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Cited by 11Acute Ischemic Stroke ManagementInflammatory Biomarkers in Disease PrognosisNeuroinflammation and Neurodegeneration Mechanisms

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Applicability of the low-grade inflammation score in predicting 90-day functional outcomes after acute ischemic stroke

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Zhou, Yang, Luo, Yufan, Liang, Huazheng, Zhong, Ping, Wu, Danhong·2023·BMC Neurology
DOI 10.1186/s12883-023-03365-6PMC PMC10483771

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Abstract

Background and purpose: The low-grade inflammation (LGI) score, a novel indicator of chronic LGI, combines C-reactive protein (CRP), leukocyte counts, the neutrophil/lymphocyte ratio (NLR), and the platelet (PLT) count to predict outcomes of patients with various conditions, such as cardiovascular diseases, cancers, and neurodegenerative diseases. However, few studies have examined the role of the LGI score in predicting functional outcomes of patients with ischemic stroke. The present study aimed to evaluate the association between the LGI score and functional outcomes of patients with ischemic stroke. Methods: A total of 1,215 patients were screened in the present study, and 876 patients were finally included in this retrospective observational study based on the inclusion and exclusion criteria. Blood tests were conducted within 24 h of admission. Severity of ischemic stroke was assessed using the NIHSS score with severe stroke denoted by NIHSS > 5. Early neurological deterioration (END) was defined as an increment in the total NIHSS score of ≥ 2 points within 7 days after admission. Patient outcomes were assessed on day 90 after stroke onset using the modified Rankin Scale (mRS). Results: The LGI score was positively correlated with baseline and the day 7 NIHSS scores (R2 = 0.119, p < 0.001;R2 = 0.123, p < 0.001). Multivariate regression analysis showed that the LGI score was an independent predictor of stroke severity and END. In the crude model, the LGI score in the fourth quartile was associated with a higher risk of poor outcomes on day 90 compared with the LGI score in the first quartile (OR = 5.02, 95% CI: 3.09–8.14, p for trend < 0.001). After adjusting for potential confounders, the LGI score in the fourth quartile was independently associated with poor outcomes on day 90 (OR = 2.65, 95% CI: 1.47–4.76, p for trend = 0.001). Finally, the ROC curve analysis showed an AUC of 0.682 for poor outcomes on day 90 after stroke onset. Conclusion: The LGI score is strongly correlated with the severity of acute ischemic stroke and that the LGI score might be a good predictor for poor outcomes on day 90 in patients with acute ischemic stroke.

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Figures

Fig. 1 The association between the LGI score and the NIHSS score. A Patients with a baseline NIHSS score > 5 had a significant increase in the LGI score compared to those with an NIHSS ≤ 5 (p < 0.001). B Patients with a one-week NIHSS score > 5 had a significant increase in the LGI score compared to those with an NIHSS ≤ 5 (p < 0.001). C The LGI score was positively correlated with the baseline (R = 0.2580, p < 0.001) and one-week NIHSS scores (R = 0.2578, p < 0.001)
Fig. 1 The association between the LGI score and the NIHSS score. A Patients with a baseline NIHSS score > 5 had a significant increase in the LGI score compared to those with an NIHSS ≤ 5 (p < 0.001). B Patients with a one-week NIHSS score > 5 had a significant increase in the LGI score compared to those with an NIHSS ≤ 5 (p < 0.001). C The LGI score was positively correlated with the baseline (R = 0.2580, p < 0.001) and one-week NIHSS scores (R = 0.2578, p < 0.001)CC BY · PubMed Central
Fig. 2 Efficacy of predicting 90-day poor outcomes using the LGI score and the conventional model
Fig. 2 Efficacy of predicting 90-day poor outcomes using the LGI score and the conventional modelCC BY · PubMed Central

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Metadata

Authors
Zhou, Y., Luo, Y., Liang, H., Zhong, P., & Wu, D.
Affiliations
  • Shaoxing People's Hospital (CN)
  • Shanghai Medical College of Fudan University (CN)
  • Suzhou Research Institute (CN)
Corresponding author
  • Zhong, Ping
  • Wu, Danhong
ORCID
Venue
BMC Neurology
Publisher
Springer Science and Business Media LLC
Published
2023-09-07
Volume
23
Issue
1
Pages
320-320
ISSN
1471-2377 (ISSN-L)
DOI
10.1186/s12883-023-03365-6
PMC
PMC10483771
OpenAlex
W4386516074
Cited by
11
References
1
Citations by year
2026: 7 · 2025: 3 · 2024: 1
FWCI
2.20
Type
journal article
Language
en
Open access
Licence
Locations
  • BMC Neurology (publishedVersion, cc-by)
  • Research Square (acceptedVersion, cc-by)
  • PubMed Central (publishedVersion, cc-by)
  • PubMed (publishedVersion)
  • Monash University Research Portal (Monash University) (submittedVersion, cc-by)
  • DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
Funders
  • Zhejiang Medical Science and Technology Project (2023RC287)
  • Shaoxing Basic Public Welfare Program (2022A14018)
  • Shanghai Committee of Science and Technology (20S31904400)
  • Beijing Health Alliance Charitable Foundation (B21088CS)
  • Cooperation Programme of Fudan University – Minhang District Joint Health Center (2021FM22)
  • Shanghai Minhang District Health and Family Planning Commission (2020MWDXK01)
Topics
  • Health Sciences › Medicine › Clinical Neurology › Acute Ischemic Stroke Management
  • Health Sciences › Medicine › Oncology › Inflammatory Biomarkers in Disease Prognosis
  • Life Sciences › Neuroscience › Neurology › Neuroinflammation and Neurodegeneration Mechanisms
Keywords
acute ischemic stroke, functional outcome, C-reactive protein, neutrophil-to-lymphocyte ratio, platelet count, stroke severity, early neurological deterioration, modified Rankin Scale, prognostic factors, inflammatory markers, NIHSS score
MeSH terms
Ischemic Stroke, C-Reactive Protein, Cardiovascular Diseases, Humans, Inflammation, Stroke

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