Quin E. Denfeld

The prevalence of frailty in heart failure: A systematic review and meta-analysis

BACKGROUND There is a growing interest in the intersection of heart failure (HF) and frailty; however, estimates of the prevalence of frailty in HF vary widely. The purpose of this paper was to quantitatively synthesize published literature on the prevalence of frailty in HF and to examine the relationship between study characteristics (i.e. age and functional class) and the prevalence of frailty in HF. METHODS The prevalence of frailty in HF, divided into Physical Frailty and Multidimensional Frailty measures, was synthesized across published studies using a random-effects meta-analysis of proportions approach. Meta-regression was performed to examine the influence of age and functional class (at the level of the study) on the prevalence of frailty. RESULTS A total of 26 studies involving 6896 patients with HF were included in this meta-analysis. Despite considerable differences across studies, the overall estimated prevalence of frailty in HF was 44.5% (95% confidence interval, 36.2%-52.8%; z=10.54; p<0.001). The prevalence was slightly lower among studies using Physical Frailty measures (42.9%, z=9.05; p<0.001) and slightly higher among studies using Multidimensional Frailty measures (47.4%, z=5.66; p<0.001). There were no significant relationships between study age or functional class and prevalence of frailty. CONCLUSIONS Frailty affects almost half of patients with HF and is not necessarily a function of age or functional classification. Future work should focus on standardizing the measurement of frailty and on broadening the view of frailty beyond a strictly geriatric syndrome in HF.

Physical and Psychological Symptom Profiling and Event-Free Survival in Adults With Moderate to Advanced Heart Failure

&NA;Heart failure (HF) is a heterogeneous symptomatic disorder. The goal of this study was to identify and link common profiles of physical and psychological symptoms to 1-year event-free survival in adults with moderate to advanced HF. Methods:Multiple valid, reliable, and domain-specific measures were used to assess physical and psychological symptoms. Latent class mixture modeling was used to identify distinct symptom profiles. Associations between observed symptom profiles and 1-year event-free survival were quantified using Cox proportional hazards modeling. Results:The mean age of the participants (n = 202) was 57 ± 13 years, 50% were men, and 60% had class III/IV HF. Three distinct profiles, mild (41.7%), moderate (30.2%), and severe (28.1%), that captured a gradient of both physical and psychological symptom burden were identified (P < .001 for all comparisons). Controlling for the Seattle HF Score, adults with the moderate symptom profile were 82% more likely (hazard ratio, 1.82; 95% confidence interval, 1.07–3.11; P = .028) and adults with the severe symptom profile were more than twice as likely (hazard ratio, 2.06; 95% confidence interval, 1.21–3.52; P = .001) to have a clinical event within 1 year than patients with the mild symptom profile. Conclusions:Profiling patterns among physical and psychological symptoms identifies HF patient subgroups with significantly worse 1-year event-free survival independent of prognostication based on objective clinical HF data.

Symptom-hemodynamic mismatch and heart failure event risk

Background:Heart failure (HF) is a heterogeneous condition of both symptoms and hemodynamics. Objective:The goals of this study were to identify distinct profiles among integrated data on physical and psychological symptoms and hemodynamics and quantify differences in 180-day event risk among observed profiles. Methods:A secondary analysis of data collected during 2 prospective cohort studies by a single group of investigators was performed. Latent class mixture modeling was used to identify distinct symptom-hemodynamic profiles. Cox proportional hazards modeling was used to quantify difference in event risk (HF emergency visit, hospitalization, or death) among profiles. Results:The mean age (n = 291) was 57 ± 13 years, 38% were female, and 61% had class III/IV HF. Three distinct symptom-hemodynamic profiles were identified: 17.9% of patients had concordant symptoms and hemodynamics (ie, moderate physical and psychological symptoms matched the comparatively good hemodynamic profile), 17.9% had severe symptoms and average hemodynamics, and 64.2% had poor hemodynamics and mild symptoms. Compared with those in the concordant profile, both profiles of symptom-hemodynamic mismatch were associated with a markedly increased event risk (severe symptoms hazards ratio, 3.38; P = .033; poor hemodynamics hazards ratio, 3.48; P = .016). Conclusions:A minority of adults with HF have concordant symptoms and hemodynamics. Either profile of symptom-hemodynamic mismatch in HF is associated with a greater risk of healthcare utilization for HF or death.

Background and design of the profiling biobehavioral responses to mechanical support in advanced heart failure study

Background:Unexplained heterogeneity in response to ventricular assist device (VAD) implantation for the management of advanced heart failure impedes our ability to predict favorable outcomes, provide adequate patient and family education, and personalize monitoring and symptom management strategies. The purpose of this article was to describe the background and the design of a study entitled “Profiling Biobehavioral Responses to Mechanical Support in Advanced Heart Failure” (PREMISE). Study Design and Methods:PREMISE is a prospective cohort study designed to (1) identify common and distinct trajectories of change in physical and psychological symptom burden; (2) characterize common trajectories of change in serum biomarkers of myocardial stress, systemic inflammation, and endothelial dysfunction; and (3) quantify associations between symptoms and biomarkers of pathogenesis in adults undergoing VAD implantation. Latent growth mixture modeling, including parallel process and cross-classification modeling, will be used to address the study aims and will entail identifying trajectories, quantifying associations between trajectories and both clinical and quality-of-life outcomes, and identifying predictors of favorable symptom and biomarker responses to VAD implantation. Conclusions:Research findings from the PREMISE study will be used to enhance shared patient and provider decision making and to shape a much-needed new breed of interventions and clinical management strategies that are tailored to differential symptom and pathogenic responses to VAD implantation.

Physical and psychological symptom biomechanics in moderate to advanced heart failure.

Background:There is a common dissociation between objective measures and patient symptomatology in heart failure (HF). Objective:The aim of this study was to explore the relationship between cardiac biomechanics and physical and psychological symptoms in adults with moderate to advanced HF. Methods:We performed a secondary analysis of data from 2 studies of symptoms among adults with HF. Stepwise regression modeling was performed to examine the influence of cardiac biomechanics (left ventricular internal diastolic diameter, right atrial pressure [RAP], and cardiac index) on symptoms. Results:The average age of the sample (n = 273) was 57 ± 16 years, 61% were men, and 61% had class III or IV HF. Left ventricular internal diastolic diameter (&bgr; = 4.22 ± 1.63, P = .011), RAP (&bgr; = 0.71 ± 0.28, P = .013), and cardiac index (&bgr; = 7.11 ± 3.19, P = .028) were significantly associated with physical symptoms. Left ventricular internal diastolic diameter (&bgr; = 0.10 ± 0.05, P = .038) and RAP (&bgr; = 0.03 ± 0.01, P = .039) were significantly associated with anxiety. There were no significant biomechanical determinants of depression. Conclusion:Cardiac biomechanics were related to physical symptoms and anxiety, providing preliminary evidence of the biological underpinnings of symptomatology among adults with HF.

Precision and Accuracy Comparison of Point-of-Care and Laboratory Glucose Concentrations in Cardiothoracic Surgery Patients

Background:There have been variable results on the practice of tight glycemic control, and studies have demonstrated that point-of-care (POC) glucometers have variable accuracy. Objective:The purpose of this study was to determine the difference between blood glucose concentrations obtained from POC glucometers as compared with laboratory results in cardiothoracic surgery (CTS) patients. Methods:This was a descriptive study on a convenience sample of 46 CTS patients. A single sample of arterial blood was collected and analyzed at the bedside with the POC glucometer and in the laboratory to obtain a serum glucose concentration and hematocrit (Hct). A paired t test was used to compare the mean differences along with Spearman ρ correlation to examine the relationship between difference scores and Hct. Results:The POC glucose was significantly higher than the laboratory result (t = 8.5, P < .001) with a mean of 12.3 (SD, 9.8) mg/dL. Spearman ρ correlation between the difference scores and Hct was −0.43, P = .003. Using a tercile split, groups with Hct of less than 26% (n = 16) and greater than 29% (n = 15) were identified. The unpaired t test on the mean difference scores of these 2 groups was t = −2.7, P < .01, with an overall mean difference 8.6 mg/dL (95% confidence interval, −15 to −2.2). The mean difference was 16.3 in the low-Hct group and 7.8 in the high-Hct group. Conclusions:Point-of-care glucometer results differ significantly from laboratory glucose concentrations, with the difference widening as the Hct decreases. This raises the concern about using POC devices to provide tight glycemic control in CTS patients.

Identifying a Relationship Between Physical Frailty and Heart Failure Symptoms

Background: Heart failure (HF) is a complex clinical syndrome associated with significant symptom burden; however, our understanding of the relationship between symptoms and physical frailty in HF is limited. Objective: The aim of this study was to quantify associations between symptoms and physical frailty in adults with HF. Methods: A sample of adults with symptomatic HF were enrolled in a cross-sectional study. Physical symptoms were measured with the HF Somatic Perception Scale–Dyspnea subscale, the Epworth Sleepiness Scale, and the Brief Pain Inventory short form. Affective symptoms were measured with the Patient Health Questionnaire-9 and the Brief Symptom Inventory–Anxiety scale. Physical frailty was assessed according to the Frailty Phenotype Criteria: shrinking, weakness, slowness, physical exhaustion, and low physical activity. Comparative statistics and generalized linear modeling were used to quantify associations between symptoms and physical frailty, controlling for Seattle HF Model projected 1-year survival. Results: The mean age of the sample (n = 49) was 57.4 ± 9.7 years, 67% were male, 92% had New York Heart Association class III/IV HF, and 67% had nonischemic HF. Physically frail participants had more than twice the level of dyspnea (P < .001), 75% worse wake disturbances (P < .001), and 76% worse depressive symptoms (P = .003) compared with those who were not physically frail. There were no differences in pain or anxiety. Conclusions: Physically frail adults with HF have considerably worse dyspnea, wake disturbances, and depression. Targeting physical frailty may help identify and improve physical and affective symptoms in HF.

Exploring the relationship between β-adrenergic receptor kinase-1 and physical symptoms in heart failure

Background: The relationship between physical heart failure (HF) symptoms and pathophysiological mechanisms is unclear. Objective: To quantify the relationship between plasma &bgr;‐adrenergic receptor kinase‐1 (&bgr;ARK1) and physical symptoms among adults with HF. Methods: We performed a secondary analysis of data collected from two studies of adults with HF. Plasma &bgr;ARK1 was quantified using an enzyme‐linked immunosorbent assay. Physical symptoms were measured with the HF Somatic Perception Scale (HFSPS). Generalized linear modeling was used to quantify the relationship between &bgr;ARK1 and HFSPS scores. Results: The average age (n = 94) was 54.5 ± 13.1 years, 76.6% were male, and a majority (83.0%) had Class III or IV HF. &bgr;ARK1 was significantly associated with HFSPS scores (&bgr; = 0.22 ± 0.10, p = 0.038), adjusting for other predictors of physical symptoms (model R2 = 0.250, F(7, 70) = 3.34, p = 0.004). Conclusions: Higher &bgr;ARK1 is associated with worse physical HF symptoms, pinpointing a potential pathophysiologic underpinning.

Comparative symptom biochemistry between moderate and advanced heart failure

BACKGROUND We have a limited understanding of the biological underpinnings of symptoms in heart failure (HF). OBJECTIVES The purpose of this paper was to compare relationships between peripheral biomarkers of HF pathogenesis and physical symptoms between patients with advanced versus moderate HF. METHODS This was a two-stage phenotype sampling cohort study wherein we examined patients with advanced HF undergoing ventricular assist device implantation in the first stage, and then patients with moderate HF (matched adults with HF not requiring device implantation) in the second stage. Linear modeling was used to compare relationships among biomarkers and physical symptoms between cohorts. RESULTS Worse myocardial stress, systemic inflammation and endothelial dysfunction were associated with worse physical symptoms in moderate HF (n=48), but less physical symptom burden in advanced HF (n=48). CONCLUSIONS Where patients are in the HF trajectory needs to be taken into consideration when exploring biological underpinnings of physical HF symptoms.

Implant Strategy–Specific Changes in Symptoms in Response to Left Ventricular Assist Devices

Background:Although we know that the quality of life generally improves after left ventricular assist device (LVAD) implantation, we know little about how symptoms change in response to LVAD. Methods:The purpose of this study was to compare the changes in symptoms between bridge and destination therapy patients as part of a prospective cohort study. Physical (dyspnea and wake disturbances) and affective symptoms (depression and anxiety) were measured before LVAD and at 1, 3, and 6 months after LVAD. Multiphase growth modeling was used to capture the 2 major phases of change: initial improvements between preimplant and 1 month after LVAD and subsequent improvements between 1 and 6 months after LVAD. Results:The sample included 64 bridge and 22 destination therapy patients as the preimplant strategy. Destination patients had worse preimplant dyspnea and wake disturbances, and they experienced greater initial improvements in these symptoms compared with bridge patients (all P < .05); subsequent change in both symptoms were similar between groups (both P > .05). Destination patients had worse preimplant depression (P = .042) but experienced similar initial and subsequent improvements in depression in response to LVAD compared with bridge patients (both P > .05). Destination patients had similar preimplant anxiety (P = .279) but experienced less initial and greater subsequent improvements in anxiety after LVAD compared with bridge patients (both P < .05). Conclusion:There are many differences in the magnitude and timing of change in symptom responses to LVAD between bridge and destination therapy patients. Detailed information on changes in specific symptoms may better inform shared decision-making regarding LVAD.