The role of the QT interval in predicting functional prognosis in patients with acute ischemic stroke

The QT interval predicts stroke occurrence, yet its impact on functional outcomes in acute ischemic stroke (AIS) remains unclear. The optimal QT interval correction formula (QTc) for prognostic prediction in AIS patients also requires further investigation.

We aimed to investigate the association between the heart rate-corrected QT interval and the 3-month functional prognosis in patients with AIS, and to identify the most suitable QTc formula for this population.

In this retrospective cohort study, we enrolled 1133 non-thrombolytic adult AIS patients admitted within 72 h of symptom onset. The association between baseline QT interval (corrected using multiple formulas: Bazett-QTcB, Fridericia-QTcF, Linear-QTa, Framingham-QTcFra, Hodges-QTcH) and an adverse 3-month functional outcome (defined as modified Rankin Scale score mRS ≥ 2) was analyzed using multivariate logistic regression. The population was randomly split into training and testing sets (7:3 ratio). A nomogram incorporating QTcB and clinical predictors was developed and validated to assess its predictive performance and clinical utility.

Multivariable logistic regression analysis of 1133 AIS patients revealed that a longer QT interval corrected by the Bazett formula (QTcB) was significantly associated with adverse 3-month functional outcome (mRS 2-6) after adjustment for age and sex (Model 1: OR per 1 SD: 1.23, 95% CI: 1.09-1.40, p = 0.001). This association remained significant after comprehensive adjustment for clinical covariates (Model 2: OR per 1 SD: 1.16, 95% CI: 1.01-1.33, p = 0.040). The nomogram incorporating QTcB demonstrated good predictive performance with an AUC and provided positive net benefit on decision curve analysis.

A prolonged QTcB at admission is independently associated with an adverse 3-month functional outcome in AIS patients. The Bazett correction formula (QTcB) is a more suitable and effective tool for functional prognosis prediction in this cohort compared to other commonly used formulas.