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

OBJECTIVE

Accurate 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.

METHODS

A 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.

RESULTS

Four 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.

CONCLUSION

We 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.