Left Atrial Strain Helps Predict Atrial Fibrillation in Heart Failure Patients

A new study from the Wroclaw Medical University in Poland suggests measurements of peak atrial longitudinal strain (PALS) and peak atrial contraction strain (PACS) can help predict what heart failure patients were at the greatest risk of developing atrial fibrillation (AF).

An analysis of 170 patients with heart failure with preserved ejection fraction (HFpEF) with a median follow-up of more than 4 years, results indicate measurements of PACS and PALS provided predictive information and led investigators to suggest including these components to improve screening and assessments of risk for AF.

“PACS and PALS have predictive value for incident AF in HFpEF, incremental to established clinical and echocardiographic prognosticators. The combination of atrial remodeling characteristics may offer a sensitive tool to guide screening for AF risk in this population,” wrote investigators.

In an effort to identify predictive factors associated with incident AF in patients with HFpEF, investigators designed a prospective cohort analysis of patients with symptomatic HFpEF who were free from AF at baseline. Patients included in the study were admitted to the University Hospital in Wroclaw, Poland from 2011-2014.

Patients were excluded from the study if they had a left ventricular ejection fraction less than 50%, heart rhythm other than stable sinus rhythm, ischemic heart disease, moderate and severe valvular heart disease, or failed to meet parameters related to hemoglobin levels and eGFR. All patients included in the study underwent clinical evaluation, cardiopulmonary exercise testing, echocardiography, and blood sampling for laboratory analysis.

In total, 170 patients were identified for inclusion in the current study. The mean age of the cohort was 65±8 years, the median follow-up time was 49 months, and 39 (23%) patients developed incident AF during the follow-up period. Of the 39 with AF, 14 were diagnosed through portable ECG monitoring and 25 were diagnosed by a physician or were diagnosed during a hospital stay.

In comparison to those without AF, those who developed AF were older and had higher CHA1DS2-VASc risk scores, BNP, creatinine, left atrial volume index (LAVI), and left ventricular mass. These patients also had lower left atrial strain and exercise capacity and greater impairment of diastolic function. Further analysis revealed PACS (area under receiver-operating characteristic curve: 0.76), PALS (AUC: 0.71), and LAVI (AUC: 0.72).

In Nested Cox regression models, results indicated predictive value of PACS and PALS was independent from and incremental to clinical data, LAVI, and E/e’ ratio. In classification and regression trees (CART) analysis, results indicated PACS of 12.7% or less, PALS of 29.4% or less, and LAVI greater than 34.3 ml/m2 as discriminatory nodes for AF—among patients considered high risk, there was a 33-fold greater risk of developing AF (P <.001).

Investigators noted a validation cohort of 103 patients with HFpEF was created using data from the KaRen study and the CART algorithm discriminated high and low AF risk in this cohort. All patients in the validation cohort met the same inclusion criteria as the 170 patient cohort.

In an editorial comment, John Gorcsan III, MD, of Washington University, commends the investigators of the current study and also highlights the importance of their work, noting the ability to more accurately predict patients at greater risk of AF would be useful and could help prevent adverse outcomes.

“AF in patients with HFpEF is a common clinical problem that is likely to increase in the future. Accumulation of new information, such as LA strain data, to determine patients who are at high risk for AF is an important advance,” wrote Gorcsan. “When combined with clinical, biomarker, and other imaging data, LA speckle tracking strain ability to forecast future AF has great promise to improve medical diagnostics and therapeutics.”

This study, “Prediction of AF in Heart Failure With Preserved Ejection Fraction,” was published in JACC Imaging.