AUTHOR=Ye Suzhen , Ding Ting , Gao Xin , Zhou Xuezhen , Xiu Meihong , Xia Yu 

TITLE=A nomogram model incorporating blood biomarkers predicts 3-week functional outcomes in stroke patients

JOURNAL=Frontiers in Neuroscience

VOLUME=Volume 19 - 2025

YEAR=2025

URL=https://www.frontiersin.org/journals/neuroscience/articles/10.3389/fnins.2025.1609156

DOI=10.3389/fnins.2025.1609156

ISSN=1662-453X

ABSTRACT=ObjectiveAccurate prediction of functional outcomes of stroke remains clinically challenging. The present study was designed to identify baseline biomarkers in demographic, clinical data, and blood biomarkers to predict 3-week outcomes in stroke patients.MethodsA prospective cohort of two hundred patients with stroke was recruited at the hospital and followed for 3 weeks. We applied the Barthel Index (BI) to measure the activities of daily living functions in stroke patients. The good outcome or poor outcome groups were classified based on the BI scores. A logistic regression analysis was performed to identify independent predictors, which were subsequently integrated into a nomogram. Discrimination and calibration values of the nomogram were analyzed, and its utility was assessed using decision curve analysis.ResultsFour blood biomarkers, including PT (OR = 1.45, 95% CI: 1.05–2.12), FIB (OR = 1.49, 95% CI: 1.14–2.00), RBG (OR = 1.20, 95% CI: 1.03–1.40), and UA (OR = 1.00, 95% CI: 0.99–1.00) were independent predictors of the 3-week functional outcomes after a stroke. The nomogram incorporating these biomarkers demonstrated moderate discriminative ability (AUC values = 0.714, 95%CI: 0.641–0.786), with satisfactory calibration and positive net benefit on DCA across clinically relevant threshold probabilities.ConclusionWe developed a pragmatic nomogram integrating readily available blood biomarkers to predict 3-week functional outcomes in stroke patients. While validation in larger cohorts is warranted, our findings provide new evidence in early risk stratification and personalized rehabilitation planning, potentially improving post-stroke care efficiency.