This cross-sectional study assesses the concordance between Pooled Cohort Equations to Prevent Heart Failure risk scoring and the presence of subclinical cardiac maladaptation in the community.
Key Points
Question
What is the concordance between the 10-year risk for heart failure (HF) as calculated by the Pooled Cohort Equations to Prevent Heart Failure and the presence of subclinical cardiac maladaptation?
Findings
In this cross-sectional study of 1020 individuals, higher 10-year HF risk score was significantly associated with higher likelihood for echocardiographic signs of left ventricular remodeling and dysfunction. The HF risk score detected left ventricular concentric remodeling, hypertrophy, and diastolic dysfunction with an accuracy of 74%, 78%, and 87%, respectively.
Meaning
Pooled Cohort Equations to Prevent Heart Failure scoring adequately detected individuals with subclinical cardiac maladaptation and may thus be a valuable HF prediction tool in primary prevention.
Abstract
Importance
The Pooled Cohort Equations to Prevent Heart Failure (PCP-HF) estimate the 10-year risk for symptomatic heart failure (HF) from routine clinical data. The PCP-HF score should detect asymptomatic individuals with cardiac maladaptation preceding HF symptoms for it to be a useful HF prediction tool in primary prevention.
Objective
To assess the concordance between PCP-HF risk scoring and the presence of subclinical cardiac maladaptation in the community.
Design, Setting, and Participants
This cross-sectional analysis included participants enrolled in the Flemish Study on Environment, Genes and Health Outcomes who underwent a clinical examination including echocardiography between May 2005 and January 2015. Participants younger than 30 years, older than 79 years, had prevalent cardiovascular disease, and/or had suboptimal echocardiographic imaging quality were excluded. Analysis began February 2020 and ended April 2020.
Exposures
Ten-year HF risk as calculated from routine clinical data using the PCP-HF. Based on tertile limits, participants were categorized as having low (≤0.4%), intermediate (0.4%-2.4%), and high (≥2.4%) 10-year HF risk score.
Main Outcomes and Measures
Echocardiographic profiles of subclinical heart remodeling and dysfunction.
Results
A total of 1020 individuals were analyzed (mean [SD] age, 52.8 [11.4] years; 541 female [53.0%]). The prevalence of left ventricular (LV) remodeling and dysfunction was significantly higher from low to intermediate and high 10-year HF risk score. A doubling in 10-year HF risk score was associated with higher odds for LV concentric remodeling (odds ratio [OR], 1.48; 95% CI, 1.36-1.61; P < .001), LV hypertrophy (OR, 1.66; 95% CI, 1.51-1.83; P < .001), abnormal LV longitudinal strain (OR, 1.12; 95% CI, 1.05-1.19; P < .001), and LV diastolic dysfunction (OR, 2.28; 95% CI, 1.94-2.69; P < .001). Moreover, the PCP-HF score detected echocardiographic abnormalities with an accuracy of 74% (LV concentric remodeling), 78% (LV hypertrophy), 59% (abnormal LV longitudinal strain), and 87% (LV diastolic dysfunction). The likelihood of LV concentric remodeling, hypertrophy, and diastolic dysfunction were 3.1, 3.8, and 9.4 times higher in participants with high 10-year HF risk score than the average population risk, respectively (P < .001). Of all PCP-HF score components, age, body mass index, and systolic blood pressure were key correlates of echocardiographic abnormalities in multivariable-adjusted analysis.
Conclusions and Relevance
PCP-HF risk scoring adequately detected individuals with subclinical heart maladaptation that precedes HF symptoms by years. Thus, it may be a valuable HF prediction tool in primary prevention.
Introduction
Heart failure (HF) guidelines advocate screening tools that identify individuals at risk for symptomatic HF to timely initiate therapies that block the transition from subclinical to overt HF stages.1 Recently, Khan et al2 derived race- and sex-specific equations from individual-level data from 7 population cohorts to calculate the 10-year HF risk from routine clinical data in asymptomatic individuals aged 30 to 79 years. To further validate the Pooled Cohort Equations to Prevent Heart Failure (PCP-HF) as an HF prediction tool, we investigated the concordance between PCP-HF risk scoring and the presence of subclinical cardiac maladaptation in the community.
Methods
Study Population and HF Risk Scoring
We randomly recruited 1851 individuals within the Flemish Study on Environment, Genes and Health Outcomes, which received a prior approval from the Ethics Committee of the University of Leuven, from May 2005 to January 2015.3 Written informed consent was obtained from 1447 participants (participation rate, 78.2%), who underwent a clinical examination including echocardiography. Exclusion criteria were (1) age younger than 30 years (n = 181) or older than 79 years (n = 40); (2) prevalent cardiovascular disease confirmed by medical records (n = 127); and/or (3) suboptimal echocardiographic imaging quality (n = 79). For the remaining participants, we calculated the 10-year HF risk from routine clinical data as specified in the PCP-HF for White individuals.2 We categorized participants into tertiles and labeled them as having low (≤0.4%), intermediate (0.4%-2.4%), and high (≥2.4%) 10-year HF risk score. To assess the performance of the PCP-HF score, we assessed incident symptomatic HF via self-report (at a follow-up visit or during a telephone interview) and medical reports provided by general practitioners and regional hospitals during a median follow-up period of 6.7 years. Self-reported HF was ascertained by medical reporting.
Echocardiographic Phenotyping
On the same day as the risk factor assessment, 2 echocardiographers (T.K. and a trained colleague) obtained standardized echocardiographic images using a Vivid 7 Pro and a Vivid E9 device (GE Vingmed). Images were postprocessed with good reproducibility by 1 expert (T.K.) blinded to the participants’ characteristics (eAppendix in the Supplement).4 Using clinically recommended criteria5,6 and population-based thresholds predictive of cardiac events,7,8 we defined (1) left ventricular (LV) concentric remodeling as relative wall thickness more than 0.425,6; (2) LV hypertrophy (LVH) as LV mass more than 50 g/m2.7 in men and more than 47 g/m2.7 in women5; (3) abnormal absolute LV longitudinal strain (LS) as LS below 17.4% in men and 18.5% in women7; and (4) early-stage LV diastolic dysfunction8 as reported previously.3
Statistical Analysis
We used SAS statistical software version 9.4 (SAS Institute) for database management and analysis. We normalized the 10-year HF risk score by log transformation. We calculated C statistics and Greenwood-Nam-D’Agostino χ2 to evaluate the performance and calibration of the PCP-HF score for prediction of symptomatic HF, respectively. With the HF risk score on both a continuous and categorical scale, we assessed the association between the 10-year predicted HF risk and echocardiographic indexes of LV structure and function (simple linear regression) and subclinical echocardiographic abnormalities (simple logistic regression). In addition, we investigated the association between the PCP-HF score components and subclinical LV remodeling and dysfunction in multiple logistic regression to identify the parameters driving the associations between the 10-year predicted risk and echocardiographic abnormalities. The level of significance was 2-sided P < .05. Analysis began February 2020 and ended April 2020.
Results
Clinical Characteristics and Model Performance
The Table presents the clinical characteristics including the PCP-HF score components and echocardiographic data for the entire cohort (N = 1020) and per HF risk score category (low, ≤0.4% [n = 340]; intermediate, 0.4%-2.4% [n = 340]; and high, ≥2.4% [n = 340]). The mean (SD) age was 52.8 (11.4) years, 541 (53.0%) were female, 435 (42.7%) had hypertension, and 523 individuals (51.3%) were receiving antihypertensive treatment. The HF incidence rate in this cohort free of prevalent cardiovascular disease at baseline was 1.37 events per 1000 person-years (10 events in total). The PCP-HF risk score demonstrated excellent discrimination (area under the curve, 0.90; 95% CI, 0.81-0.98) and good calibration (Greenwood-Nam-D’Agostino χ2 P = .38) for prediction of incident HF during a median (interquartile range) follow-up period up 6.7 (4.3-9.4) years. Individuals with high 10-year HF risk score (>2.4%) at baseline were associated with having significantly higher risk for future cardiac events than those with low to intermediate predicted HF risk (eFigure in the Supplement). However, within the group of individuals with high HF risk score at baseline, the presence of at least 2 echocardiographic abnormalities (ie, LV remodeling, diastolic dysfunction, and/or abnormal global LS) was associated with worse cardiac outcome compared with those with no or only 1 LV abnormality (eFigure in the Supplement).
Table. Clinical and Echocardiographic Characteristics of the Study Participants Among 10-Year Heart Failure (HF) Risk Score Tertiles.
| Characteristic | Mean (SD) | P value for trend | |||
|---|---|---|---|---|---|
| All (N = 1020) | 10-y HF risk | ||||
| ≤0.4% (n = 340) | 0.4%-2.1% (n = 340) | ≥2.1% (n = 340) | |||
| Clinical data | |||||
| Age, y | 52.8 (11.4) | 41.2 (6.0) | 52.8 (5.5) | 64.4 (7.2) | <.001 |
| Female, No. (%) | 541 (53.0) | 222 (65.3) | 168 (49.4) | 151 (44.4) | <.001 |
| BMI | 26.6 (4.2) | 25.0 (4.0) | 26.6 (4.0) | 28.1 (4.1) | <.001 |
| Blood pressure, mm Hg | |||||
| Systolic | 129.7 (16.4) | 120.2 (11.9) | 129.6 (14.1) | 139.4 (16.8) | <.001 |
| Diastolic | 82.0 (9.3) | 83.1 (7.1) | 83.9 (9.1) | 90.7 (15.5) | <.001 |
| Hypertension, No. (%) | 435 (42.7) | 44 (12.9) | 143 (42.1) | 248 (72.9) | <.001 |
| Treated for hypertension, No. (%) | 223 (21.9) | 5 (1.5) | 50 (14.7) | 168 (49.4) | <.001 |
| Fasting glucose level, mg/dL | 86.6 (11.9) | 83.1 (7.1) | 86.2 (10.4) | 90.7 (15.5) | <.001 |
| History of diabetes, No. (%) | 40 (3.9) | 2 (0.6) | 6 (1.8) | 32 (9.4) | <.001 |
| Current smokers, No. (%) | 191 (18.7) | 49 (14.4) | 72 (21.2) | 70 (20.6) | .045 |
| Total cholesterol level, mg/dL | 202.3 (36.3) | 193.7 (36.5) | 206.8 (33.6) | 206.5 (37.2) | <.001 |
| HDL-C, mg/dL | 56.9 (14.8) | 59.0 (15.1) | 57.3 (14.7) | 54.5 (14.3) | <.001 |
| QRS duration, ms | 92.5 (13.2) | 90.9 (10.9) | 91.7 (10.2) | 94.9 (17.0) | <.001 |
| Echocardiographic data | |||||
| Relative wall thickness | 0.37 (0.06) | 0.35 (0.04) | 0.38 (0.05) | 0.40 (0.06) | <.001 |
| LV mass index, g/m2 | 90.3 (19.5) | 80.7 (15.4) | 90.5 (17.5) | 99.7 (20.5) | <.001 |
| E/e’ ratio | 7.10 (2.00) | 6.10 (1.23) | 6.94 (1.73) | 8.27 (2.26) | <.001 |
| LV global LS, % | 19.4 (2.2) | 19.7 (1.95) | 19.2 (2.0) | 19.3 (2.42) | .005 |
Abbreviations: BMI, body mass index (calculated as weight in kilograms divided by height in meters squared); HDL-C, high-density lipoprotein cholesterol; LS, longitudinal strain; LV, left ventricular.
SI conversion factor: To convert cholesterol to millimoles per liter, multiply by 0.0259; glucose to millimoles per liter, multiply by 0.0555.
Association Between 10-Year HF Risk Score and Echocardiographic Indexes of LV Structure and Function
In participants with high 10-year HF risk score, relative wall thickness, LV mass index, and E/e′ ratio were significantly higher, and LV global LS was lower compared with the low and intermediate HF risk groups (Table). In simple linear regression, a 2-fold increase in 10-year HF risk score was associated with higher relative wall thickness (0.010; 95% CI, 0.008-0.011), higher LV mass index (3.06 g/m2; 95% CI, 2.65-3.47), higher E/e′ (0.35; 95% CI, 0.31-0.39), and lower global LS (−0.07%; 95% CI, −0.12 to −0.02) (P ≤ .006).
Association Between 10-Year HF Risk Score and Subclinical LV Remodeling and Dysfunction
We observed a higher proportion of LV remodeling and dysfunction from low to intermediate and high 10-year HF risk score (Figure 1A). In simple logistic regression, the probability for maladaptive LV phenotypes was directly associated with higher 10-year HF risk score on a continuous scale (Figure 1B). As such, a doubling in 10-year HF risk score was associated with higher odds for LV concentric remodeling (odds ratio [OR], 1.48; 95% CI, 1.36-1.61; P < .001), for LVH (OR, 1.66; 95% CI, 1.51-1.83; P < .001), for abnormal LS (OR, 1.12; 95% CI, 1.05-1.19; P < .001), and for LV diastolic dysfunction (OR, 2.28; 95% CI, 1.94-2.69; P < .001). Moreover, the HF risk score on a continuous scale distinguished abnormal from normal phenotypes with an accuracy of 74% (LV concentric remodeling), 78% (LVH), 59% (abnormal LS), and 87% (LV diastolic dysfunction). In participants with high 10-year HF risk score (≥2.4%), the likelihood of LV concentric remodeling, LVH, and LV diastolic dysfunction were 3.1, 3.8, and 9.4 times higher than the average population risk, respectively.
Figure 1. Prevalence and Probability of Subclinical Left Ventricular (LV) Abnormalities by 10-Year Heart Failure (HF) Risk Score.
B, Probability lines for the presence of LV abnormalities are presented (left y-axis) together with a histogram depicting the distribution of the 10-year HF risk score in the study population (right y-axis). The shaded areas represent the 95% CI of the predicted probability lines. LS indicates longitudinal strain.
aP < .05 vs ≤0.4% HF risk (first tertile).
bP < .05 vs <2.4% HF risk (first and second tertile).
Association Between PCP-HF Score Components and LV Remodeling and Dysfunction
Figure 2 presents the mutually adjusted associations between the PCP-HF score components and subclinical echocardiographic abnormalities. Age, body mass index, and systolic blood pressure were the main associations with LV remodeling and dysfunction profiles (Figure 2).
Figure 2. Multivariable-Adjusted Risk for Subclinical Left Ventricular (LV) Maladaptation by Pooled Cohort Equations to Prevent Heart Failure Risk Score Components.
Per risk factor, odds ratios and 95% CIs were adjusted for the other risk score components. BMI indicates body mass index (calculated as weight in kilograms divided by height in meters squared); BP, blood pressure; HDL-C, high-density lipoprotein cholesterol; LS, longitudinal strain; NA, not applicable.
SI conversion factor: To convert cholesterol to millimoles per liter, multiply by 0.0259.
Discussion
We observed a strong association between 10-year calculated HF risk and the likelihood for subclinical heart remodeling and dysfunction. This concordance seemed predominantly driven by age, obesity, and hypertension, 3 key risk factors of HF incorporated in the PCP-HF score.9 Overall, PCP-HF risk scoring adequately detected individuals with maladaptive LV phenotypes that precede HF symptoms by years and may thus be a valuable HF prediction tool in primary prevention. In the future, PCP-HF estimations might steer the discussion between individuals at substantial HF risk and clinicians and help decide on the type and intensity of preventive measures. For this, large-scale studies should examine the cost-effectiveness of preselecting asymptomatic but high-risk individuals using HF risk grading for guiding downstream testing and initiating preventive strategies to block the transition from subclinical to overt HF.
Limitations
This study had limitations. First, echocardiographic measurements are prone to errors owing to signal noise, acoustic artifacts, and angle dependency. However, echocardiographic images were recorded using a standardized protocol and postprocessed with good reproducibility. Second, the participation of exclusively White individuals may limit the extrapolation of our findings to other races/ethnicities.
Conclusions
In this study, PCP-HF risk scoring adequately detected individuals with subclinical heart maladaptation that precedes HF symptoms by years. Thus, it may be a valuable HF prediction tool in primary prevention.
eAppendix. Reproducibility of echocardiographic measurements
eReferences.
eFigure. Kaplan-Meier Survival Estimates for Cardiac Events by 10-Year HF Risk Score and Subclinical Echocardiographic Abnormalities
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Associated Data
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Supplementary Materials
eAppendix. Reproducibility of echocardiographic measurements
eReferences.
eFigure. Kaplan-Meier Survival Estimates for Cardiac Events by 10-Year HF Risk Score and Subclinical Echocardiographic Abnormalities
