Background: Atrial myopathy—characterized by changes in left atrial function and size—may precede and promote atrial fibrillation (AF) and cardiac thromboembolism. In people without prior AF or stroke, whether analysis of left atrial function and size can improve ischemic stroke prediction is unknown. Objective: To evaluate the association of echocardiographic left atrial function (reservoir, conduit, and contractile strain) and left atrial size (left atrial volume index) with ischemic stroke and determine whether these measures can improve the stroke prediction achieved by CHA2DS2-VASc score variables. Design: Prospective cohort study. Setting: ARIC (Atherosclerosis Risk in Communities) study. Participants: 4917 ARIC participants without prevalent stroke or AF. Measurements: Ischemic stroke events (2011 to 2019) were adjudicated by physicians. Left atrial strain was measured using speckle-tracking echocardiography. Results: Over 5 years, the cumulative incidences of ischemic stroke in the lowest quintiles of left atrial reservoir, conduit, and contractile strain were 2.99% (95% CI, 1.89% to 4.09%), 3.18% (CI, 2.14% to 4.22%), and 2.15% (CI, 1.09% to 3.21%), respectively, and that of severe left atrial enlargement was 1.99% (CI, 0.23% to 3.75%). On the basis of the Akaike information criterion, left atrial reservoir strain plus CHA2DS2VASc variables was the best predictive model. With the addition of left atrial reservoir strain to CHA2DS2-VASc variables, 11.6% of the 112 participants with stroke after 5 years were reclassified to higher risk categories and 1.8% to lower risk categories. Among the 4805 participants who did not develop stroke, 12.2% were reclassified to lower and 12.7% to higher risk categories. Decision curve analysis showed a predicted net benefit of 1.34 per 1000 people at a 5-year risk threshold of 5%. Limitation: Underascertainment of subclinical AF. Conclusion: In people without prior AF or stroke, when added to CHA2DS2-VASc variables, left atrial reservoir strain improves stroke prediction and yields a predicted net benefit, as shown by decision curve analysis.
|Original language||English (US)|
|Number of pages||10|
|Journal||Annals of internal medicine|
|State||Published - Jan 1 2023|
Bibliographical noteFunding Information:
Grant Support: The ARIC study has been funded in whole or in part with federal funds from the National Heart, Lung, and Blood Institute, National Institutes of Health, Department of Health and Human Services, under contracts HHSN268201700001I, HHSN268201700002I, HHSN268201700003I, HHSN268201700004I, and HHSN268201700005I. This study was funded by R01 HL141288. Dr. Chen is supported by R01HL126637, R01 HL141288, RF1 NS127266, R01 HL158022, and K24HL155813.
© 2022 American College of Physicians.
PubMed: MeSH publication types
- Journal Article
- Research Support, N.I.H., Extramural