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    Assessing the predictive value of neutrophil percentage to albumin ratio for ICU admission in ischemic stroke patients

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    fneur-15-1322971.pdf (660.7Kb)
    Date
    2024
    Author
    Zawiah, Mohammed
    Khan, Amer Hayat
    Farha, Rana Abu
    Usman, Abubakar
    Al-Ashwal, Fahmi Y.
    Akkaif, Mohammed Ahme
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    Abstract
    Background: Acute ischemic stroke (AIS) remains a substantial global health challenge, contributing to increased morbidity, disability, and mortality. This study aimed at investigating the predictive value of the neutrophil percentage to albumin ratio (NPAR) in determining intensive care unit (ICU) admission among AIS patients. Methods: A retrospective observational study was conducted, involving AIS cases admitted to a tertiary hospital in Jordan between 2015 and 2020. Lab data were collected upon admission, and the primary outcome was ICU admission during hospitalization. Descriptive and inferential analyses were performed using SPSS version 29. Results: In this study involving 364 AIS patients, a subset of 77 (21.2%) required admission to the ICU during their hospital stay, most frequently within the first week of admission. Univariable analysis revealed significantly higher NPAR levels in ICU-admitted ischemic stroke patients compared to those who were not admitted (23.3 vs. 15.7, p < 0.001), and multivariable regression models confirmed that higher NPAR (≥19.107) independently predicted ICU admission in ischemic stroke patients (adjusted odds ratio [aOR] = 4.85, 95% CI: 1.83–12.83). Additionally, lower GCS scores and higher neutrophil-to-lymphocyte ratio (NLR) were also associated with increased likelihood of ICU admission. In terms of predictive performance, NPAR showed the highest accuracy with an AUC of 0.885, sensitivity of 0.805, and specificity of 0.854, using a cutoff value of 19.107. NPAR exhibits an AUC of 0.058, significantly outperforming NLR (Z = 2.782, p = 0.005). Conclusion: NPAR emerged as a robust independent predictor of ICU admission in ischemic stroke patients, surpassing the predictive performance of the NLR.
    DOI/handle
    http://dx.doi.org/10.3389/fneur.2024.1322971
    http://hdl.handle.net/10576/54206
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