthesize the evidence, and evidence quality was evaluated following Grading of Recommendations, Assessment, Development and Evaluations recommendations. RESULTS: Thirty-three RCTs (7240 participants) provided analyzable data. All treatments were equally acceptable. At 8 weeks, combination therapy (1 study), exercise (1 study), and antidepressants (10 studies) yielded the strongest effects versus comparators. At 26 weeks, antidepressants were consistently effective, but psychotherapy was only effective versus usual care. There were no differences in treatment groups for mortality. Grading of Recommendations, Assessment, Development and Evaluations ratings ranged from very low to low. CONCLUSIONS: Overall, the evidence was limited and biased. Although all treatments for post-CAD depression were equally acceptable, antidepressants have the most robust evidence base and should be the first-line treatment. Combinations of antidepressants and psychotherapy, along with exercise, could be more effective than antidepressants alone but require further rigorous, multiarm intervention trials.Systematic Review Registration: CRD42018108293 (International Prospective Register of Systematic Reviews).

Psychosocial Syndemics and Multimorbidity in Patients with Heart Failure †.

Heart failure (HF) is a common cause of hospitalization and mortality in older adults. HF is almost always embedded within a larger pattern of multimorbidity, yet many studies exclude patients with complex psychiatric and medical comorbidities or cognitive impairment. This has left significant gaps in research on the problems and treatment of patients with HF. In addition, HF is only one of multiple challenges facing patients with multimorbidity, stressful socioeconomic circumstances, and psychosocial problems. The purpose of this study is to identify combinations of comorbidities and health disparities that may affect HF outcomes and require different mixtures of medical, psychological, and social services to address. The syndemics framework has yielded important insights into other disorders such as HIV/AIDS, but it has not been applied to the complex psychosocial problems of patients with HF. The multimorbidity framework is an alternative approach for investigating the effects of multiple comorbidities on health outcomes. The specific aims are: (1) to determine the coprevalence of psychiatric and medical comorbidities in patients with HF (n = 535); (2) to determine whether coprevalent comorbidities have synergistic effects on readmissions, mortality, self-care, and global health; (3) to identify vulnerable subpopulations of patients with HF who have high coprevalences of syndemic comorbidities; (4) to determine the extent to which syndemic comorbidities explain adverse HF outcomes in vulnerable subgroups of patients with HF; and (5) to determine the effects of multimorbidity on readmissions, mortality, self-care, and global health.

Left Ventricular Dysfunction and Depression in Hospitalized Patients with Heart Failure.

OBJECTIVE: This study examined whether the severity of left ventricular systolic dysfunction is associated with depression in patients with heart failure (HF). Other factors were also studied to identify independent correlates of depression in HF. METHODS: The sample consisted of 400 hospitalized patients with HF. Left ventricular ejection fraction and other medical data were obtained from medical records. Depression and other psychosocial characteristics were assessed by an interview and questionnaires. Proportional odds models were used to test the relationships of these characteristics to Diagnostic and Statistical Manual of Mental Disorders (Fifth Edition) depressive disorders, and analysis of covariance was used to test relationships with continuous measures of depression in secondary models. RESULTS: The models produced no evidence of an association between left ventricular ejection fraction and depression. The adjusted odds ratio (95% confidence interval) was 1.00 (0.98-1.01; p = .87) for depression diagnosis. Analysis of covariance estimates (standard errors) were -0.01 (0.02; p = .54) for the Hamilton Rating Scale for Depression and -0.01 (0.01; p = .59) for the Patient Health Questionnaire. The odds of depression were higher in African American patients and in those with high levels of anxiety or stress. Other characteristics that have been associated with depression in previous studies, including sex and age, were not consistently associated with depression in this study. CONCLUSIONS: There is no relationship between the severity of left ventricular systolic dysfunction and depression in hospitalized patients with HF. In contrast, African American patients and those with a high level of anxiety or perceived stress are more likely than other patients to have a comorbid depressive disorder.

Effectiveness of collaborative care in reducing suicidal ideation: An individual participant data meta-analysis.

To assess whether CC is more effective at reducing suicidal ideation in people with depression compared with usual care, and whether study and patient factors moderate treatment effects. METHOD: We searched Medline, Embase, PubMed, PsycINFO, CINAHL, CENTRAL from inception to March 2020 for Randomised Controlled Trials (RCTs) that compared the effectiveness of CC with usual care in depressed adults, and reported changes in suicidal ideation at 4 to 6 months post-randomisation. Mixed-effects models accounted for clustering of participants within trials and heterogeneity across trials. This study is registered with PROSPERO, CRD42020201747. RESULTS: We extracted data from 28 RCTs (11,165 patients) of 83 eligible studies. We observed a small significant clinical improvement of CC on suicidal ideation, compared with usual care (SMD, -0.11 [95%CI, -0.15 to -0.08]; I2, 0·47% [95%CI 0.04% to 4.90%]). CC interventions with a recognised psychological treatment were associated with small reductions in suicidal ideation (SMD, -0.15 [95%CI -0.19 to -0.11]). CC was more effective for reducing suicidal ideation among patients aged over 65 years (SMD, - 0.18 [95%CI -0.25 to -0.11]). CONCLUSION: Primary care based CC with an embedded psychological intervention is the most effective CC framework for reducing suicidal ideation and older patients may benefit the most.

Risk stratification after acute myocardial infarction by amplitude-frequency mapping of cyclic variation of heart rate.

BACKGROUND: Blunted cyclic variation of heart rate (CVHR), measured as a decrease in CVHR amplitude (Acv), predicts mortality risk after acute myocardial infarction (AMI). However, Acv also can be reduced in mild sleep apnea with mild O2 desaturation. We investigated whether Acv's predictive power for post-AMI mortality could be improved by considering the effect of sleep apnea severity. METHODS: In 24-hr ECG in 265,291 participants of the Allostatic State Mapping by Ambulatory ECG Repository project, sleep apnea severity was estimated by the frequency of CVHR (Fcv) measured by an automated algorithm for auto-correlated wave detection by adaptive threshold (ACAT). The distribution of Acv on the Acv-Fcv relation map was modeled by percentile regression, and a function converting Acv into percentile value was developed. In the retrospective cohort of the Enhancing Recovery in Coronary Heart Disease (ENRICHD) study, consisting of 673 survivors and 44 non-survivors after AMI, the mortality predictive power of percentile Acv calculated by the function was compared with that of unadjusted Acv. RESULTS: Among the ALLSTAR ECG data, low Acv values appeared more likely when Fcv was low. The logistic regression analysis for mortality in the ENRICHD cohort showed c-statistics of 0.667 (SE, 0.041), 0.817 (0.035), and 0.843 (0.030) for Fcv, unadjusted Acv, and the percentile Acv, respectively. Compared with unadjusted Acv, the percentile Acv showed a significant net reclassification improvement of 0.90 (95% CI, 0.51-1.42). CONCLUSIONS: The predictive power of Acv for post-AMI mortality is improved by considering its relation to sleep apnea severity estimated by Fcv.

Survival Predictors of Heart Rate Variability After Myocardial Infarction With and Without Low Left Ventricular Ejection Fraction.

BACKGROUND: Heart rate variability (HRV) and heart rate (HR) dynamics are used to predict the survival probability of patients after acute myocardial infarction (AMI), but the association has been established in patients with mixed levels of left ventricular ejection fraction (LVEF). OBJECTIVE: We investigated whether the survival predictors of HRV and HR dynamics depend on LVEF after AMI. METHODS: We studied 687 post-AMI patients including 147 with LVEF ≤35% and 540 with LVEF >35%, of which 23 (16%) and 22 (4%) died during the 25 month follow-up period, respectively. None had an implanted cardioverter-defibrillator. From baseline 24 h ECG, the standard deviation (SDNN), root mean square of successive difference (rMSSD), percentage of successive difference >50 ms (pNN50) of normal-to-normal R-R interval, ultra-low (ULF), very-low (VLF), low (LF), and high (HF) frequency power, deceleration capacity (DC), short-term scaling exponent (α1), non-Gaussianity index (λ25 s), and the amplitude of cyclic variation of HR (Acv) were calculated. RESULTS: The predictors were categorized into three clusters; DC, SDNN, α1, ULF, VLF, LF, and Acv as Cluster 1, λ25 s independently as Cluster 2, and rMSSD, pNN50, and HF as Cluster 3. In univariate analyses, mortality was best predicted by indices belonging to Cluster 1 regardless of LVEF. In multivariate analyses, however, mortality in patients with low LVEF was best predicted by the combinations of Cluster 1 predictors or Cluster 1 and 3 predictors, whereas in patients without low LVEF, it was best predicted by the combinations of Cluster 1 and 2 predictors. CONCLUSION: The mortality risk in post-AMI patients with low LVEF is predicted by indices reflecting decreased HRV or HR responsiveness and cardiac parasympathetic dysfunction, whereas in patients without low LVEF, the risk is predicted by a combination of indices that reflect decreased HRV or HR responsiveness and indicator that reflects abrupt large HR changes suggesting sympathetic involvement.