Optimal time point for neutrophil-to-lymphocyte ratio to predict stroke-associated pneumonia

Neurol Sci. 2023 Jul;44(7):2431-2442. doi: 10.1007/s10072-023-06654-7. Epub 2023 Feb 20.

Abstract

Purpose: This study aimed at the population receiving thrombolytic therapy and to explore the optimal time point for neutrophil-to-lymphocyte ratio (NLR) in predicting stroke-associated pneumonia (SAP).

Methods: We assessed patients undergoing intravenous thrombolysis (IVT) for acute ischemic stroke. Blood parameters were sampled before thrombolysis (within 30 min after admission) and within 24-36 h after thrombolysis, respectively. The primary outcome measure was the occurrence of SAP. Multivariate logistic regression analysis was performed to analyze the association between admission blood parameters and the event of SAP. We also used receiver operating characteristic (ROC) curve analysis to assess the discriminative ability of blood parameters measured at different times in predicting SAP.

Results: Among the 388 patients, SAP occurred in 60 (15%) patients. Multivariate logistic regression analysis showed that NLR was significantly associated with SAP (NLR before IVT: aOR = 1.288; 95%CI = 1.123-1.476; p < 0.001; NLR after IVT: (aOR = 1.127, 95%CI = 1.017-1.249; p = 0.023). The ROC curve showed that the predictive ability of NLR after IVT was better than NLR before IVT, not only in predicting the occurrence of SAP but also in predicting short-term and long-term functional outcomes, hemorrhagic transformation, and 1-year mortality.

Conclusion: Increased NLR measured within 24-36 h after IVT has a significant predictive effect on the occurrence of SAP and can be used to predict short-term and long-term poor functional outcomes, hemorrhagic transformation, and 1-year mortality.

Keywords: Lymphocyte; Neutrophil; Pneumonia; Prognosis; Stroke; Thrombolysis.

MeSH terms

  • Humans
  • Ischemic Stroke*
  • Lymphocytes
  • Neutrophils
  • Pneumonia*
  • Retrospective Studies
  • Stroke* / complications
  • Stroke* / drug therapy