Inflammation and immune response are the key parts in pathophysiological processes of cerebral ischemia.CD4+ T cells play an important role in it.This article reviews the roles and mechanisms of each subtype of CD4+ T cells in cerebral ischemia in order to provide the basis for the treatment of cerebral ischemia with CD4 + T cells as targets.

Objective:To explore independent predictors for poor outcome at 3 months in elderly patients with acute cerebral infarction(ACI)treated with intravenous thrombolysis(IVT), and to develop a nomogram-based predictive model.Methods:This was a retrospective cohort study.Clinical, laboratory and imaging data of 346 elderly patients with ACI treated with IVT from January 2016 to April 2021 in our hospital were collected.Poor outcome was defined as a modified Rankin Scale(mRS)score >2 at 3 months after the stroke.Logistic regression analysis was used to screen for independent factors predicting poor outcome in elderly ACI patients treated with IVT, and a corresponding nomogram model was developed using the R software.The ROC curve, calibration plots and decision curve analysis were used to evaluate discrimination, calibration and clinical application value of the nomogram model.Results:Among 346 candidates, 109 developed a poor outcome, representing a rate of 31.5%.Logistic regression analysis showed that symptomatic hemorrhagic transformation( OR=15.647, 95% CI: 8.913-27.454), stroke severity(moderate stroke, OR=3.322, 95% CI: 1.414-7.811; moderate-severe stroke, OR=8.169, 95% CI: 4.102-16.258; severe stroke, OR=9.653, 95% CI: 5.440-17.121), stroke-associated pneumonia( OR=2.239, 95% CI: 1.134-4.420), and heart failure( OR=2.758, 95% CI: 1.424-5.336)were independent predictors for poor outcome at 3 months in elderly ACI patients treated with intravenous thrombolysis(all P<0.05). With the area under curve(AUC-ROC)value at 0.85(95% CI: 0.80-0.89), the nomogram model, which was composed of the above four predictors, demonstrated good discrimination.On the calibration plot, the mean absolute error was 0.020, indicating that the model had good calibration.Decision curve analysis revealed that the model had good clinical application value. Conclusions:The nomogram model composed of symptomatic hemorrhagic transformation, stroke severity, stroke-associated pneumonia and heart failure may predict poor outcome at 3 months in elderly ACI patients treated with IVT, with high prediction accuracy and high clinical application value.