Shuhong Yu1, Yi Luo1, Tan Zhang1, Chenrong Huang1, Yu Fu1, Qiang Zhang1, Fangyue Zeng1, Hao Huang1, Chunyuan Zhang2, Zhiliang Guo3. 1. Department of Encephalopathy, Suzhou Hospital of Integrated Traditional Chinese and Western Medicine, Suzhou, 215101, China. 2. Department of Neurology and Suzhou Clinical Research Center of Neurological Disease, The Second Affiliated Hospital of Soochow University, No. 1055, Sanxiang Road, Suzhou, 215004, Jiangsu, China. zcyself@sina.com. 3. Department of Neurology and Suzhou Clinical Research Center of Neurological Disease, The Second Affiliated Hospital of Soochow University, No. 1055, Sanxiang Road, Suzhou, 215004, Jiangsu, China. guozhiliang3@163.com.
Abstract
BACKGROUND: It has been shown that eosinophils are decreased and monocytes are elevated in patients with acute ischemic stroke (AIS), but the impact of eosinophil-to-monocyte ratio (EMR) on clinical outcomes among AIS patients remains unclear. We aimed to determine the relationship between EMR on admission and 3-month poor functional outcome in AIS patients. METHODS: A total of 521 consecutive patients admitted to our hospital within 24 h after onset of AIS were prospectively enrolled and categorized in terms of quartiles of EMR on admission between August 2016 and September 2018. The endpoint was the poor outcome defined as modified Rankin Scale score of 3 to 6 at month 3 after admission. RESULTS: As EMR decreased, the risk of poor outcome increased (p < 0.001). Logistic regression analysis revealed that EMR was independently associated with poor outcome after adjusting potential confounders (odds ratio, 0.09; 95% CI 0.03-0.34; p = 0.0003), which is consistent with the result of EMR (quartile) as a categorical variable (odds ratio, 0.23; 95% CI 0.10-0.52; ptrend < 0.0001). A non-linear relationship was detected between EMR and poor outcome, whose point was 0.28. Subgroup analyses further confirmed these associations. The addition of EMR to conventional risk factors improved the predictive power for poor outcome (net reclassification improvement: 2.61%, p = 0.382; integrated discrimination improvement: 2.41%, p < 0.001). CONCLUSIONS: EMR on admission was independently correlated with poor outcome in AIS patients, suggesting that EMR may be a potential prognostic biomarker for AIS.
BACKGROUND: It has been shown that eosinophils are decreased and monocytes are elevated in patients with acute ischemic stroke (AIS), but the impact of eosinophil-to-monocyte ratio (EMR) on clinical outcomes among AIS patients remains unclear. We aimed to determine the relationship between EMR on admission and 3-month poor functional outcome in AIS patients. METHODS: A total of 521 consecutive patients admitted to our hospital within 24 h after onset of AIS were prospectively enrolled and categorized in terms of quartiles of EMR on admission between August 2016 and September 2018. The endpoint was the poor outcome defined as modified Rankin Scale score of 3 to 6 at month 3 after admission. RESULTS: As EMR decreased, the risk of poor outcome increased (p < 0.001). Logistic regression analysis revealed that EMR was independently associated with poor outcome after adjusting potential confounders (odds ratio, 0.09; 95% CI 0.03-0.34; p = 0.0003), which is consistent with the result of EMR (quartile) as a categorical variable (odds ratio, 0.23; 95% CI 0.10-0.52; ptrend < 0.0001). A non-linear relationship was detected between EMR and poor outcome, whose point was 0.28. Subgroup analyses further confirmed these associations. The addition of EMR to conventional risk factors improved the predictive power for poor outcome (net reclassification improvement: 2.61%, p = 0.382; integrated discrimination improvement: 2.41%, p < 0.001). CONCLUSIONS: EMR on admission was independently correlated with poor outcome in AIS patients, suggesting that EMR may be a potential prognostic biomarker for AIS.
Entities:
Keywords:
Biomarker; Eosinophil-to-monocyte ratio (EMR); Ischemic stroke; Outcome
Authors: Ana Carolina Alba; Thomas Agoritsas; Michael Walsh; Steven Hanna; Alfonso Iorio; P J Devereaux; Thomas McGinn; Gordon Guyatt Journal: JAMA Date: 2017-10-10 Impact factor: 56.272
Authors: Alexander M Kollikowski; Michael K Schuhmann; Bernhard Nieswandt; Wolfgang Müllges; Guido Stoll; Mirko Pham Journal: Ann Neurol Date: 2020-01-16 Impact factor: 10.422