The lactate-to-albumin ratio as a novel predictor for post-stroke epilepsy: insights from a large cohort

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ID: 332496
2026
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Abstract
Abstract Ischemic stroke (IS) represents a leading cause of adult mortality and long-term disability globally, and post-stroke epilepsy (PSE) constitutes a severe complication that worsens neurological recovery and reduces quality of life, yet reliable early predictive biomarkers remain insufficient. The serum lactate-to-albumin ratio (LAR, mmol/g), an integrated indicator reflecting hypoxic-ischemic stress, energy metabolic disturbance, and systemic inflammation, has emerged as a promising prognostic marker but has not been investigated for predicting PSE risk. This multicenter retrospective cohort study enrolled 21,459 acute IS patients from four centers to examine the association between admission LAR and one-year PSE incidence. Multivariable logistic regression, restricted cubic spline (RCS) analysis, subgroup stratification, and sensitivity testing were applied for statistical evaluation. Overall, 936 patients (4.36%) developed PSE within one year. In the fully adjusted model, each 1-unit increment in LAR was associated with an odds ratio (OR) of 1.13 (95% CI: 1.04–1.22, p=0.003) for PSE. Compared with the lowest LAR quartile (Q1), the highest quartile (Q4) conferred a markedly elevated risk (OR=12.02, 95% CI: 7.91–18.90, p<0.001), with a significant nonlinear dose-response relationship and an inflection point at LAR=0.06. The association was stronger in patients with atrial fibrillation or cortical stroke lesions, and sensitivity analyses confirmed result robustness. Taken together, these data indicate that serum LAR measured at admission behaves as an independent, non-linear correlate of PSE risk after acute IS. As a readily available biomarker derived from routine serum laboratory tests, LAR may serve as a promising candidate for early risk stratification in IS patients, although prospective studies are warranted to confirm its clinical utility.
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Authors Dandan Chen, Yuanlin Liu, Yingru Zhou, Qi Yang, Xiao Wu, Yunliang Tang
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Journal Brain communications
Year 2026
DOI
10.1093/braincomms/fcag391
URL
https://doi.org/10.1093/braincomms/fcag391
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