Clinical contribution of lipid profiles to the stroke progression in Chinese population: a single-centered cohort study

Background: Clinical performance and contribution of lipid profile in atherosclerosis is well established but require further investigation in stroke patients. Objectives: To explore lipid parameters and their impact on stroke outcomes in patients with and without thrombolysis. Methods: We prospectively enrolled acute ischemic stroke (AIS) patients, both with and without thrombolysis in our single center, and divided them into improvement (good outcome at 2 weeks) and non-improvement groups. Comparisons of demographic, laboratory, imaging, and clinical scaling data were conducted between the two groups. The performance and importance of each lipid (triglyceride, total cholesterol, high-density lipoprotein (HDL), low-density lipoprotein (LDL), apolipoprotein B100 (ApoB100), and lipoprotein a) were assessed using logistic regression and random forest models. Results: A total of 262 stroke patients were enrolled, with 165 receiving thrombolysis. It was found that ApoB100 levels were lower in patients who received thrombolysis (p < 0.001), and there were no significant differences in lipids between the improvement and non-improvement groups. The random forest model generated barplots showing the importance of lipids and risk factors in patients with AIS, indicating that HDL and ApoB100 from lipids (both over 15%) were more important for predicting favorable stroke outcomes. Conclusions: This study demonstrates that HDL and ApoB100 are key predictors of favorable stroke outcomes, as evaluated using a machine learning model. These findings highlight the potential value of incorporating HDL and ApoB100 into clinical risk assessment tools for stroke patients, warranting further investigation in larger, diverse cohorts. Trial registration : ChiCTR1800018315, 11/09/2018