Silent brain infarctions (SBI) and white matter hyperintensities (WMH) are associated with increased risk for stroke (1). Left atrial (LA) functional impairment is associated with increased cardiovascular events including stroke (2). Although LA volume measurement is the gold standard for the assessment of LA remodeling, LA strain (ε) and strain rate (SR) using speckle-tracking echocardiography provide additional prognostic information (2). However, it is not known whether LAε and SR are associated with subclinical cerebrovascular disease even in the presence of normal LA volumes. We examined the relationship between LAε and SR measured using speckle-tracking echocardiography and the presence of subclinical cerebrovascular disease on brain cardiac magnetic resonance in a predominantly elderly community-based cohort.
We examined LAε and SR in 270 participants (mean age 69.1 ± 9.7 years; 63.7% women) from the community-based CABL (Cardiac Abnormalities and Brain Lesions) study. SBI were present in 26 patients (9.6%); the upper quartile of WMH distribution (WMH4) was used in the analyses (68 participants). Speckle-tracking analysis was performed (Philips QLAB, version 8.1), and the following LAε measures were obtained: 1) LA reservoir function expressed as global peak positive longitudinal LAε (LAεpos) and SR (LASRpos) during ventricular systole; 2) LA conduit function expressed as global peak negative longitudinal SR (LASRearly-neg) during early ventricular diastole; and 3) LA pump function expressed as global peak negative longitudinal SR (LASRlate-neg) during LA contraction. The study was approved by the Institutional Review Board of Columbia University Irving Medical Center.
LA strain variables were independently associated with SBI, but not with WMH4 (Table 1). The addition of each LA strain parameter to other independent variables (age, hypertension, systolic blood pressure, left ventricular [LV] mass, LA volume, and LV global longitudinal strain) increased the predictive power for SBI (c-index from 0.67 to 0.77; p < 0.001 for all; integrated discrimination improvement from 0.096 to 0.123; p < 0.009 for all; net reclassification improvement from 0.419 to 0.733; p < 0.05 for all), but not for WMH4 (c-index from 0.77 to 0.78; p > 0.05 for all).
TABLE 1.
Association of LAε and LA SR With the Presence of SBI and WMH4: Multivariate Analysis
| OR | 95% CI | p Value | |
|---|---|---|---|
| SBI* | |||
| LAεpos | 2.43 | 1.62-3.65 | <0.001 |
| LV GLS | 1.18 | 1.01-1.37 | 0.036 |
| LASRpos | 2.37 | 1.64-3.44 | <0.001 |
| LV GLS | 1.18 | 1.01-1.38 | 0.036 |
| LASRearly-neg | 2.74 | 1.69-4.46 | <0.001 |
| LV GLS | 1.16 | 1.00-1.35 | 0.052 |
| LASRlate-neg | 2.98 | 1.81-4.89 | <0.001 |
| LV GLS | 1.19 | 1.02-1.39 | 0.027 |
| WMH4† | |||
| LAεpos | 1.42 | 0.98-2.05 | 0.063 |
| Age | 1.11 | 1.07-1.16 | <0.001 |
| Hypertension | 1.99 | 0.80-4.92 | 0.139 |
| LAVimin | 0.97 | 0.91-1.03 | 0.305 |
| LASRpos | 1.36 | 0.95-1.95 | 0.094 |
| Age | 1.11 | 1.07-1.16 | <0.001 |
| Hypertension | 1.93 | 0.78-4.78 | 0.154 |
| LAVimin | 0.97 | 0.91-1.03 | 0.346 |
| LASRearly-neg | 1.35 | 1.00-1.82 | 0.053 |
| Age | 1.10 | 1.06-1.14 | <0.001 |
| Hypertension | 1.84 | 0.80-4.24 | 0.154 |
| LASRlate-neg | 1.37 | 1.01-1.85 | 0.040 |
| Age | 1.10 | 1.07-1.15 | <0.001 |
| Hypertension | 1.89 | 0.82-4.35 | 0.137 |
Final model after stepwise variable selection (p = 0.30 for entry and 0.35 for stay) with age, LV mass index, LVEF, LV GLS, LAVimax, and LAVimin and each LAε
Final model after stepwise variable selection (p = 0.30 for entry and 0.35 for stay) with age, hypertension, SBP, LV mass index, LV GLS. and LAVimin and each LAε
CI = confidence interval; LAε = left atrial strain; LAVimax = left atrial maximum volume index; LAVimin = left atrial minimum volume index; LV GLS = left ventricular global longitudinal strain; OR = odds ratio; SBI =silent brain infarcts; SBP = systolic blood pressure; SR = strain rate; WMH4 = white matter hyperintensities volume.
In the past, we reported that LA minimum volume and LA ejection fraction were strongly associated with SBI and WMH (3). However, this is the first time to our knowledge that LA strain variables, which may detect LA dysfunction before LA enlargement occurs (2), has been studied in this regard. In our study, LA strain variables was independently associated with SBI but not with WMH4 (Figure 1), suggesting a different mechanism linking LA subclinical dysfunction to those conditions. An explanation might be cardiac microembolism, which may be more frequently at play for SBI, whereas small vessel disease may be more frequently the underlying mechanism for WMH (3). Alternatively, undetected episodes of paroxysmal atrial fibrillation may have contributed to our results. However, a state of “atrial cardiopathy” has been postulated, which might predispose to thromboembolism and stroke in the absence of documented atrial fibrillation (4). Therefore, its association with SBI might suggest that LA strain variables may be a marker of atrial cardiopathy. Importantly, the association was independent of LV GLS, another independent predictor of SBI (5).
FIGURE 1. Association of LA Strain and Strain Rate With Subclinical Cerebrovascular Disease.
LAε = Left atrial strain; LAεpos = global peak positive longitudinal LAε during ventricular systole; LASRpos = global peak positive longitudinal LA SR during ventricular systole; LASRearly-neg = global peak negative Longitudinal SR during early ventricular diastole; LASRlate-neg = global peak negative Longitudinal SR during LA contraction.
The addition of LA strain variables to the model including other independent predictors significantly improved the prediction of SBI, not of WMH4, suggesting its possible role as a potential novel biomarker for SBI presence and, therefore, related stroke risk. The hypothesis that LA strain may help identify individuals at high risk for stroke who need closer monitoring requires further investigation.
ACKNOWLEDGMENTS
The authors thank Janet De Rosa, MPH, Project Manager, and Rui Liu, MD, Clinical Research Coordinator, for their participation in the collection of the data.
This work was supported by grants from the National Institute of Neurological Disorders and Stroke (grant R01 NS36286 to Dr. Di Tullio and R37 NS29993 to Drs. Sacco and Elkind). All other authors have reported that they have no relationships relevant to the contents of this paper to disclose.
Footnotes
The authors attest they are in compliance with human studies committees and animal welfare regulations of the authors’ institutions and Food and Drug Administration guidelines, including patient consent where appropriate. For more information, visit the Author Center
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