Abstract 147: The Association Between Hematocrit and Mortality among Ischemic Stroke Patients

Stroke ◽  
2012 ◽  
Vol 43 (suppl_1) ◽  
Author(s):  
Jason J Sico ◽  
Laura J Myers ◽  
Dede Ordin ◽  
Linda S Williams ◽  
Dawn M Bravata
Keyword(s):  
Logistic Regression ◽  
Ischemic Stroke ◽  
Acute Ischemic Stroke ◽  
Stroke Mortality ◽  
Multivariate Logistic Regression ◽  
P Values ◽  
Time Points ◽  
Post Stroke ◽  
One Year ◽  
The Relationship

Introduction: Anemia is associated with higher mortality among patients with such non-stroke vascular conditions as heart failure and myocardial infarction. Less is known regarding the relationship between anemia and mortality among patients with acute ischemic stroke. Methods: Medical records were abstracted for a sample of 3965 veterans from 131 Veterans Health Administration (VHA) facilities who were admitted for a confirmed diagnosis of ischemic stroke (fiscal year 2007). Hematocrit (Hct) values from 24-hours of admission were categorized into 6-tiers (≤27%, 28-32%, 33-37%, 38-42%, 43-47%, ≥48%). We excluded patients with: female gender (n=95), incomplete Hct data (n=94), thrombolysis (n=32), and inconsistent death dates (n=6). We used multivariate logistic regression to examine the relationship between anemia and in-hospital, 30-day, 60-day and one-year mortality using multivariate logistic regression models for each time point, adjusting for age, NIHSS, comorbidity (including pneumonia), and Acute Physiology and Chronic Health Evaluation (APACHE)-III scores. The discrimination (c-statistics) and calibration (Hosmer-Lemeshow goodness of fit [HLGOF]) statistics were generated to gauge model performance and fit. Results: Approximately 2.1% of the N=3750 patients presented with Hcts ≤27%, 6.2% were 28-32%, 17.9% were 33-37%, 36.4% were 38-42%, 28.2% were 43-47%, and 9.1% were ≥48%. Adjusted mortality odds at all time points were 2.5 to 3.5 times higher for those with ≤Hct 27% (p values < 0.013 for in-hospital and 30-day mortality; p values at 6 months and one year were 0.002 and 0.001, respectively). Mortality risk at 6 months and 1 year showed a significant and dose-response relationship to Hct for all Hct groups <38%. High Hcts were independently associated only with in-hospital mortality and only in those with Hct ≥48 (OR 2.9, p=0.004). Models performed well across time points (C=0.813, HLGOF=0.9684 [in-hospital]; C=0.832, HLGOF=0.8186 [30-day]; C=0.863, HLGOF=0.7307 [60-day]; C=0.880, HLGOF=0.4313 [one-year]). Conclusions: Even a moderate level of anemia is independently associated with an increased risk of death during the first year following acute ischemic stroke. Very low or very high Hct is associated with early post-stroke mortality. Further work is required to evaluate whether interventions that treat anemia, its complications and underlying etiologies may also reduce post-stroke mortality.

scholarly journals Risk stratification model for post-stroke pneumonia in patients with acute ischemic stroke

2019 ◽  
Vol 19 (6) ◽  
pp. 513-520
Author(s):  
Ya-Wen Kuo ◽  
Yen-Chu Huang ◽  
Meng Lee ◽  
Tsong-Hai Lee ◽  
Jiann-Der Lee
Keyword(s):  
Logistic Regression ◽  
Ischemic Stroke ◽  
Acute Ischemic Stroke ◽  
Pulse Rate ◽  
Predictive Factors ◽  
Smoking Habit ◽  
Multivariate Logistic Regression ◽  
Nihss Score ◽  
Post Stroke ◽  
Cart Analysis

Background: Post-stroke pneumonia (PSP) has been implicated in the morbidity, mortality, and increased medical costs after acute ischemic stroke. Aim: The aim of this study was to develop a prediction model for PSP in patients with acute ischemic stroke. Methods: A retrospective, case-control, secondary analysis study was conducted using data for 10,034 patients with ischemic stroke who presented to the hospital within 24 hours of onset of stroke symptoms. The predictive factors for PSP were analyzed using multivariate logistic regression and classification and regression tree (CART) analyses. Results: Among the study population, 546 patients (5.4%) had PSP. Multivariate logistic regression revealed that age, atrial fibrillation, smoking habit, body temperature at admission, pulse rate at admission, National Institute of Health Stroke Scale (NIHSS) score upon admission, white blood cell count, and blood urea nitrogen level were major predictive factors of PSP. CART analysis identified NIHSS score at admission, pulse rate at admission, and percentage of lymphocyte as important factors for PSP to stratify the patients into subgroups. The subgroup of patients with an NIHSS score >14 at admission and pulse rate >111 beats per minute at admission and those with an NIHSS score >14, pulse rate ⩽111 beats per minute at admission, and percentage of lymphocyte ⩽9.2% had a relatively high risk of PSP (39.6% and 35.5%, respectively). Conclusions: In this study, CART analysis has a similar predictive value of PSP as compared with a logistic regression model. In addition, decision rules generated by CART can easily be interpreted and applied in clinical practice.

Serum Albumin as a Potential Predictor of Pneumonia after an Acute Ischemic Stroke

2020 ◽  
Vol 17 (4) ◽  
pp. 385-393
Author(s):  
Xue Yang ◽  
Lu Wang ◽  
Lukai Zheng ◽  
Jiongxing Wu ◽  
Junfeng Liu ◽  
...  
Keyword(s):  
Logistic Regression ◽  
Ischemic Stroke ◽  
Serum Albumin ◽  
Acute Ischemic Stroke ◽  
Area Under The Curve ◽  
Albumin Level ◽  
Multivariate Logistic Regression ◽  
Post Stroke ◽  
Mild Stroke ◽  
Univariate Analyses

Background: Serum albumin level is associated with infection after stroke, but whether albumin predicts post-stroke pneumonia is unclear. The potential relationship between albumin level and pneumonia in patients with acute ischemic stroke (AIS) was evaluated in this study. Methods: A consecutive sample of 798 AIS patients who were admitted to West China Hospital within 24 h after onset, from the year 2017 to 2018, were retrospectively analyzed. Blood was collected on admission and assayed for serum albumin. Univariate analyses, multivariate logistic regression, and stratified logistic regression were performed to identify the risk factors of post-stroke pneumonia. Results: Out of the 798 patients, 240 (30.2%) developed pneumonia at a median of 48 h after onset (interquartile range, 27-74 h). Patients with pneumonia had significantly lower serum albumin levels than those without pneumonia (40.6 vs. 42.9 g/l, p<0.001). After adjustment, the albumin level was still significantly associated with pneumonia in multivariate logistic regression (odds ratio [OR] 0.87, 95% confidence interval [CI] 0.81-0.94). The association between serum albumin and pneumonia tended to depend on National Institutes of Health Stroke Scale score (p = 0.045), but this was significant only in patients with mild stroke (OR 0.84, 95% CI 0.77-0.93). A dosedependent inverse relationship was found between albumin levels and the risk of pneumonia after AIS. Albumin values predicted pneumonia with an area under the curve of 0.661 (95% CI 0.620- 0.701), and the optimal cutoff was 42.6 g/L. Conclusion: Low serum albumin levels may be independent predictors of pneumonia in patients with AIS, especially in mild stroke. In fact, the risk of pneumonia may vary inversely with albumin level.

High Risk of One-year Stroke Recurrence in Patients with Younger Age and Prior History of Ischemic Stroke

2019 ◽  
Vol 16 (3) ◽  
pp. 250-257 ◽  
Author(s):  
Jiann-Der Lee ◽  
Ya-Han Hu ◽  
Meng Lee ◽  
Yen-Chu Huang ◽  
Ya-Wen Kuo ◽  
...  
Keyword(s):  
Logistic Regression ◽  
Ischemic Stroke ◽  
Multivariate Logistic Regression Analysis ◽  
Stroke Recurrence ◽  
Prior History ◽  
Multivariate Logistic Regression ◽  
Cart Analysis ◽  
Younger Age ◽  
History Of ◽  
One Year

Background and Purpose: Recurrent ischemic strokes increase the risk of disability and mortality. The role of conventional risk factors in recurrent strokes may change due to increased awareness of prevention strategies. The aim of this study was to explore the potential risk factors besides conventional ones which may help to affect the advances in future preventive concepts associated with one-year stroke recurrence (OSR). Methods: We analyzed 6,632 adult patients with ischemic stroke. Differences in clinical characteristics between patients with and without OSR were analyzed using multivariate logistic regression and classification and regression tree (CART) analyses. Results: Among the study population, 525 patients (7.9%) had OSR. Multivariate logistic regression analysis revealed that male sex (OR 1.243, 95% CI 1.025 – 1.506), age (OR 1.015, 95% CI 1.007 - 1.023), and a prior history of ischemic stroke (OR 1.331, 95% CI 1.096 – 1.615) were major factors associated with OSR. CART analysis further identified age and a prior history of ischemic stroke were important factors for OSR when classified the patients into three subgroups (with risks of OSR of 8.8%, 3.8%, and 12.5% for patients aged > 57.5 years, ≤ 57.5 years/with no prior history of ischemic stroke, and ≤ 57.5 years/with a prior history of ischemic stroke, respectively). Conclusions: Male sex, age, and a prior history of ischemic stroke could increase the risk of OSR by multivariate logistic regression analysis, and CART analysis further demonstrated that patients with a younger age (≤ 57.5 years) and a prior history of ischemic stroke had the highest risk of OSR.

Abstract T P307: Similar Rates of Early Cognitive Dysfunction after Intracerebral Hemorrhage and Acute Ischemic Stroke

Stroke ◽  
2015 ◽  
Vol 46 (suppl_1) ◽  
Author(s):  
M. Carter Denny ◽  
Suhas S Bajgur ◽  
Kim Y Vu ◽  
Rahul R Karamchandani ◽  
Amrou Sarraj ◽  
...  
Keyword(s):  
Logistic Regression ◽  
Ischemic Stroke ◽  
Intracerebral Hemorrhage ◽  
Acute Ischemic Stroke ◽  
Cognitive Dysfunction ◽  
Hospital Setting ◽  
Stroke Severity ◽  
Regression Analyses ◽  
Post Stroke ◽  
Poor Outcome

Introduction: Post-stroke cognitive dysfunction (CD) affects at least 1/3 of acute ischemic stroke (AIS) patients when assessed at 3 months. Limited data exists on CD in intracerebral hemorrhage (ICH). The role of early, in-hospital cognitive screening using the brief Montreal Cognitive Assessment (mini MoCA) is being investigated at our center. Hypothesis: We assessed the rates of early CD in ICH and AIS and hypothesized that even minor deficits from these disorders causes significant CD. Methods: 1218 consecutive stroke patients admitted from 2/13 to 12/13 were reviewed; 610, 442 with AIS and 168 with ICH, with admission NIHSS and mini MoCAs were included in the final analyses. CD was defined as mini MoCA <9 (max 12). Poor outcome was defined as discharge mRS 4-6. Stroke severity was stratified by NIHSS score of 0-5, 6-10, 11-15, 16-20, 21-42 as in ECASS-I . Chi-squared tests and univariate logistic regression analyses were performed. Results: Baseline characteristics are shown in table 1. AIS and ICH groups were similar with regard to race, gender and stroke severity. ICH patients were younger, had longer stroke service lengths of stay and poorer outcomes than AIS patients (p=0.03, p<0.001, p<0.001). No difference was seen in rates of CD between AIS and ICH patients (60% vs. 57%, p=0.36, OR 1.2 (CI 0.8-1.7)). CD rates ranged from 36% for NIHSS 0-5 to 96% for 21-42 (figure 1). Older patients were twice as likely to have CD (p<0.001, OR 2.2 (CI 1.6 - 3.0)). Patients with CD had five times the odds of having a poor outcome compared to the cognitively intact (p<0.001, OR 5.2 (CI 3.4-7.7)). In univariate logistic regression analyses, age was a significant predictor of CD in AIS, but not in ICH (p= <0.001, p=0.06). Conclusion: Post-stroke CD is common across all severities and occurs at similar rates in AIS and ICH. More than 1/3 of patients with minor deficits (NIHSS 0-5) had CD in the acute hospital setting. Whether early CD is predictive of long term cognitive outcomes deserves further study.

scholarly journals Delayed Stroke Treatment during COVID-19 Pandemic in China

2020 ◽  
Author(s):  
Shiyuan Gu ◽  
Zhengze Dai ◽  
Huachao Shen ◽  
Yongjie Bai ◽  
Xiaohao Zhang ◽  
...  
Keyword(s):  
Logistic Regression ◽  
Regression Analysis ◽  
Ischemic Stroke ◽  
Acute Stroke ◽  
Acute Ischemic Stroke ◽  
Logistic Regression Analysis ◽  
Multivariate Logistic Regression Analysis ◽  
Intravenous Thrombolysis ◽  
Multivariate Logistic Regression ◽  
Delayed Treatment

ABSTRACTBackgroundSocial distance, quarantine, pathogen testing and other preventive strategies implemented during COVID-19 pandemic may negatively influence the management of acute stroke.ObjectiveThe current study aimed to evaluate the impacts of COVID-19 pandemic on treatment delay of acute stroke in China.MethodsThis study included patients with acute stroke admitted in two hospitals in Jiangsu, China. Patients admitted before and after the COVID-19 epidemic outbreak (January 31, 2020, as officially announced by Chinese government) were compared for pre- (measured as onset-to-door time) and post-hospital delay (measured as door-to-needle time). The influence factors for delayed treatment (indicated as onset-to-needle time >4.5 hours) were analyzed with multivariate logistic regression analysis.ResultsOnset-to-door time increased from 202 min (IQR 65-492) before to 317 min (IQR 75-790) after the COVID-19 pandemic (P=0.001). Door-to-needle time increased from 50min (IQR 40-75) before to 65 min (IQR 48-84) after the COVID-19 pandemic (P=0.048). The proportion of patients with intravenous thrombolysis in those with acute ischemic stroke was decreased significantly after the pandemic (15.4% vs 20.1%; P=0.030). Multivariate logistic regression analysis indicated that patients after COVID-19 pandemic, lower educational level, rural residency, mild symptoms and transported by other means than ambulance were associated with delayed treatment.ConclusionsCOVID-19 pandemic has remarkable impacts on the management of acute ischemic stroke. Both pre- and post-hospital delays were prolonged significantly, and proportion of patient arrived within the 4.5-hour time window for intravenous thrombolysis treatment was decreased. Given that anti-COVID-19 measures are becoming medical routines, efforts are warranted to shorten the delay so that the outcomes of stroke could be improved.

Insulin resistance may affect the functional recovery of acute ischemic stroke in non-diabetic patients

2020 ◽  
Author(s):  
Yoonkyung Chang ◽  
Chi Kyung Kim ◽  
Min-Kyung Kim ◽  
Woo‐Keun Seo ◽  
Kyungmi Oh
Keyword(s):  
Insulin Resistance ◽  
Logistic Regression ◽  
Ischemic Stroke ◽  
Blood Glucose ◽  
Acute Ischemic Stroke ◽  
Functional Recovery ◽  
Diabetic Patients ◽  
Model Assessment ◽  
Multivariate Logistic Regression ◽  
Stroke Patients

Abstract Background Insulin resistance is associated with the occurrence of stroke and atherosclerotic disease. However, the relationship between insulin resistance and the prognosis of acute ischemic stroke in nondiabetic patients is unclear. We hypothesized that insulin resistance may affect short-term functional recovery after acute ischemic stroke in nondiabetic patients. Methods Between May 2014 and December 2016, 1377 consecutive patients with acute ischemic stroke were enrolled from a prospectively maintained stroke registry. After excluding patients with transient ischemic attacks (TIA), pre-stroke disabilities, diabetes mellitus, and patients with incomplete evaluations, 517 patients were included in the study. The homeostasis model assessment of insulin resistance (HOMA-IR) score was used to evaluate the degree of insulin resistance. The factors associated with poor functional outcomes were analyzed using multivariate logistic regression. Results The patients with the highest quartile of log HOMA-IR index scores were younger and had higher fasting blood glucose, total cholesterol, triglycerides, low-density lipoprotein, and HbA1c levels. Multivariate logistic regression analysis revealed that log HOMA-IR scores were independently associated with poor prognosis after adjusting for age and sex and p < 0.1 in univariate analysis. Conclusion Insulin resistance measured by the HOMA-IR index was associated with the poor functional outcome of non-diabetic stroke patients. This evidence supports treating insulin resistance in acute ischemic stroke patients with blood glucose levels within the normal range.

Abstract WMP103: Epilepsy is Associated With Poorer Neurologic Outcome After Pediatric Arterial Ischemic Stroke

Stroke ◽  
2016 ◽  
Vol 47 (suppl_1) ◽  
Author(s):  
Christine K Fox ◽  
Lori C Jordan ◽  
Mark T Mackay ◽  
Gabrielle deVeber ◽  
Keyword(s):  
Ischemic Stroke ◽  
Neurologic Outcome ◽  
First Year ◽  
Stroke Outcome ◽  
Arterial Ischemic Stroke ◽  
Post Stroke ◽  
One Year ◽  
Active Epilepsy ◽  
Relationship Of ◽  
The Relationship

Introduction: Post-stroke epilepsy is common in children, but the relationship of childhood epilepsy with stroke outcome is poorly understood. Hypothesis: Children with epilepsy after arterial ischemic stroke have worse outcomes than those without epilepsy. Methods: We prospectively enrolled children (birth-18 years) with arterial ischemic stroke and identified remote seizures (occurring ≥ 7 days post-stroke). At one-year, patients with active epilepsy (≥ 1 remote seizure + maintenance anti-convulsant) were identified and Pediatric Stroke Outcome Measure (PSOM) was scored. Total PSOM scores range from 0-10; higher values reflect more severe neurologic deficits. Ordinal logistic regression was used to evaluate the relationship between clinical factors and PSOM scores. PSOM scores were categorized 0-1, 1.5-3, 3.5-6, 6.5-10 to depict stratified distribution. Results: Among 94 children (54% male; 20% Hispanic; 25% neonatal strokes; median age for childhood strokes 6.1 years, IQR 1.3-12), 12 had ≥ 1 remote seizure during the first year post-stroke. At one-year follow-up, 19 children were taking a maintenance anti-convulsant and 10 children had active epilepsy. Median PSOM score at one-year for the overall cohort was 0.5 (IQR 0-1.5). Median PSOM score among children with active epilepsy was 3.3 (IQR 0.5-6). Figure demonstrates distribution of categorized PSOM scores stratified by the presence of active epilepsy. On univariable regression analyses, older age (OR 1.1, 95% CI 1.0-1.1, P=0.02), maintenance anti-convulsant at one-year (OR 2.7, 95% CI 1.0-7.0, P=0.04) and active epilepsy (OR 6.3, 95% CI 1.7-25, P=0.007) were associated with higher total PSOM scores. After multivariable adjustment for age and maintenance anti-convulsant, active epilepsy remained associated with higher total PSOM score (OR 7.8, 95% CI 1.3-46, P=0.02). Conclusions: Active epilepsy one-year after pediatric arterial ischemic stroke is associated with poorer neurologic outcome.

Development of a prediction model for 1-year poor prognosis in patients with acute ischemic stroke

2019 ◽  
Vol 67 (6) ◽  
pp. 957-963 ◽  
Author(s):  
Xia Ling ◽  
Bo Shen ◽  
Kangzhi Li ◽  
Lihong Si ◽  
Xu Yang
Keyword(s):  
Risk Factors ◽  
Logistic Regression ◽  
Ischemic Stroke ◽  
Prediction Model ◽  
Acute Ischemic Stroke ◽  
Poor Prognosis ◽  
Multivariate Logistic Regression ◽  
Lemeshow Test ◽  
Independent Risk Factors ◽  
Auc Value

The goals of this study were to develop a new prediction model to predict 1-year poor prognosis (death or modified Rankin scale score of ≥3) in patients with acute ischemic stroke (AIS) and to compare the performance of the new prediction model with other prediction scales. Baseline data of 772 patients with AIS were collected, and univariate and multivariate logistic regression analyses were performed to identify independent risk factors for 1-year poor prognosis in patients with AIS. The area under the receiver operating characteristics curve (AUC) value of the new prediction model and the THRIVE, iScore and ASTRAL scores was compared. The Hosmer-Lemeshow test was used to assess the goodness of fit of the model. We identified 196 (25.4%) patients with poor prognosis at 1-year follow-up, and of these 68 (68/196, 34.7%) had died. Multivariate logistic regression and receiver operating characteristic curve analyses showed that age ≥70 years, consciousness (lethargy or coma), history of stroke or transient ischemic attack, cancer, abnormal fasting blood glucose levels ≥7.0 mmol/L, and National Institutes of Health Stroke Scale score were independent risk factors for 1-year poor prognosis in patients with AIS. Scores were assigned for each variable by rounding off β coefficient to the integer score, and a new prediction model with a maximum total score of 9 points was developed. The AUC value of the new prediction model was higher than the THRIVE score (p<0.05). The χ2 value for the Hosmer-Lemeshow test was 7.337 (p>0.05), suggesting that the prediction model had a good fit. The new prediction model can accurately predict 1-year poor prognosis in Chinese patients with AIS.

scholarly journals Simple prediction model for unfavorable outcome in ischemic stroke after intravenous thrombolytic therapy

2016 ◽  
Vol 74 (12) ◽  
pp. 986-989 ◽  
Author(s):  
Daniel Amitrano ◽  
Ivan Rocha Ferreira da Silva ◽  
Bernardo B. Liberato ◽  
Valéria Batistella ◽  
Janaina Oliveira ◽  
...  
Keyword(s):  
Logistic Regression ◽  
Ischemic Stroke ◽  
Thrombolytic Therapy ◽  
Acute Ischemic Stroke ◽  
Logistic Regression Model ◽  
National Institutes Of Health ◽  
Unfavorable Outcome ◽  
Multivariate Logistic Regression ◽  
Stroke Patients ◽  
Present On Admission

ABSTRACT Objective We aimed to develop a model to predict unfavorable outcome in patients with acute ischemic stroke treated with intravenous thrombolytic therapy (IVT), based on simple variables present on admission. Methods Retrospective analysis of acute ischemic stroke patients treated with IVT in a hospital in Rio de Janeiro. Clinical and radiographic variables were selected for analysis. Multivariate logistic regression was used to develop a predictive model. Results We analyzed a total of 82 patients. Median National Institutes of Health Stroke Scale (NIHSS) on admission was 9 (3–22), 40.2% presented with a hyperdense artery sign (HAS), 62% had identifiable early parenchymal changes and 61.6% experienced a favorable outcome. An NIHSS score of > 12 on arrival, age > 70 and the presence of HAS were associated with the outcome, even after correction in a logistic regression model. Conclusion An NIHSS > 12 on arrival, presence of HAS and age > 70 years were predictors of unfavorable outcome at three months in patients with acute ischemic stroke treated with IVT.

ASPECTS discrepancies between CT and MR imaging: analysis and implications for triage protocols in acute ischemic stroke

2016 ◽  
Vol 9 (3) ◽  
pp. 240-243 ◽  
Author(s):  
Ferdinand K Hui ◽  
Nancy A Obuchowski ◽  
Seby John ◽  
Gabor Toth ◽  
Irene Katzan ◽  
...  
Keyword(s):  
Logistic Regression ◽  
Ischemic Stroke ◽  
Acute Ischemic Stroke ◽  
Diffusion Weighted Imaging ◽  
Multivariate Analyses ◽  
National Institutes Of Health ◽  
Imaging Analysis ◽  
Multivariate Logistic Regression ◽  
The Cost ◽  
Optimal Imaging

BackgroundOptimal imaging triage for intervention for large vessel occlusions remains unclear. MR-based imaging provides ischemic core volumes at the cost of increased imaging time. CT Alberta Stroke Program Early CT Score (ASPECTS) estimates are faster, but may be less sensitive.ObjectiveTo assesses the rate at which MRI changed management in comparison with CT imaging alone.MethodsRetrospective analysis of patients with acute ischemic stroke undergoing imaging triage for endovascular therapy was performed between 2008 and 2013. Univariate and multivariate analyses were performed. Multivariate logistic regression was used to evaluate the effect of time on disagreement in MRI and CT ASPECTS scores.ResultsA total of 241 patients underwent both diffusion-weighted imaging (DWI) and CT. Six patients with DWI ASPECTS ≥6 and CT ASPECTS <6 were omitted, leaving 235 patients. For 47 patients, disagreement between the two modalities resulted in different treatment recommendations. The estimated probability of disagreement was 20.0% (95% CI 15.4% to 25.6%). In a multivariate logistic regression, CT ASPECTS >7 (p=0.004) and admission National Institutes of Health Stroke Scale (NIHSS) score <16 (p=0.008) were simultaneously significant predictors of agreement in ASPECTS. The time between modalities was a marginally significant predictor (p=0.080).ConclusionsThe study suggests that patients with NIHSS scores at admission of <16 and patients with CT ASPECTS >7 have a higher likelihood of agreement between CT and DWI based on an ASPECTS cut-off value of 6. Additional MRI for triage in patients with NIHSS at admission of >16, and ASPECTS of 6 or 7 may be more likely to change management. Unsurprisingly, patients with low CT ASPECTS had good correlation with MRI ASPECTS.

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