Left atrial strain parameters for predicting new-onset atrial fibrillation: a systematic review and meta-analysis

Early identification of new-onset atrial fibrillation (NOAF) is crucial for preventing related complications. Left atrial strain parameters (LASPs), evaluated by speckle tracking echocardiography, are considered promising markers reflecting atrial cardiomyopathy and functional abnormalities. Therefore, this study aimed to quantitatively evaluate the predictive value of LASPs for NOAF through a systematic review and meta-analysis.

The Cochrane Library, Embase, PubMed, and Web of Science were retrieved up to July 30, 2025, for cohort, case-control, and cross-sectional investigations evaluating the correlation of peak atrial longitudinal strain (PALS), left atrial reservoir strain (LASr), left atrial conduit strain (LAScd), left atrial systolic strain (LASct), and peak atrial contraction strain (PACS) with the risk of NOAF. Random-effects models were employed to pool risk ratios (RR) and diagnostic performance metrics. Sensitivity analyses and Egger's test were applied to verify the stability of prognostic outcomes and publication bias, respectively. Subgroup and meta-regression analyses were conducted for multiple confounders. A summary receiver operating characteristic (SROC) curve was plotted, and the area under the curve (AUC) was computed.

Thirty-nine studies involving 20,681 subjects were incorporated. Meta-analyses revealed that low levels of PALS [RR (95% CI): 3.95 (1.57-9.92)], LASr [3.73 (2.34-5.96)], LAScd [2.26 (1.22-4.19)], and LASct [6.54 (2.25-19.0)] as dichotomous variables were associated with a higher risk of NOAF. As continuous variables, a one-unit decrease in PALS, PACS, LASr, LAScd, and LASct was independently associated with an elevated risk of NOAF (all P < 0.05). SROC analysis indicated that the pooled AUCs for PALS, LASr, and LASct were 0.84, 0.84, and 0.78, respectively, suggesting good diagnostic performance for these parameters.

LASPs exhibit significant diagnostic value for NOAF. They can be utilized in clinical practice to evaluate and predict the risk of NOAF.

https://www.crd.york.ac.uk/PROSPERO/view/CRD420251044556.