scholarly journals The Antioxidant Enzyme PON1: A Potential Prognostic Predictor of Acute Ischemic Stroke

2021 ◽  
Vol 2021 ◽  
pp. 1-8
Author(s):  
Yuzhen Xu ◽  
Kai Wang ◽  
Qian Wang ◽  
Yihong Ma ◽  
Xueyuan Liu
Keyword(s):  
Logistic Regression ◽  
Ischemic Stroke ◽  
Acute Ischemic Stroke ◽  
Functional Outcome ◽  
Antioxidant Enzyme ◽  
Laboratory Data ◽  
Activity Level ◽  
Pon1 Activity ◽  
Poor Outcomes ◽  
Serum Pon1 Activity

Objective. Paraoxonase 1 (PON1) is an antioxidant enzyme, which has been proved to be involved in the pathophysiological process of oxidative stress and various neurological diseases in recent years. Although reduced PON1 activity has been reported in patients with acute ischemic stroke (AIS), the prognostic value of PON1 in AIS has not been clearly established. The purpose of this study was to determine whether the baseline serum PON1 activity level is related to the functional outcome of AIS patients. Methods. From July 2017 to June 2020, AIS patients within 3 days of symptom onset were continuously prospectively included in the study. On admission, clinical and laboratory data were recorded, and serum PON1 activity was tested. The National Institute of Health Stroke Scale (NIHSS) score was used to evaluate the initial neurologic deficit at admission, and the modified Rankin scale (mRS) was used to evaluate the functional outcome at 3 months. A multiple logistic regression model was used to analyze the relationship between the baseline PON1 activity level and the prognosis of AIS. Results. A total of 336 AIS patients were finally included in this study. The serum PON1 activity of AIS patients with good outcomes was significantly higher than that of patients with poor outcomes ( 193.4 ± 16.3   U / mL vs. 127.2 ± 14.9   U / mL , p < 0.001 ). However, the comparison of other clinical and laboratory data between AIS patients with good and poor outcomes was not significant ( p > 0.05 ). There was a significant decrease in the mRS score in patients with AIS across serum PON1 quartiles ( 3.0 ± 1.6 , 2.6 ± 1.5 , 2.4 ± 1.4 , and 2.4 ± 1.3 , p = 0.007 ). Multivariate logistic regression analysis showed that the 3-month functional outcome of AIS patients was significantly correlated with the quartile of serum PON1 activity. Conclusions. This study suggests that the serum PON1 activity may be an independent predictor of the functional outcome of AIS patients.

scholarly journals Machine Learning-Based Three-Month Outcome Prediction in Acute Ischemic Stroke: A Single Cerebrovascular-Specialty Hospital Study in South Korea

Diagnostics ◽  
2021 ◽  
Vol 11 (10) ◽  
pp. 1909
Author(s):  
Dougho Park ◽  
Eunhwan Jeong ◽  
Haejong Kim ◽  
Hae Wook Pyun ◽  
Haemin Kim ◽  
...  
Keyword(s):  
Machine Learning ◽  
Logistic Regression ◽  
Ischemic Stroke ◽  
Acute Ischemic Stroke ◽  
Functional Outcome ◽  
Outcome Prediction ◽  
Prediction Models ◽  
Gradient Boosting ◽  
Support Vector ◽  
Extreme Gradient Boosting

Background: Functional outcomes after acute ischemic stroke are of great concern to patients and their families, as well as physicians and surgeons who make the clinical decisions. We developed machine learning (ML)-based functional outcome prediction models in acute ischemic stroke. Methods: This retrospective study used a prospective cohort database. A total of 1066 patients with acute ischemic stroke between January 2019 and March 2021 were included. Variables such as demographic factors, stroke-related factors, laboratory findings, and comorbidities were utilized at the time of admission. Five ML algorithms were applied to predict a favorable functional outcome (modified Rankin Scale 0 or 1) at 3 months after stroke onset. Results: Regularized logistic regression showed the best performance with an area under the receiver operating characteristic curve (AUC) of 0.86. Support vector machines represented the second-highest AUC of 0.85 with the highest F1-score of 0.86, and finally, all ML models applied achieved an AUC > 0.8. The National Institute of Health Stroke Scale at admission and age were consistently the top two important variables for generalized logistic regression, random forest, and extreme gradient boosting models. Conclusions: ML-based functional outcome prediction models for acute ischemic stroke were validated and proven to be readily applicable and useful.

Serum Vitamin D Status as a Predictor of Prognosis in Patients with Acute Ischemic Stroke

2015 ◽  
Vol 40 (1-2) ◽  
pp. 73-80 ◽  
Author(s):  
Kwang-Yeol Park ◽  
Pil-Wook Chung ◽  
Yong Bum Kim ◽  
Heui-Soo Moon ◽  
Bum-Chun Suh ◽  
...  
Keyword(s):  
Vitamin D ◽  
Logistic Regression ◽  
Ischemic Stroke ◽  
Acute Ischemic Stroke ◽  
Functional Outcome ◽  
Multivariable Analysis ◽  
Stroke Severity ◽  
Baseline Serum ◽  
Nihss Score ◽  
Good Functional Outcome

Background: Low 25-hydroxyvitamin D (25(OH)D) concentrations have been shown to predict risk of cardiovascular disease and all-cause mortality. Although the prevalence of 25(OH)D deficiency is high in patients with acute stroke, the prognostic value of 25(OH)D in stroke has not been clearly established. The purpose of this study was to determine whether the baseline serum 25(OH)D level was associated with the functional outcome in patients with acute ischemic stroke. Methods: From June 2011 to January 2014, consecutive patients with acute ischemic stroke within 7 days of symptom onset were enrolled in this study from a prospectively maintained stroke registry. Serum 25(OH)D level was measured at admission. Clinical and laboratory data including stroke severity using the National Institute of Health Stroke Scale (NIHSS) score were collected during admission, and the functional outcome at 3 months was assessed by modified Rankin scale (mRS). The association between the baseline 25(OH)D level and a good functional outcome (mRS 0-2) at 3 months was analyzed by multiple logistic regression models. Results: A total of 818 patients were enrolled in this study. Mean age was 66.2 (±12.9) years, and 40.5% were female. The mean 25(OH)D level was 47.2 ± 31.7 nmol/l, and the majority of patients met vitamin D deficient status (<50 nmol/l; 68.8%), while an optimal vitamin D level (≥75 nmol/l) was present in only 13.6% of the patients, and 436 (53.3%) patients showed good functional outcome at 3 months. Serum 25(OH)D levels in patients with good outcomes were significantly higher than those with poor outcome (50.2 ± 32.7 vs. 43.9 ± 30.0 nmol/l, p = 0.007). The 3-month functional outcome was significantly associated with month-specific 25(OH)D quartiles in multivariable logistic regression analysis. After adjustment for age and sex, the highest 25(OH)D quartile group had higher tendency for good functional outcome at 3 months (odds ratio (OR) = 1.68, 95% confidence interval (CI) = 1.13-2.51). After fully adjusting for other potential confounders, such as stroke severity and vascular risk factors, the association was further strengthened with an OR (95% CI) of 1.90 (1.14-3.16). Other factors associated with good functional outcome in multivariable analysis were younger age, lower initial NIHSS score and absence of diabetes. Conclusions: This study suggests that serum 25(OH)D level is an independent predictor of functional outcome in patients with acute ischemic stroke. Further studies are required to determine whether vitamin D supplementation could improve functional outcome in patients with ischemic stroke.

scholarly journals Atherogenic Index of Plasma Predicts Outcomes in Acute Ischemic Stroke

2021 ◽  
Vol 12 ◽  
Author(s):  
Hongbing Liu ◽  
Kai Liu ◽  
Lulu Pei ◽  
Shen Li ◽  
Jiawei Zhao ◽  
...  
Keyword(s):  
Logistic Regression ◽  
Ischemic Stroke ◽  
Acute Ischemic Stroke ◽  
Adverse Outcomes ◽  
Atherogenic Index ◽  
Receiver Operating Curve ◽  
Large Artery ◽  
Atherogenic Index Of Plasma ◽  
Outcome Group ◽  
Poor Outcomes

Aim: The atherogenic index of plasma (AIP) was significantly related to adverse outcomes in patients with cardiovascular disease. Our aim was to investigate the association between AIP and adverse outcomes in acute ischemic stroke.Methods: Patients with acute ischemic stroke (AIS) admitted between 2015 and 2018 were prospectively enrolled in this study. Functional outcomes were evaluated by the modified Rankin Scale (mRS). Poor outcomes were defined as mRS 3–6. The relationship of AIP with the risk of outcomes was analyzed by multivariate logistic regression models.Results: A total of 1,463 patients with AIS within 24 h of symptom onset were enrolled. The poor outcome group had a significantly higher level of AIP [0.09 (−0.10 to 0.27) vs. 0.04 (−0.09 to 0.18), p &lt; 0.001] compared with the good outcome group. Multivariable logistic regression analysis showed that higher AIP was associated with poor outcomes in all the stroke patients (OR 1.84, 95% CI, 1.23–2.53, p = 0.007), which was more evident in patients with large-artery atherosclerosis subtype (OR 1.90, 95% CI, 1.53–2.62, p = 0.002), but not in the other subtypes. Receiver operating curve (ROC) analysis revealed that the best predictive cutoff value of AIP was 0.112, with a sensitivity of 70.8% and a specificity of 59.2%, and the area under the ROC curves for AIP was 0.685.Conclusion: AIP may be an important and independent predictor of the outcome of dysfunction in patients with AIS, especially the stroke subtype of large-artery atherosclerosis.

scholarly journals Cortical Microinfarcts Associated With Worse Outcomes in Patients With Acute Ischemic Stroke Receiving Endovascular Treatment

Stroke ◽  
2020 ◽  
Vol 51 (9) ◽  
pp. 2742-2751
Author(s):  
Yufei Wei ◽  
Yuehua Pu ◽  
Yuesong Pan ◽  
Ximing Nie ◽  
Wanying Duan ◽  
...  
Keyword(s):  
Logistic Regression ◽  
Ischemic Stroke ◽  
Endovascular Treatment ◽  
Acute Ischemic Stroke ◽  
Functional Outcome ◽  
Odds Ratio ◽  
Adjusted Odds Ratio ◽  
Primary Outcome ◽  
Large Vessel Occlusion ◽  
Vessel Occlusion

Background and Purpose: We aimed to evaluate the impact of cortical microinfarcts (CMIs) on functional outcome after endovascular treatment in patients with acute ischemic stroke. Methods: In a multicenter registration study for RESCUE-RE (a registration study for Critical Care of Acute Ischemic Stroke After Recanalization), eligible patients with large vessel occlusion stroke receiving endovascular treatment, who had undergone 3T magnetic resonance imaging on admission or within 24 hours after endovascular treatment were analyzed. We evaluated the presence and numbers of CMIs with assessment of axial T1, T2-weighted images, and fluid-attenuated inversion recovery images. The primary outcome was functional dependence or death defined as modified Rankin Scale scores of 3 to 6 at 90 days. Secondary outcomes included early neurological improvement, any intracranial hemorrhage, symptomatic intracranial hemorrhage, and mortality. We investigated the independent associations of CMIs with the outcomes using multivariable logistic regression in overall patients and in subgroups. Results: Among 414 patients (enrolled from July 2018 to May 2019) included in the analyses, 96 (23.2%) patients had at least one CMI (maximum 6). Patients with CMI(s) were more likely to be functionally dependent or dead at 90 days, compared with those without (55.2% versus 37.4%; P <0.01). In multivariable logistic regression analyses, presence of CMI(s) (adjusted odds ratio, 1.78 [95% CI, 1.04−3.07]; P =0.04) and multiple CMIs (CMIs ≥2; adjusted odds ratio, 7.41 [95% CI, 2.48−22.17]; P <0.001) were independently, significantly associated with the primary outcome. There was no significant difference between subgroups in the associations between CMI presence and the primary outcome. Conclusions: Acute large vessel occlusion stroke patients receiving endovascular treatment with CMI(s) were more likely to have a poor functional outcome at 90 days, independent of patients’ characteristics. Such associations may be dose-dependent. Registration: URL: http://www.chictr.org.cn ; Unique identifier: ChiCTR1900022154.

Abstract 1122‐000106: Comparing Machine Learning Algorithms and Regression Models for Predicting Functional Outcome in the STRATIS Registry

2021 ◽  
Vol 1 (S1) ◽  
Author(s):  
Mouhammad A Jumaa ◽  
Zeinab Zoghi ◽  
Syed Zaidi ◽  
Nils Mueller‐Kronast ◽  
Osama Zaidat ◽  
...  
Keyword(s):  
Machine Learning ◽  
Logistic Regression ◽  
Ischemic Stroke ◽  
Acute Ischemic Stroke ◽  
Functional Outcome ◽  
Learning Algorithms ◽  
Learning Model ◽  
Machine Learning Algorithms ◽  
Systematic Evaluation ◽  
Machine Learning Model

Introduction : Machine learning algorithms have emerged as powerful predictive tools in the field of acute ischemic stroke. Here, we examine the predictive performance of a machine algorithm compared to logistic regression for predicting functional outcomes in the prospective Systematic Evaluation of Patients Treated With Neurothrombectomy Devices for Acute Ischemic Stroke (STRATIS) Registry. Methods : The STRATIS Registry was a prospective, observational study of the use of the Solitaire device in acute ischemic stroke patients. Patients with posterior circulation stroke or missing 90‐day mRS were excluding from the analysis. A statistical algorithm (logistic regression) and a machine learning algorithm (decision tree) were implemented on the preprocessed dataset using 10‐fold cross‐validation method where 80% of the data were fed into the models to be trained and the remaining 20% were utilized in the test phase to evaluate the performance of the models for prediction of 90‐day mRS score as dichotomous output. Results : Of the 938 STRATIS patients, 702 with 90‐day mRS were included. The machine learning model outperformed the logistic regression model with a 0.92±0.026 Area Under Curve (AUC) score compared to a 0.88±0.028 AUC score obtained by implementing logistic regression. Conclusions : Our machine learning model delivered improved performance in comparison with the statistical model in predicting 90‐day functional outcome. More studies are needed to understand and externally validate the predictive capacity of our machine learning model.

Adverse Influence of Pre-Stroke Dementia on Short-Term Functional Outcomes in Patients with Acute Ischemic Stroke: The Fukuoka Stroke Registry

2016 ◽  
Vol 43 (1-2) ◽  
pp. 82-89 ◽  
Author(s):  
Yoshinobu Wakisaka ◽  
Ryu Matsuo ◽  
Jun Hata ◽  
Junya Kuroda ◽  
Takanari Kitazono ◽  
...  
Keyword(s):  
Logistic Regression ◽  
Cohort Study ◽  
Ischemic Stroke ◽  
Acute Ischemic Stroke ◽  
Functional Outcome ◽  
Neurological Deterioration ◽  
Stroke Onset ◽  
Matched Cohort ◽  
Poor Functional Outcome ◽  
Stroke Registry

Background: Dementia and stroke are major causes of disability in the elderly. However, the association between pre-stroke dementia and functional outcome after stoke remains unresolved. We aimed to determine this association in patients with acute ischemic stroke. Methods: Among patients registered in the Fukuoka Stroke Registry from June 2007 to May 2015, 4,237 patients with ischemic stroke within 24 h of onset, who were functionally independent before the onset, were enrolled in this study. Pre-stroke dementia was defined as any type of dementia that was present prior to the index stroke. Primary and secondary study outcomes were poor functional outcome (modified Rankin Scale 3-6) at 3 months after the stroke onset and neurological deterioration (≥2-point increases on the National Institutes of Health Stroke Scale score during hospitalization), respectively. For propensity score (PS)-matched cohort study to control confounding variables for pre-stroke dementia, 318 pairs of patients with and without pre-stroke dementia were also selected on the basis of 1:1 matching. Multivariable logistic regression models and conditional logistic regression analysis were used to quantify associations between pre-stroke dementia and study outcomes. Results: Of all 4,237 participants, 347 (8.2%) had pre-stroke dementia. The frequencies of neurological deterioration and poor functional outcome were significantly higher in patients with pre-stroke dementia than in those without pre-stroke dementia (neurological deterioration, 16.1 vs. 7.1%, p < 0.01; poor functional outcome, 63.7 vs. 27.1%, p < 0.01). Multivariable analysis showed that pre-stroke dementia was significantly associated with neurological deterioration (OR 1.67; 95% CI 1.14-2.41; p < 0.01) and poor functional outcome (OR 2.91; 95% CI 2.17-3.91; p < 0.01). In the PS-matched cohort study, the same trends were observed between the pre-stroke dementia and neurological deterioration (OR 2.60; 95% CI 1.17-5.78; p < 0.01) and between the dementia and poor functional outcome (OR 3.62; 95% CI 1.89-6.95; p < 0.01). Conclusions: Pre-stroke dementia was significantly associated with higher risks for poor functional outcome at 3 months after stroke onset as well as for neurological deterioration during hospitalization in patients with acute ischemic stroke.

Association between Blood Urea Nitrogen-to-creatinine Ratio and Three-Month Outcome in Patients with Acute Ischemic Stroke

2019 ◽  
Vol 16 (2) ◽  
pp. 166-172 ◽  
Author(s):  
Linghui Deng ◽  
Changyi Wang ◽  
Shi Qiu ◽  
Haiyang Bian ◽  
Lu Wang ◽  
...  
Keyword(s):  
Logistic Regression ◽  
Ischemic Stroke ◽  
Clinical Outcome ◽  
Acute Ischemic Stroke ◽  
Blood Urea Nitrogen ◽  
Univariate Analysis ◽  
Density Lipoprotein ◽  
Hydration Status ◽  
Creatinine Ratio ◽  
Urea Nitrogen

Background: Hydration status significantly affects the clinical outcome of acute ischemic stroke (AIS) patients. Blood urea nitrogen-to-creatinine ratio (BUN/Cr) is a biomarker of hydration status. However, it is not known whether there is a relationship between BUN/Cr and three-month outcome as assessed by the modified Rankin Scale (mRS) score in AIS patients. Methods: AIS patients admitted to West China Hospital from 2012 to 2016 were prospectively and consecutively enrolled and baseline data were collected. Poor clinical outcome was defined as three-month mRS > 2. Univariate and multivariate logistic regression analyses were performed to determine the relationship between BUN/Cr and three-month outcome. Confounding factors were identified by univariate analysis. Stratified logistic regression analysis was performed to identify effect modifiers. Results: A total of 1738 patients were included in the study. BUN/Cr showed a positive correlation with the three-month outcome (OR 1.02, 95% CI 1.00-1.03, p=0.04). However, after adjusting for potential confounders, the correlation was no longer significant (p=0.95). An interaction between BUN/Cr and high-density lipoprotein (HDL) was discovered (p=0.03), with a significant correlation between BUN/Cr and three-month outcome in patients with higher HDL (OR 1.03, 95% CI 1.00-1.07, p=0.04). Conclusion: Elevated BUN/Cr is associated with poor three-month outcome in AIS patients with high HDL levels.

Association of admission leukocyte count with clinical outcomes in acute ischemic stroke patients undergoing intravenous thrombolysis with recombinant tissue plasminogen activator

2020 ◽  
Vol 17 ◽  
Author(s):  
Jie Chen ◽  
Fu-Liang Zhang ◽  
Shan Lv ◽  
Hang Jin ◽  
Yun Luo ◽  
...  
Keyword(s):  
Ischemic Stroke ◽  
Acute Ischemic Stroke ◽  
Plasminogen Activator ◽  
Tissue Plasminogen Activator ◽  
Leukocyte Count ◽  
Intravenous Thrombolysis ◽  
Recombinant Tissue Plasminogen Activator ◽  
Functional Independence ◽  
Tissue Plasminogen ◽  
Poor Outcomes

Objective:: Increased leukocyte count are positively associated with poor outcomes and all-cause mortality in coronary heart disease, cancer, and ischemic stroke. The role of leukocyte count in acute ischemic stroke (AIS) remains important. We aimed to investigate the association between admission leukocyte count before thrombolysis with recombinant tissue plasminogen activator (rt-PA) and 3-month outcomes in AIS patients. Methods:: This retrospective study included consecutive AIS patients who received intravenous (IV) rt-PA within 4.5 h of symptom onset between January 2016 and December 2018. We assessed outcomes including short-term hemorrhagic transformation (HT), 3-month mortality, and functional independence (modified Rankin Scale [mRS] score of 0–2 or 0–1). Results:: Among 579 patients who received IV rt-PA, 77 (13.3%) exhibited HT at 24 h, 43 (7.4%) died within 3 months, and 211 (36.4%) exhibited functional independence (mRS score: 0–2). Multivariable logistic regression revealed admission leukocyte count as an independent predictor of good and excellent outcomes at 3 months. Each 1-point increase in admission leukocyte count increased the odds of poor outcomes at 3 months by 7.6% (mRS score: 3–6, odds ratio (OR): 1.076, 95% confidence interval (CI): 1.003–1.154, p=0.041) and 7.8% (mRS score: 2–6, OR: 1.078, 95% CI: 1.006–1.154, p=0.033). Multivariable regression analysis revealed no association between HT and 3-month mortality. Admission neutrophil and lymphocyte count were not associated with 3-month functional outcomes or 3-month mortality. Conclusion:: Lower admission leukocyte count independently predicts good and excellent outcomes at 3 months in AIS patients undergoing rt-PA treatment.

scholarly journals Study of Short Latency Somatosensory and Brain Stem Auditory Evoked Potentials Patients with Acute Ischemic Stroke Involving Middle Cerebral Artery Territory

2021 ◽  
Author(s):  
Abhishek Miryala ◽  
Mahendra Javali ◽  
Anish Mehta ◽  
Pradeep R. ◽  
Purushottam Acharya ◽  
...  
Keyword(s):  
Ischemic Stroke ◽  
Evoked Potentials ◽  
Middle Cerebral Artery ◽  
Acute Ischemic Stroke ◽  
Brain Stem ◽  
Functional Outcome ◽  
Cerebral Artery ◽  
Negative Correlation ◽  
Auditory Evoked Potentials ◽  
Positive Correlation

Abstract Background The precise timings of evoked potentials in evaluating the functional outcome of stroke have remained indistinct. Few studies in the Indian context have studied the outcome of early prognosis of stroke utilizing evoked potentials. Objective The aim of this study was to determine somatosensory evoked potentials (SSEPs) and brain stem auditory evoked potentials (BAEPs), their timing and abnormalities in acute ischemic stroke involving the middle cerebral artery (MCA) territory and to correlate SSEP and BAEP with the functional outcome (National Institutes of Health Stroke Scale (NIHSS), modified Rankin scale (mRS) and Barthel’s index) at 3 months. Methods MCA territory involved acute ischemic stroke patients (n = 30) presenting consecutively to the hospital within 3 days of symptoms onset were included. Details about clinical symptoms, neurological examination, treatment, NIHSS score, mRS scores were collected at the time of admission. All patients underwent imaging of the brain and were subjected to SSEP and BAEP on two occasions, first at 1 to 3 days and second at 4 to 7 days from the onset of stroke. At 3 months of follow-up, NIHSS, mRS, and Barthel’s index were recorded. Results P37 and N20 amplitude had a strong negative correlation (at 1–3 and 4–7 days) with NIHSS at admission, NIHSS at 3 months, mRS at admission, and mRS at 3 months and a significant positive correlation with Barthel’s index (p < 0.0001). BAEP wave V had a negative correlation (at 1–3 and 4–7 days) with NIHSS at admission, NIHSS at 3 months, mRS at admission, and mRS at 3 months and a positive correlation with Barthel’s index (p < 0.0001). Conclusion SSEP abnormalities recorded on days 4 to 7 from onset of stroke are more significant than those recorded within 1 to 3 days of onset of stroke; hence, the timing of 4 to 7 days after stroke onset can be considered as better for predicting functional outcome.

scholarly journals Eosinophil-to-monocyte ratio is a potential biomarker in the prediction of functional outcome among patients with acute ischemic stroke

2021 ◽  
Vol 22 (1) ◽  
Author(s):  
Shuhong Yu ◽  
Yi Luo ◽  
Tan Zhang ◽  
Chenrong Huang ◽  
Yu Fu ◽  
...  
Keyword(s):  
Ischemic Stroke ◽  
Acute Ischemic Stroke ◽  
Functional Outcome ◽  
Odds Ratio ◽  
Poor Outcome ◽  
Net Reclassification Improvement ◽  
Potential Biomarker ◽  
The Impact ◽  
The Relationship ◽  
Integrated Discrimination Improvement

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.

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