Abstract

Early neurological deterioration is a common complication of acute ischemic stroke (AIS), which aggravates symptoms, worsens the condition, and counteracts the benefits of clinical treatment. The aim of this paper was to analyze the correlation between lipoprotein-associated phospholipase A2 (Lp-PLA2), matrix metalloproteinase-9 (MMP-9), and the occurrence of early neurological deterioration (END) in patients with AIS and to explore the clinical prediction of END by the combination of the 2 assays for the clinical prediction of END. A total of 500 AIS patients admitted to our hospital from October 2022 to October 2023 were included as study subjects, and the clinical data of all AIS patients were collected and organized to detect the levels of Lp-PLA2 and MMP-9. Categorized into END and non-END groups according to whether END occurred within 7 days of the onset of AIS, and comparing the clinical baseline data and laboratory index levels of the 2 groups. Logistic regression analysis was performed to determine the independent predictors of END, and the predictive effects of Lp-PLA2 and MMP-9 levels on END were assessed by subject work characteristics (ROC) curves. END occurred in 111 (22.2%) of 500 AIS patients. Multivariate logistic regression analysis showed that diabetes (OR 2.717, 95% CI:1.53-4.81, P < .001), baseline NIHSS score (OR 1.65, 95% CI:1.41-1.94, P < .001), Lp-PLA2 (OR 1.07, 95% CI:1.05-1.09, P < .001) and MMP-9 (OR 1.12, 95% CI:1.09-1.16, P < .001) levels were independent influences on the occurrence of END in patients with AIS after correcting for confounders. ROC curve analysis showed that Lp-PLA2, MMP-9, and a combination of both predicted END with an area under the curve was 0.730, 0.763, and 0.831, respectively, and the area under the curve for the combination of both predicting END was significantly higher than that for any of the inflammatory markers alone (P < .05). Both inflammatory markers, Lp-PLA2 and MMP-9, were independent predictors of the development of END in patients with AIS, and the combination of the two had a higher predictive value.

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