Abstract
Objectives
To evaluate the course, correlates, and prognosis of longitudinal changes in left ventricular (LV) diastolic dysfunction (DD) in the community-based Framingham Heart Study.
Background
Relations of clinical risk factors to longitudinal progression of DD are incompletely understood.
Methods
Diastolic function was assessed by echocardiography at consecutive examinations (Visits 1 and 2, mean interval 5.6 years) in 1740 participants (age 64±8 years at Visit 1, 59% women) with normal LV systolic function and no atrial fibrillation.
Results
Of 1615 individuals with normal-mild DD at Visit 1, 198 (12%) progressed to ≥moderate DD at Visit 2. Progression was more likely in women and with advancing age (P<0.0001). Of 125 individuals with ≥moderate DD at Visit 1, 25 (20%) regressed to normal-mild DD by Visit 2. Regression of DD was associated with younger age (P<0.03). In stepwise regression models, age, female sex, baseline and change for systolic blood pressure, diastolic blood pressure, body mass index, serum triglycerides, heart rate, and diabetes were positively associated with worsening diastolic function (all P<0.05). Non-cardiac comorbidity tracked with progressive DD. Cardiovascular disease (CVD)/death events occurred in 44 or 1509 participants free of CVD at visit 2 during 2.7±0.6 years of post Visit 2 follow-up. Presence of ≥moderate DD was associated with higher risk (age- and sex-adjusted hazard ratio for CVD/death, 2.14; 95% CI, 1.06–4.32; P=0.03).
Conclusions
In a community-based cohort of middle-age to older adults, cardiometabolic risk factors and non-cardiac comorbidities were associated with DD progression. Moderate or worse DD was associated with higher CVD/death risk.
Keywords: Diastolic function, prevention, cardiometabolic risk factors
INTRODUCTION
Left ventricular (LV) diastolic dysfunction (DD) may represent an intermediate stage in the development of cardiovascular disease (CVD) in older individuals, and is associated with a number of conditions including heart failure (HF) (1–4), atrial fibrillation (5,6), and cardiovascular mortality (7,8). The pathophysiologic link between LV DD and HF with preserved ejection fraction (HFpEF) is particularly strong as progression of subclinical DD is thought to contribute to the pathogenesis of the syndrome (9). HFpEF currently accounts for approximately half of new HF diagnoses, and its prevalence relative to HF with reduced ejection fraction (HFrEF) continues to rise (10). As treatment options for HFpEF remain limited (11), despite its considerable morbidity and mortality (12), prevention of HFpEF is vital to individual and population health. Hence, it is critical to understand factors that contribute to the development and progression of LV DD.
Several previous reports have demonstrated the associations of LV DD with modifiable cardiometabolic risk factors such as blood pressure and body mass index (BMI) (13,14). However, strong relations of age with LV DD and risk factor burden may partially obscure cross-sectional associations between LV DD and risk factors (15–18). Examining relations of cardiometabolic traits with longitudinal changes in diastolic function measures may thus provide further insight into key contributors to the progression of DD. In addition to traditional cardiovascular risk factors, non-cardiac morbidity – such as chronic kidney disease, chronic lung disease, musculoskeletal weakness, generalized systemic inflammation, and frailty – also predates HF and appears closely related to the development and the prognosis of HFpEF (2,19,20). The association of non-cardiac comorbidity with the longitudinal progression of LV DD has not been well elucidated.
Accordingly, we sought to evaluate the course, predictors (both cardiac and non-cardiac), and prognostic significance of longitudinal changes in LV diastolic function over a six-year period in a moderately-sized, community-based cohort consisting of individuals mostly 60–70 years of age, when CVD incidence accelerates. We hypothesized that prevalent and worsening cardiometabolic risk factors and comorbidity burden are positively associated with adverse changes in common echocardiographic measures of LV diastolic function, and that worsening LV DD over time is associated with a higher risk of future CVD.
METHODS
Study Sample
The design and enrollment of the Framingham Offspring and Omni Generation 1 cohorts have been detailed (21,22). We included Framingham Offspring participants who attended both the 8th (2005–2008, Visit 1) and the 9th (2011–2014, Visit 2) examination cycles, and Omni Generation 1 participants who attended their 3rd (2007–2008, Visit 1) and 4th (2011–2014, Visit 2) examinations. From 2478 participants attending both examinations, we excluded individuals as follows: missing LV diastolic function indices (N=290), baseline LV wall motion abnormalities (N=78), interim myocardial infarction between examinations (N=43), left ventricular systolic dysfunction (defined as fractional shortening ≤0.29 or 2D evidence of ≥mild LV systolic dysfunction; N=21), ≤ moderate valvular disease (N=105), paced rhythm (N=18), atrial fibrillation at the time of echo (N=2), or missing covariates (N=181). The final sample of 1740 was used to evaluate predictors of longitudinal changes in LV diastolic function. To evaluate associations of non-cardiac comorbidities with DD progression, we excluded an additional 339 individuals with missing comorbidity measures. For prospective analyses relating longitudinal changes in diastolic function with incident CVD, we excluded participants with prevalent CVD at Visit 2 (N=231); Supplemental Figure 1. All participants provided informed consent and the Boston University Medical Center Institutional Review Board approved all study protocols.
Echocardiography
Two-dimensional echocardiography with Doppler color flow imaging was performed at both examination visits (details in Supplemental Material). We characterized LV diastolic function as normal, mild DD, moderate DD, or severe DD using the modified Olmsted criteria (excluding mitral inflow velocities during the Valsalva maneuver and pulmonary venous flow patterns, which were not available for the present investigation) (7,23). The following criteria were used: normal LV diastolic function, E/A >0.75 and E/E′ <10; mild DD, E/A ≤0.75 and E/E′ <10; moderate DD, E/A ≤1.5 and E/E′ ≥10; severe DD, E/A >1.5 and E/E′ ≥10.
Covariates
A comprehensive medical history, cardiovascular-focused clinical examination, anthropometry, and phlebotomy were performed at each Framingham Heart Study examination. Details of the assessment of clinical covariates are provided in the Supplemental Material.
Comorbidity Assessment and Score
Select measures representing kidney (estimated glomerular filtration rate [eGFR]) and lung function (forced expiratory volume in 1 second [FEV1] to forced vital capacity [FVC] ratio), musculoskeletal weakness (handgrip), frailty (gait speed), and general inflammation (C-reactive protein, CRP) were combined to calculate a ‘comorbidity score’ for each participant using measures available at both examination cycles (details in Supplemental Material). We then calculated a composite ‘comorbidity score’ by assigning a value of 0 to referent values and 1 to abnormal values (‘comorbidity score’ range 0–5) for each component of the score.
Clinical Outcome Ascertainment
FHS participants are under longitudinal surveillance for the development of cardiovascular outcomes, which are adjudicated by a committee of three investigators after review of pertinent medical records. Our outcome was a composite of first CVD event or death. CVD events were defined as follows: fatal and nonfatal myocardial infarction, acute coronary syndromes without myocardial necrosis, angina, stroke or transient ischemic attack, intermittent claudication, or HF using standardized Framingham criteria (24).
Statistical Analysis
We displayed characteristics separately for the first and second visits. For categorical analyses, we defined DD as ≥ moderate LV DD due to the small number of individuals with severe DD in our sample, and we identified four categories to characterize longitudinal changes in DD (Table 1). ‘Progressors’ had normal-mild LV DD at baseline and moderate-severe LV DD at follow-up; ‘regressors’ had moderate-severe LV DD at baseline and normal-mild LV DD at follow-up; ‘normal’ had normal-mild LV DD at both examination cycles, and ‘stable DD’ had moderate-severe LV DD at both examination cycles. In secondary analyses, we tested two alternate categorization schemes: 1) normal versus ≥mild DD; 2) using three different categories (i.e., normal, mild DD, moderate-severe DD (Supplemental Table 1).
Table 1.
Diastolic dysfunction “change categories.”
| Diastolic function category | Visit 2 | |
|---|---|---|
| Visit 1 | Normal-mild DD | Moderate-severe DD |
| Normal-mild DD | ‘Normal’ | ‘Progressors’ |
| Moderate-severe DD | ‘Regressors’ | ‘Stable DD’ |
DD = diastolic dysfunction
Using stepwise multivariable-adjusted regression models, we evaluated the relations of clinical predictors (including both baseline and longitudinal changes in these variables) with longitudinal changes in quantitative echocardiographic measures of LV DD or with categories of longitudinal changes in DD. Baseline predictor variables, the baseline value of the echocardiographic variable being analyzed, and the interval between attendance at the two examinations were forced into the models. For each continuous predictor variable, a ‘change variable’ (Δ) was calculated as the difference between visits (Visit 2 – Visit 1). For binary variables (e.g., smoking), the ‘change variable’ was defined as a different value at the two examination cycles (e.g., starting smoking or stopping smoking) and modeled as a 3-level categorical variable. All continuous variables were standardized to mean=0 and standard deviation (SD)=1. We tested effect modification by age and sex on the associations of changes in clinical predictors and changes in continuous echocardiographic measures of LV diastolic function using multiplicative interaction terms.
In prospective analyses, we used Cox proportional hazards regression models to relate the four DD change categories with incident CVD or mortality. Multivariable models were adjusted for age, and sex (model 1), and then additionally adjusted for clinical CVD risk factors including systolic blood pressure, hypertension treatment status, BMI, diabetes, smoking, heart rate, ln(triglycerides), and total/HDL cholesterol at Visit 2. We tested the proportionality of hazards assumption by assessing the interaction of DD categories with log(survival time).
We also tested the association of the comorbidity score with the presence of moderate-severe LV DD at the later examination (i.e., ‘progressors’ and ‘stable DD’) using logistic regression models adjusted for age and sex.
We used a two-sided p-value <0.05 to determine statistical significance and we performed all analyses with SAS version 9.4 (Cary, NC).
RESULTS
Characteristics for the 1740 study participants (1027 women, 59%) are displayed in Table 2. The mean age was 64 years at Visit 1 and 70 years at Visit 2. During an average of 5.6±0.5 years (range 3.6–7.5 years) between Visits 1 and 2, changes in the mean values for clinical risk factors were modest. Notably, the proportion of participants on hypertension or lipid lowering treatment increased. Sex differences in baseline characteristics (Supplemental Table 2) were most pronounced for measures of LV diastolic function, which were less optimal in women. The prevalence of ≥ moderate LV DD was higher in women during both examinations.
Table 2.
Characteristics of the study sample
| Characteristic | Visit 1 (N=1740) | Visit 2 (N=1740) |
|---|---|---|
| Age, years | 64±8 | 70±8 |
| Female sex, N (%) | 1027 (59) | - |
| Race, nonwhite, N (%) | 201 (12) | - |
| Systolic blood pressure, mm Hg | 138±19 | 137±18 |
| Diastolic blood pressure, mm Hg | 70±8 | 65±9 |
| Body mass index, kg/m2 | 28.1±5.3 | 28.3±5.3 |
| Total/HDL cholesterol | 3.5±1.0 | 3.1±0.9 |
| Triglycerides, mg/dL | 115±65 | 112±53 |
| Fasting glucose, mg/dL | 104±20 | 102±20 |
| Heart rate, beats per minute | 61±10 | 62±9 |
| Hypertension treatment, N (%) | 782 (45) | 919 (53) |
| Current smoking, N (%) | 125 (7) | 116 (7) |
| Lipid lowering treatment, N (%) | 660 (38) | 870 (50) |
| Diabetes, N (%) | 175 (10) | 243 (14) |
| E wave velocity (cm/s) | 64.1±12.7 | 67.6±13.7 |
| A wave velocity (cm/s) | 69.1±14.5 | 71.3±16.6 |
| E/A ratio | 1.0±0.2 | 1.0±0.3 |
| Lateral E′ velocity (cm/s) | 9.8±2.1 | 8.9±1.9 |
| E/E′ ratio | 6.8±2.0 | 8.0±2.4 |
| LV Diastolic dysfunction ≤ moderate, N (%) | 125 (7) | 288 (17) |
|
| ||
| Comorbidity traits | Visit 1 (N=1401) | Visit 2 (N=1401) |
|
| ||
| Kidney dysfunction (eGFR <60), N (%) | 105 (8) | 281 (20) |
| FEV1/FVC <20th percentile, N (%) | 276 (20) | 291 (21) |
| CRP (>80th percentile), N (%) | 269 (19) | 292 (21) |
| Handgrip (<20th percentile), N (%) | 219 (16) | 328 (23) |
| Gait (>80th percentile), N (%) | 227 (16) | 336 (24) |
| Comorbidity score, mean ± SD | 0.8 ± 0.9 | 1.1 ± 1.1 |
Percentiles for comorbidity traits were calculated from pooled samples by combining observatons from the two examination cycles.
Natural History of DD
LV DD ≥ moderate in severity increased in prevalence between visits. Of the 1615 individuals with normal-mild DD at the baseline examination cycle, 198 (12%) developed moderate-severe DD between visits (Figure 1 and Supplemental Table 3). Women were more likely than men to progress between visits. The rate of progression increased with age (Figure 1). Conversely, of the 125 individuals with moderate-severe DD at Visit 1, 25 (20%) were categorized as having normal-mild DD at Visit 2 (Figure 1 and Supplemental Table 3). Younger age was associated with higher odds of regression of LV DD.
Figure 1. Longitudinal course of progression or regression of DD by sex and age.
Progressors were defined by normal-mild diastolic dysfunction at Visit 1 and moderate-severe DD at Visit 2. Regressors were defined by moderate-severe DD at Visit 1 and normal-mild diastolic dysfunction at Visit 2. The proportion of progressors therefore consisted of the ratio of individuals with ≥moderate DD at Visit 2 and normal diastolic function at Visit 1, and the proportion of regressors consisted of the ratio individuals with normal-mild DD at Visit 2 out of those with ≥moderate DD at Visit 1. Odds ratios (ORs) for progressing represent the relative odds of progressing to moderate-severe DD at Visit 2 given normal-mild DD at Visit 1 compared to the referent group. ORs for regressing represent the relative odds of regressing from moderate-severe diastolic dysfunction at Visit 1 to normal-mild diastolic dysfunction at Visit 2 cycle compared to the referent group. ORs for the ‘by sex’ analysis are adjusted for age group, and the ‘by age group’ analyses are adjusted for sex.
Longitudinal Changes in Risk Factors Relate to Progression of DD
We observed a negative relation between changes in the E/A ratio and age, diastolic blood pressure (baseline and change), triglycerides (baseline and change), and heart rate (baseline and change; P for all <0.05), Table 3. Changes in the component measures of E and A velocities were, in turn, related to a number of clinical variables (Supplemental Table 5). Decrements in the E′ velocity also was associated with higher age, female sex, systolic blood pressure (baseline and change), diastolic blood pressure (baseline and change), change in BMI, heart rate (baseline and change), and baseline diabetes (P for all <0.03). Rising E/E′ ratio between the examination cycles was directly associated with age, female sex, change in systolic blood pressure, and baseline diabetes (P <0.01).
Table 3.
Multivariable-adjusted associations of clinical predictors with longitudinal changes in LV diastolic function traits
| Predictor | Change in E/A | Change in E′ (cm/s) | Change in E/E′ | |||
|---|---|---|---|---|---|---|
| Est beta ± SE | P value | Est beta ± SE | P value | Est beta ± SE | P value | |
| Age | −0.02±0.01 | 0.005 | −0.30±0.04 | <0.0001 | 0.35±0.05 | <0.0001 |
| Female sex | −0.01±0.01 | 0.36 | −0.51±0.07 | <0.0001 | 0.70±0.09 | <0.0001 |
| Systolic blood pressure | −0.01±0.01 | 0.18 | −0.11±0.05 | 0.02 | 0.11±0.06 | 0.06 |
| Δ Systolic blood pressure | -- | -- | −0.12±0.04 | 0.006 | 0.22±0.05 | <0.0001 |
| Diastolic blood pressure | −0.02±0.01 | 0.05 | −0.10±0.05 | 0.03 | 0.05±0.05 | 0.28 |
| Δ Diastolic blood pressure | −0.02±0.01 | 0.004 | −0.13±0.05 | 0.005 | -- | -- |
| BMI | 0.00±0.01 | 0.94 | −0.07±0.04 | 0.06 | 0.05±0.05 | 0.26 |
| Δ BMI | -- | -- | −0.13±0.03 | 0.0002 | -- | -- |
| Total/HDL cholesterol | 0.01±0.01 | 0.51 | −0.02±0.05 | 0.63 | −0.05±0.06 | 0.39 |
| Δ Total/HDL cholesterol | -- | -- | -- | -- | -- | -- |
| ln(Triglycerides) | −0.02±0.01 | 0.02 | −0.01±0.05 | 0.88 | 0.06±0.06 | 0.32 |
| Δ ln(Triglycerides) | −0.03±0.01 | <0.0001 | -- | -- | -- | -- |
| Heart rate | −0.04±0.01 | <0.0001 | −0.12±0.04 | 0.004 | −0.03±0.04 | 0.50 |
| Δ Heart rate | −0.05±0.01 | <0.0001 | −0.17±0.04 | <0.0001 | -- | -- |
| Hypertension treatment status | −0.00±0.01 | 0.97 | 0.02±0.08 | 0.75 | −0.11±0.09 | 0.22 |
| Smoking | −0.03±0.02 | 0.13 | 0.03±0.13 | 0.79 | −0.21±0.16 | 0.21 |
| Diabetes | 0.00±0.02 | 0.86 | −0.35±0.12 | 0.003 | 0.36±0.15 | 0.01 |
The estimated beta coefficients represent the estimated change in the echocardiographic trait for each 1-SD higher value of the predictor variable.
Δ indicates continuous ‘change variables’ which are defined as the follow-up value minus the baseline value
Each 1 SD is equal to: 7.9 years for age, 18.7 mm Hg for systolic blood pressure, 16.4 mm Hg for change in systolic blood pressure, 8.5 mm Hg for diastolic blood pressure, 8.4 mm Hg for change in diastolic blood pressure, 5.3 kg/m2 for BMI, 2.1 kg/m2 for change in BMI, 1.0 for total/HDL cholesterol, 0.8 for change in total/HDL cholesterol, 0.5 for ln(triglycerides), 0.4 for change in ln(triglycerides), 9.5 beats per minute for heart rate, 8.5 beats per minute for change in heart rate.
The multivariable models are additionally adjusted for the interval between the 2 examination cycles and the baseline value of the echocardiographic trait. Fasting glucose, change in fasting glucose, change in hypertension treatment status, change in smoking, and change in diabetes were included as potential predictor variables but did not meet criteria for model inclusion.
When DD was analyzed as a categorical variable, we observed similar associations between modifiable risk factors and the presence or progression of DD (Table 4). Specifically, age, female sex, systolic blood pressure (baseline and change), baseline BMI, baseline diabetes, and development of diabetes during follow-up were positively associated with stable or progressive DD, and baseline heart rate was inversely associated (P ≤0.03).
Table 4.
Multivariable-adjusted associations of clinical predictors with LV diastolic dysfunction
| Predictor | Stable or progressive LV DD | Progressive LV DD* | ||
|---|---|---|---|---|
| Odds Ratio (95% CI) | P value | Odds Ratio (95% CI) | P value | |
| Age | 1.87 (1.56–2.25) | <0.0001 | 1.68 (1.39–2.02) | <0.0001 |
| Female sex | 3.70 (2.57–5.32) | <0.0001 | 3.20 (2.19–4.68) | <0.0001 |
| Systolic blood pressure | 1.27 (1.03–1.55) | 0.02 | 1.19 (0.96–1.47) | 0.11 |
| Δ Systolic blood pressure | 1.33 (1.12–1.57) | 0.0011 | 1.30 (1.10–1.55) | 0.003 |
| Diastolic blood pressure | 0.99 (0.82–1.18) | 0.88 | 0.98 (0.81–1.18) | 0.79 |
| Δ Diastolic blood pressure | -- | -- | -- | -- |
| Baseline BMI | 1.27 (1.08–1.48) | 0.003 | 1.26 (1.07–1.48) | 0.005 |
| Δ BMI | -- | -- | -- | -- |
| Total/HDL cholesterol | 0.97 (0.79–1.20) | 0.80 | 0.98 (0.79–1.22) | 0.88 |
| Δ Total/HDL cholesterol | -- | -- | -- | -- |
| ln(Triglycerides) | 1.15 (0.93–1.43) | 0.19 | 1.21 (0.97–1.51) | 0.10 |
| Δ ln(Triglycerides) | -- | -- | -- | -- |
| Heart rate | 0.84 (0.72–0.99) | 0.03 | 0.83 (0.71–0.98) | 0.03 |
| Δ Heart rate | -- | -- | -- | -- |
| Hypertension treatment status | 0.92 (0.66–1.29) | 0.64 | 0.84 (0.59–1.19) | 0.32 |
| Smoking | 0.85 (0.44–1.61) | 0.61 | 0.82 (0.41–1.65) | 0.58 |
| Diabetes | 1.94 (1.18–3.17) | 0.009 | 1.60 (0.98–2.62) | 0.06 |
| Change in diabetes status | ||||
| 1. No at visit 1, yes at visit 2 | 2.43 (1.30–4.54) | 0.005 | -- | -- |
| 2. Yes at visit 1, no at visit 2 | 0.26 (0.03–2.31) | 0.22 | -- | -- |
Odds ratios represent the odds of having the outcome for each 1-SD higher value of the predictor variable.
Δ indicates continuous ‘change variables’ which are defined as the follow-up value minus the baseline value
1 SD is equal to: 7.9 years for age, 18.7 mm Hg for systolic blood pressure, 16.4 mm Hg for change in systolic blood pressure, 8.5 mm Hg for diastolic blood pressure, 8.4 mm Hg for change in diastolic blood pressure, 5.3 kg/m2 for BMI, 2.1 kg/m2 for change in BMI, 1.0 for total/HDL cholesterol, 0.8 for change in total/HDL cholesterol, 0.5 for ln(triglycerides), 0.4 for change in ln(triglycerides), 9.5 beats per minute for heart rate, 8.5 beats per minute for change in heart rate.
The multivariable models are additionally adjusted for the interval between the 2 examination cycles and the baseline value of the echocardiographic trait. Fasting glucose, change in fasting glucose, change in hypertension treatment status, and change in smoking status were included as potential variables but did not meet criteria for model inclusion.
In secondary analyses, we included ln(CRP), ln(insulin), and eGFR (and their change variables) as potential predictor variables (Supplemental Tables 7 and 8). After adjusting for all other clinical variables, we did not observe statistically significant associations between eGFR or CRP with diastolic function measures. We did observe an association for an increase in insulin concentration over time with a reduction in E/A ratio but it was not associated with stable or progressive DD.
We evaluated for effect modification by age and sex on the cross-sectional associations of clinical predictors with diastolic function traits and observed several nominally significant interactions (Supplemental Table 10).
Burden of Non-cardiac Comorbidity Relates to DD Progression
We examined the relations of a ‘comorbidity score’ with the progression of DD. The mean ‘comorbidity score’ increased between the two Visits (Table 2), and was higher in individuals with more advanced DD (Table 5). Each 1-unit higher comorbidity score at Visit 1 was associated with a 27% higher odds of having moderate-severe DD at Visit 2 (‘progressors’ or ‘stable DD’) in age- and sex-adjusted analyses (95% CI 1.06–1.53, p=0.01).
Table 5.
Average comorbidity score across visits by DD change category
| DD Change Category | Mean Score |
|---|---|
| Normal or regressors (N=1187) | 0.87 ± 0.82 |
| Stable DD or progressors (N=214) | 1.33 ± 1.09 |
|
| |
| Normal (N=1159) | 0.86 ± 0.81 |
| Regressors (N=28) | 1.05 ± 0.88 |
| Progressors (N=152) | 1.19 ± 1.04 |
| Stable DD (N=62) | 1.66 ± 1.15 |
Association of DD Category with Incident CVD
During follow-up after the second examination cycle (2.7±0.6 years), we observed events in 44 participants (17 deaths, 27 incident CVD – 5 HF, 6 myocardial infarction, 7 angina-coronary insufficiency, and 9 stroke/TIA). Compared with individuals with normal or improved DD, those with moderate-severe DD at Visit 2 (‘progressors or stable DD’) had a greater than twofold higher risk of CVD in age- and sex-adjusted models that was partially attenuated upon adjustment for clinical risk factors (Table 6). Compared with individuals with normal diastolic function at both visits, individuals with stable DD had the highest CVD risk, with a >2.5-fold higher relative hazard (Supplemental Tables 12 and 13).
Table 6.
Incidence of CVD or death after Visit 2
| DD change category | # events/# at risk | Age- and sex-adjusted HR (95% CI) |
P value | Multivariable-adjusted* HR (95% CI) |
P value |
|---|---|---|---|---|---|
| Normal or regressors | 29/1275 | Referent | Referent | ||
| Stable DD or progressors | 15/234 | 2.14 (1.06 – 4.32) | 0.03 | 1.81 (0.87 – 3.79) | 0.11 |
Multivariable model is adjusted for age, sex, systolic blood pressure, body mass index, diabetes, hypertension treatment status, smoking, heart rate, ln(triglycerides), and total/HDL cholesterol
DISCUSSION
We evaluated the course, correlates, and prognostic significance of longitudinal changes in LV DD in a predominantly middle aged or older community-based sample. There are several key findings: 1) LV diastolic function generally worsens over time in older people, especially in women and at older ages; 2) some individuals with LV DD can improve or regress to the mean, which is more common at younger ages; 3) modifiable cardiometabolic risk factors (both baseline values and changes over time) are related to worsening diastolic function and progression of LV DD; 4) progression of general (non-cardiac) comorbidity tracks in parallel with worsening DD in this age group; and, 5) the presence of moderate-severe LV DD at Visit 2 was associated with the composite outcome of incident CVD or death. Taken together, these findings demonstrate that worsening clinical risk profiles in the 7th to 8th decades of life are associated with progressive LV DD, and that progressive LV DD is associated with adverse cardiovascular outcomes.
Longitudinal Changes in Risk Factors Predict Worsening LV Diastolic Function
Cardiometabolic risk factors – blood pressure and BMI in particular – have been linked with LV DD in previous reports (13,14), but predictors of longitudinal changes in diastolic function are incompletely understood. From the Olmsted County Heart Function Study, Kane and colleagues demonstrated that DD worsened over time and that progressive DD was associated with incident HF in a sample of individuals with mean age of 61 years (3). In a younger cohort than ours, with a mean age of 50 years, Kuznetsova and colleagues examined the correlates of progressive LV DD and observed that advanced age, higher baseline insulin level, baseline and change in heart rate, baseline blood pressure, change in systolic blood pressure, and initiation of antihypertensive therapy were directly associated with progressive LV DD (25). Our findings, therefore, complement and extend previous reports to a sample approximately 10–15 years older (on average) and underscore the contributions of numerous cardiometabolic risk factors to decrements in LV diastolic function. Indeed, longitudinal increases in systolic and diastolic blood pressure, BMI, serum triglycerides, heart rate, and diabetes were all found to predict worsening diastolic function in our sample. Although observational, these longitudinal findings support the hypothesis that adverse changes in cardiometabolic risk profiles may promote DD progression in this age group.
Factors Associated with Regression of LV Diastolic Dysfunction
In our study, some individuals with moderate-severe LV DD at baseline were observed to have regression of their DD at the follow-up examination. Transition to more favorable LV diastolic function was more common in younger individuals and a trend favoring a higher odds of LV DD regression in men was observed. To the best of our knowledge, no previous studies have evaluated factors related to amelioration of DD in community-based individuals free of manifest HF. One potential explanation for these findings is “regression to the mean” over time, which might be expected to occur more frequently in younger individuals. However, data from prior studies does support the potential for improved LV DD in response to risk factor modification in select patients with HF (26,27). Our findings, therefore, are consistent with this limited previous evidence, and we speculate that targeting interventions to improve cardiometabolic profiles in individuals most likely to benefit (i.e., individuals at younger age and, potentially, men) may have a substantial impact on the burden of LV DD.
General Non-cardiac Comorbidity and LV Diastolic Dysfunction
Non-cardiac organ dysfunction is known to be highly prevalent in patients with HFpEF (28–31) and to be associated with risk for HFpEF development (19). However, previous reports of relations of non-cardiac predictors to the development of LV DD are scant. Comorbidities are theorized to partially contribute to HFpEF through the actions of associated inflammatory pathways on endothelial and myocyte function (32). These pathophysiologic mechanisms may partially explain the association we observed between advanced comorbidity and progressive LV DD by positing that shared mechanisms (such as systemic inflammation and simultaneous aging of interrelated organ systems) drive both. Other explanations for this observation include potential direct effects of comorbid conditions on LV diastolic function. Our findings are observational and exploratory, and therefore additional studies are warranted to evaluate the underlying mechanisms explaining the parallelism between progressive DD and advancing non-cardiac comorbidity.
Limitations and Strengths
The present investigation should be interpreted within the context of its limitations. Several echocardiographic features previously demonstrated to relate to LV diastolic function, such as the septal E′ velocity, left atrial size, regurgitant velocity through the tricuspid valve, pulmonary vein inflow, LV longitudinal strain, and mitral inflow during the Valsalva maneuver were not obtained due to time constraints during the FHS examination cycle. As a result, we were unable to grade LV DD using the more recent 2016 Guidelines (33). Future studies are warranted to extend our findings to the more contemporary guidelines. Visit 2 was recently performed (2011–2014) and the number of CVD events that have been observed since this cycle is, therefore, relatively low, which limits our ability to evaluate the association of longitudinal changes in LV DD with specific CVD outcomes, such as HF. Our study design required participants to attend 2 consecutive examination cycles. Individuals with DD at Visit 1 who did not attend Visit 2 were hence not available for analysis. The extent to which survival bias may have affected our findings is unknown. Our analyses were not adjusted for multiple comparisons; further studies are warranted to confirm our findings. Lastly, the generalizability of our results is limited to samples with similar charactertistics. Although our sample did include a smaller, non-white cohort, the majority of the study sample consisted of white individuals of European descent; we lacked sufficient numbers of non-European ancestry individuals to analyze differences among ethnic subgroups.
These limitations notwithstanding, our study has several important strengths. It was conducted in a moderate sized, community-based cohort with standardized assessments of echocardiograms, clinical variables (both cardiac and non-cardiac), and outcomes; the ability to analyze longitudinal measures of LV diastolic function in a cohort of this size is rare. Furthermore, our study sample consisted of individuals with a mean age of ~65–70 years, which is when HF risk climbs. As a result, our findings might be especially informative to HF prevention efforts.
CONCLUSIONS
In a large community-based sample, we observed that adverse changes in modifiable cardiometabolic risk factors, most notably rising blood pressure, gain in BMI, new-onset of diabetes, and increases in blood triglyceride concentrations relate to longitudinal deterioration in measures of LV diastolic function. Progression of LV DD was also related to increasing levels of non-cardiac comorbidity and to incidence of adverse CVD outcomes. While observational, our findings raise the possibility that interventions to improve cardiometabolic risk profiles, especially in younger individuals and before the risk factor burden is overwhelming, could be expected to improve LV DD, and potentially, prevent HF. Additional studies are needed to further explore this premise.
Supplementary Material
CLINICAL PERSPECTIVES.
Clinical relevance
Left ventricular diastolic dysfunction is associated with incident cardiovascular disease. Modifiable cardiovascular risk factors and non-cardiac comorbidity are associated with the progression of diastolic dysfunction.
Translational outlook
Future studies are warranted to investigate if improving cardiometabolic risk profiles results in improvements in (or prevention of) left ventricular diastolic dysfunction and, potentially, heart failure.
Acknowledgments
Funding sources: This work was partially supported by the National Heart, Lung and Blood Institute’s Framingham Heart Study (Contracts N01-HC-25195 and HHSN268201500001I) and by grants HL076784, G028321, HL070100, HL060040, HL080124, HL071039, HL077447, HL107385, HL126136, 2R01HL092577, 1R01HL128914, 1P50HL120163; and 2-K24-HL04334. Dr. Nayor received support from K23-HL138260 and training grant U10HL110337 from the NHLBI. Dr. Cooper is supported by the UNCF/Merck Science Initiative. Dr. Vasan is supported by an Evans Scholar award and Jay and Louis Coffman Foundation from the Department of Medicine, Boston University School of Medicine.
ABBREVIATION LIST
- LV
left ventricular
- DD
diastolic dysfunction
- CVD
cardiovascular disease
- HF
heart failure
- HFpEF
heart failure with preserved ejection fraction
- HFrEF
heart failure with reduced ejection fraction
- BMI
body mass index
- eGFR
estimated glomerular filtration rate
- FEV1
forced expiratory volume in 1 second
- FVC
forced vital capacity
- CRP
C-reactive protein
Footnotes
Disclosures: Dr. Mitchell is the owner of Cardiovascular Engineering, Inc., a company that develops and manufactures devices to measure vascular stiffness, serves as a consultant to and receives grants and honoraria from Novartis, Merck, Servier and Philips Healthcare.
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