Related Experiment Video
Updated: May 6, 2026

A Thrombotic Stroke Model Based On Transient Cerebral Hypoxia-ischemia
Published on: August 18, 2015
A predictive model for early neurological deterioration after intravenous thrombolysis in patients with ischemic
Liping He1,2, Meng Zhang1,2, Fei Xu2
1Department of School, Bengbu Medical University Graduate School, Bengbu, China.
Objective:
Intravenous thrombolysis (IVT) is the treatment of choice for acute ischemic stroke (AIS), but some patients develop early neurological deterioration (END) within 24 h after IVT. Therefore, we aimed to identify predictors of END in AIS patients following treatment with IVT.
Methods:
We retrospectively analyzed the clinical data of 621 AIS patients who received IVT with recombinant tissue-type plasminogen activator (rt-PA) at the Stroke Centre of the People's Hospital of Lu'an City, China, from July 2018 to July 2023. Clinical data, including demographic characteristics, clinical assessment results, underlying diseases, and laboratory indices, were collected at the time of admission. The patients were divided into training and validation cohorts, after which LASSO regression was applied to select the most important predictor variables, and multivariate logistic regression was used to construct a nomogram. The discriminative power of the model was determined by calculating the area under the curve (AUC), and calibration and decision curve analyses (DCA) were performed.
Results:
The platelet-to-lymphocyte ratio (PLR) (OR 1.01, 95% CI 1.01-1.01, p < 0.001), mean platelet corpuscular volume (MPV) (OR 2.12, 95% CI 1.67-2.69, p < 0.001), and admission NIHSS score (OR 1.25, 95% CI 1.16-1.36, p < 0.001) were significantly associated with the development of END. The AUC of the prediction model constructed from these three factors was 0.896 (95% CI 0.862-0.93), and the calibration curve was close to the diagonal.
Conclusion:
This predictive model can be used for the early identification of the risk of developing END after IVT and development of active interventions to improve the prognosis of AIS.

