LIU Yiran, LI Yingnan, SUN Yan, ZHANG Li. Value of serological indicators in predicting early neurological deterioration in patients with acute ischemic stroke[J]. Journal of Clinical Medicine in Practice, 2024, 28(13): 63-66, 71. DOI: 10.7619/jcmp.20241162
Citation: LIU Yiran, LI Yingnan, SUN Yan, ZHANG Li. Value of serological indicators in predicting early neurological deterioration in patients with acute ischemic stroke[J]. Journal of Clinical Medicine in Practice, 2024, 28(13): 63-66, 71. DOI: 10.7619/jcmp.20241162

Value of serological indicators in predicting early neurological deterioration in patients with acute ischemic stroke

More Information
  • Received Date: March 18, 2024
  • Revised Date: May 08, 2024
  • Available Online: July 19, 2024
  • Objective 

    To explore the value of serological indicators in predicting early neurological deterioration (END) in patients with acute ischemic stroke (AIS).

    Methods 

    A total of 276 AIS patients were selected as the study subjects and divided into END group (72 cases) and non-END group (204 cases) based on the occurrence of END. Clinical data from all AIS patients were collected. Multivariable Logistic regression analysis was used to analyze the independent influencing factors of END in AIS patients. The receiver operating characteristic (ROC) curve was used to evaluate the predictive value of various serological markers for END.

    Results 

    Univariate analysis showed that the END group had a significantly higher proportion of patients aged >75 years, higher National Institutes of Health Stroke Scale (NIHSS) scores, fasting blood glucose (FBG), uric acid, fibrinogen, platelet-to-lymphocyte ratio (PLR) and neutrophil-to-lymphocyte ratio (NLR) compared to the non-END group (P < 0.05). Multivariable Logistic regression analysis revealed that age (OR=1.322, 95%CI, 1.049 to 1.666), NIHSS score (OR=1.793, 95%CI, 1.281 to 2.510), FBG (OR=1.392, 95%CI, 1.126 to 1.722), PLR (OR=1.505, 95%CI, 1.128 to 2.008) and NLR (OR=1.677, 95%CI, 1.280 to 2.197) were independent influencing factors for END in AIS patients. The ROC curve showed that the areas under the curve (AUC) for FBG, PLR and NLR in predicting END in AIS patients were 0.642, 0.581 and 0.759, respectively.

    Conclusion 

    PLR, NLR and FBG are independent influencing factors for the occurrence of END in AIS patients. NLR has a higher predictive value for END in AIS patients.

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