Abstract TP21: Is Presence of Diabetes Mellitus a Key Prognostic Factor among Patients Receiving Endovascular Treatment for Acute Ischemic Stroke?

Stroke ◽  
2017 ◽  
Vol 48 (suppl_1) ◽  
Author(s):  
Seong-Joon Lee ◽  
Yang-Ha Hwang ◽  
Ji Man Hong ◽  
Jin Wook Choi ◽  
Dong-Hun Kang ◽  
...  
Keyword(s):  
Diabetes Mellitus ◽  
Logistic Regression ◽  
Regression Analysis ◽  
Ischemic Stroke ◽  
Acute Ischemic Stroke ◽  
Logistic Regression Analysis ◽  
Multiple Logistic Regression Analysis ◽  
Univariate Analysis ◽  
Intravenous Thrombolysis ◽  
The Impact

Introduction: Given the recent positive endovascular therapy trials for acute ischemic stroke (AIS), this therapeutic strategy is now being increasingly incorporated into routine clinical practice. Identifying prognostic factors among AIS patients receiving endovascular revascularization treatments (ERT) in the real world could be important for clinicians and patients. While the impact of diabetes mellitus (DM) on IV thrombolytic outcomes after AIS has been extensively investigated, there is a paucity of data assessing effects of DM on ERT outcomes after AIS. We evaluated the impact of comorbid DM on ERT for AIS. Methods: From Jan 2011 to Feb 2016, patients with AIS who underwent ERT for cervicocephalic occlusions were consecutively enrolled into the Acute Stroke due to Intracranial Atherosclerotic occlusion and Neurointervention - Korean Retrospective (ASIAN KR) registry from 3 hospitals. Patients were excluded if onset to puncture time over 8 hours, in-hospital stroke, or unavailable 3-month mRS. DM was diagnosed if a patient had the history, or hemoglobin A1c on admission was over 6.5. Univariate analysis was performed to compare the characteristics between DM and non-DM population. Multiple logistic regression analysis was used to validate the effect of comorbid DM on 3 month outcomes. Results: Of 721 patients, 667 (93%) were finally included, with 233 DM patients and 434 non-DM patients. In the univariate analysis, comorbidity with hypertension (71.2% vs. 58.3%, p=0.001) and dyslipidemia (36.7% vs. 26.7%, p=0.012) were more frequent in the DM population. Periprocedural factors such as target vessels, intravenous thrombolysis, and final reperfusion grades did not differ. Good outcomes with mRS 0-2 were less frequent in the DM population (43.3% vs. 53.7%, p=0.011). In the logistic regression analysis adjusting age, male sex, initial NIHSS, premorbid mRS, hypertension history, atrial fibrillation, intravenous thrombolysis, onset to puncture time and successful reperfusion, DM was an independent predictor of poor outcomes (mRS 3-6; 1.933, 1.274-2.933, p=0.002). Conclusion: In patients receiving ERT for AIS due to cervicocephalic artery occlusions, the presence of DM as a comorbidity confers greater odds of a poor functional outcome.

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.

scholarly journals Serum Albumin Is Negatively Associated with Hemorrhagic Transformation in Acute Ischemic Stroke Patients

2019 ◽  
Vol 47 (1-2) ◽  
pp. 88-94 ◽  
Author(s):  
Changyi Wang ◽  
Linghui Deng ◽  
Shi Qiu ◽  
Haiyang Bian ◽  
Lu Wang ◽  
...  
Keyword(s):  
Logistic Regression ◽  
Regression Analysis ◽  
Ischemic Stroke ◽  
Serum Albumin ◽  
Acute Ischemic Stroke ◽  
Logistic Regression Analysis ◽  
Univariate Analysis ◽  
Multivariate Logistic Regression Analysis ◽  
Hemorrhagic Transformation ◽  
Dependent Manner

Background and Objective: Hemorrhagic transformation (HT) is a major complication of acute ischemic stroke (AIS). Serum albumin is known for its neuroprotective effects and is a marker of improved AIS patient outcomes. However, it is not known whether there is a relationship between serum albumin and HT. Methods: AIS patients admitted to the Department of Neurology of West China Hospital from 2012 to 2016 were prospectively and consecutively enrolled. Baseline characteristics were collected. HT during hospitalization was diagnosed by brain imaging. Multivariate logistic regression analysis was performed to determine the relationship between serum albumin and HT. Confounding factors were identified by univariate analysis. Stratified logistic regression analysis was performed to identify effect modifiers. Results: A total of 1996 AIS patients were recruited, of whom 135 (6.8%) developed HT. Serum albumin negatively correlated with HT. Patients in the upper serum albumin tertile (42.6–54.1 g/L) had a 46% lower risk of HT than patients in the lower tertile (19.3–39.1 g/L) after adjustment for potential confounders (OR 0.54, 95% CI 0.29–0.99, p = 0.04). Risk of HT decreased stepwise with higher serum albumin tertile (p for trend = 0.04). There was a significant interaction between serum albumin and age (p = 0.02), with no significant correlation between serum albumin and HT in patients over 60 years of age. Conclusions: Higher serum albumin is associated with lower HT risk in a dose-dependent manner in AIS patients younger than 60 years.

scholarly journals Syrian mothers, why to accept or to refuse HPV vaccine for their teen girls

2018 ◽  
Vol 1 (1) ◽  
pp. 7-13
Author(s):  
Mohammed Al Saad ◽  
Saad Ahmed Ali Jadoo
Keyword(s):  
Logistic Regression ◽  
Regression Analysis ◽  
Logistic Regression Analysis ◽  
Hpv Vaccine ◽  
Multiple Logistic Regression Analysis ◽  
Univariate Analysis ◽  
Cluster Sampling ◽  
Cross Sectional Survey ◽  
Cross Sectional ◽  
Gynecological Examination

Background: Cervical cancer (CC) ranks the eighth most frequent cancer among Syrian women with crude incidence rates 1.4 per 100, 000 populations per year. This study aimed to test the acceptance of the human papillomavirus (HPV) vaccine among mothers of schoolgirls in sixth-grade class. Methods: A cross-sectional survey was conducted through a structured and self-administrated questionnaire. A total of 400 Syrian mothers of schoolgirls were selected randomly by the cluster sampling method in Aleppo city, Syria, in 2011. Significant variables from univariate analysis were included in an enter technique multiple logistic regression analysis. Results: The response rate was 86%. If the vaccine was free, 282 (81.7%) mothers would accept the vaccine for themselves and 236 (68.4%) for their daughters, respectively. However, the acceptance rate grossly decreased to 24.6% and 15.1%, respectively, if the vaccine was not provided free. The high cost of the HPV vaccine and lack of knowledge were the significant barriers for mothers' acceptance of the HPV vaccine. Protection of daughters and the trust with health authority were the main encouraging reasons to accept the HPV vaccine. Findings from logistic regression analysis revealed that the employed mothers (odds ratio = 2.4; 95% CI: 1.3–4.4), with a positive history of gynecological examination (OR = 2.1; 95% CI: 1.6–2.9) and having sound knowledge (OR = 2.4; 95% CI: 1.0–5.7) are independent factors related to the acceptance of the HPV vaccine for their daughters. Conclusion: The results from this study suggest that mothers from different cultural backgrounds, including Syrian mothers, are holding different beliefs on privacy and health that may affect their willingness to accept the HPV vaccine.

scholarly journals Complications as important predictors of disability in ischemic stroke

2017 ◽  
Vol 36 (3) ◽  
pp. 197
Author(s):  
Rizaldy Taslim Pinzon ◽  
Rosa De Lima Renita Sanyasi
Keyword(s):  
Logistic Regression ◽  
Regression Analysis ◽  
Ischemic Stroke ◽  
Logistic Regression Analysis ◽  
Predictive Factors ◽  
Recurrent Stroke ◽  
Multiple Logistic Regression Analysis ◽  
Multiple Logistic Regression ◽  
Cross Sectional ◽  
Stroke Registry

Background<br />Stroke is the main cause of disability and death in many countries. The high incidence of disability in stroke survivors requires special attention to determine various predictive factors of disability. This study aimed to identify the various predictive factors of disability in ischemic stroke.<br /><br />Methods<br />This study was a cross sectional study on 4510 ischemic stroke patients. Each patient’s data had been recorded in the electronic stroke registry of Bethesda Hospital. Ischemic stroke diagnosis was confirmed by brain CT scan, which was interpreted by a neurologist and a radiologist. Disability was assessed using the modified Rankin scale. Predictors of disability were assessed. Multiple logistic regression analysis was used to analyse the data. <br /><br />Results<br />The subjects were predominantly males, &gt;60 years of age, and suffered stroke for the first time. The incidence of disability was 31.5% (1420/4510). Multiple logistic regression analysis showed that the presence of complications (OR: 6.43; 95% CI: 4.74-8.73; p&lt;0.001), decreased level of consciousness (OR: 4.82; 95% CI: 3.95-5.90; p &lt;0.001), onset ³3 hours (OR: 1.93; 95% CI: 1.52-2.45; p&lt;0.001), recurrent stroke (OR: 1.63; 95% CI: 1.39-1.90; p&lt;0.001), and age &gt;60 years (OR: 1.55; 95% CI: 1.35-1.79; p&lt;0.001) were independent predictive factors of disability.<br /><br />Conclusion<br />We demonstrated that a substantial proportion of patients with ischemic stroke become disabled. And the presence of complications was the most predictive factor of disability in ischemic stroke.

scholarly journals Predictive Value of the Alberta Stroke Program Early CT Score (ASPECTS) in the Outcome of the Acute Ischemic Stroke and Its Correlation with Stroke Subtypes, NIHSS, and Cognitive Impairment

2021 ◽  
Vol 2021 ◽  
pp. 1-10
Author(s):  
Ahmed Esmael ◽  
Mohammed Elsherief ◽  
Khaled Eltoukhy
Keyword(s):  
Logistic Regression ◽  
Regression Analysis ◽  
Ischemic Stroke ◽  
Middle Cerebral Artery ◽  
Acute Ischemic Stroke ◽  
Logistic Regression Analysis ◽  
Middle Cerebral Artery Territory ◽  
Spearman Correlation ◽  
Cutoff Value

Objectives. This study is aimed at correlating ASPECTS with mortality and morbidity in patients with acute middle cerebral artery territory infarction and at determining the cutoff value of ASPECTS that may predict the outcome. Methods. 150 patients diagnosed with acute middle cerebral artery territory infarction were involved in this study. Risk factors, initial NIHSS, and GCS were determined. An initial or follow-up noncontrast CT brain was done and assessed by ASPECTS. Outcomes were determined by mRS during the follow-up of cases after 3 months. Correlations of ASPECTS and outcome variables were done by Spearman correlation. Logistic regression analysis and ROC curve were done to detect the cutoff value of ASPECTS that predicts unfavorable outcomes. Results. The most common subtypes of ischemic strokes were lacunar stroke in 66 patients (44%), cardioembolic stroke in 39 patients (26%), and LAA stroke in 30 cases (20%). The cardioembolic stroke had a statistically significant lower ASPECT score than other types of ischemic strokes ( P < 0.05 ). Spearman correlation showed that lower ASPECTS values (worse outcome) were more in older patients and associated with lower initial GCS. ASPECTS values were inversely correlated with initial NIHSS, inpatient stay, inpatient complications, mortality, and mRS. The ASPECTS cutoff value determined for the prediction of unfavorable outcomes was equal to ≤7. The binary logistic regression analysis detected that patients with ASPECTS ≤ 7 were significantly associated with about fourfold increased risk of poor outcomes (OR 3.95, 95% CI 2.09–11.38, and P < 0.01 ). Conclusions. ASPECTS is a valuable and appropriate technique for the evaluation of the prognosis in acute ischemic stroke. Patients with high ASPECTS values are more likely to attain favorable outcomes, and the cutoff value of ASPECTS is a strong predictor for unfavorable outcomes. This trial is registered with ClinicalTrials.gov NCT04235920.

scholarly journals Development and validation of a model to estimate the risk of acute ischemic stroke in geriatric patients with primary hypertension

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Xifeng Zheng ◽  
Fang Fang ◽  
Weidong Nong ◽  
Dehui Feng ◽  
Yu Yang
Keyword(s):  
Logistic Regression ◽  
Regression Analysis ◽  
Ischemic Stroke ◽  
Prediction Model ◽  
Acute Ischemic Stroke ◽  
Logistic Regression Analysis ◽  
Geriatric Patients ◽  
Primary Hypertension ◽  
Multivariable Logistic Regression Analysis ◽  
Training Set

Abstract Objectives This study aimed to construct and validate a prediction model of acute ischemic stroke in geriatric patients with primary hypertension. Methods This retrospective file review collected information on 1367 geriatric patients diagnosed with primary hypertension and with and without acute ischemic stroke between October 2018 and May 2020. The study cohort was randomly divided into a training set and a testing set at a ratio of 70 to 30%. A total of 15 clinical indicators were assessed using the chi-square test and then multivariable logistic regression analysis to develop the prediction model. We employed the area under the curve (AUC) and calibration curves to assess the performance of the model and a nomogram for visualization. Internal verification by bootstrap resampling (1000 times) and external verification with the independent testing set determined the accuracy of the model. Finally, this model was compared with four machine learning algorithms to identify the most effective method for predicting the risk of stroke. Results The prediction model identified six variables (smoking, alcohol abuse, blood pressure management, stroke history, diabetes, and carotid artery stenosis). The AUC was 0.736 in the training set and 0.730 and 0.725 after resampling and in the external verification, respectively. The calibration curve illustrated a close overlap between the predicted and actual diagnosis of stroke in both the training set and testing validation. The multivariable logistic regression analysis and support vector machine with radial basis function kernel were the best models with an AUC of 0.710. Conclusion The prediction model using multiple logistic regression analysis has considerable accuracy and can be visualized in a nomogram, which is convenient for its clinical application.

scholarly journals Deliberate employment of postoperative hypotension for brain arteriovenous malformation surgery and the incidence of delayed postoperative hemorrhage: a prospective cohort study

2017 ◽  
Vol 127 (5) ◽  
pp. 1025-1040 ◽  
Author(s):  
Michael Kerin Morgan ◽  
Markus Karl Hermann Wiedmann ◽  
Nazih N. A. Assaad ◽  
Michael J. A. Parr ◽  
Gillian Z. Heller
Keyword(s):  
Logistic Regression ◽  
Regression Analysis ◽  
Logistic Regression Analysis ◽  
Neurological Deficit ◽  
Multiple Logistic Regression Analysis ◽  
Postoperative Hemorrhage ◽  
Maximum Diameter ◽  
Multiple Logistic Regression ◽  
Arterial Blood ◽  
The Impact

OBJECTIVEThe aim of this study was to examine the impact of deliberate employment of postoperative hypotension on delayed postoperative hemorrhage (DPH) for all Spetzler-Ponce Class (SPC) C brain arteriovenous malformations (bAVMs) and SPC B bAVMs ≥ 3.5 cm in diameter (SPC B 3.5+).METHODSA protocol of deliberate employment of postoperative hypotension was introduced in June 1997 for all SPC C and SPC B 3.5+ bAVMs. The aim was to achieve a maximum mean arterial blood pressure (BP) ≤ 70 mm Hg (with cerebral perfusion pressure > 50 mm Hg) for a minimum of 7 days after resection of bAVMs (BP protocol). The authors compared patients who experienced DPH (defined as brain hemorrhage into the resection bed that resulted in a new neurological deficit or that resulted in reoperation during the hospitalization for microsurgical bAVM resection) between 2 periods (prior to adopting the BP protocol and after introduction of the BP protocol) and 4 bAVM categories (SPC A, SPC B 3.5− [that is, SPC B < 3.5 cm maximum diameter], SPC B 3.5+, and SPC C). Patients excluded from treatment by the BP protocol were managed in the intensive care unit to avoid moderate hypertensive episodes. The pooled cases of all bAVM treated by surgery were analyzed to identify characteristics associated with the risk of DPH. These identified characteristics were then examined by multiple logistic regression analysis in both SPC B 3.5+ and SPC C cases.RESULTSFrom a cohort of 641 bAVMs treated by microsurgery, 32 patients with DPH were identified. Of those, 66% (95% CI 48–80) had a permanent new neurological deficit with a modified Rankin Scale score of 2–6. This included a mortality rate of 13% (95% CI 4.4–29). The BP protocol was used to treat 162 patients with either SPC B 3.5+ or SPC C. For SPC B 3.5+, there was no significant reduction in DPH with the introduction of the BP protocol (p = 0.77). For SPC C, there was a significant (p = 0.035) reduction of DPH from 29% (95% CI 13%–53%) to 8.2% (95% CI 3.2%–18%) associated with the introduction of the BP protocol. Multiple logistic regression analysis found that the absence of the BP protocol (p = 0.011, odds ratio 7.5, 95% CI 1.6–36) remained significant for the development of DPH in patients with SPC C bAVMs.CONCLUSIONSTreating patients with SPC C bAVMs with a protocol that lowers BP immediately after resection seems to reduce the risk of DPH. For SPC A and SPC B 3.5− bAVMs, there is unlikely to be a need to do more than avoid postoperative hypertension. For SPC B 3.5+ bAVMs, a larger number of patients would be required to test the absence of benefit of the BP protocol.

scholarly journals Disparities in the Outcomes Following Ischemic Stroke Between the Floating Population and Indigenous Population of Shanghai

2021 ◽  
Vol 12 ◽  
Author(s):  
Xiaochuan Liu ◽  
Qian Sun ◽  
Sichen Yao ◽  
Junhui Zhang ◽  
Huanyin Li
Keyword(s):  
Logistic Regression ◽  
Regression Analysis ◽  
Ischemic Stroke ◽  
Acute Ischemic Stroke ◽  
Logistic Regression Analysis ◽  
Endovascular Therapy ◽  
Indigenous Population ◽  
Arrival Rate ◽  
Floating Population ◽  
Indigenous Populations

Background and Purposes: Through this study, we hope to gain more insights into the differences in outcome following an ischemic stroke between the floating population and the indigenous population of Shanghai.Method: In this retrospective cohort study, we analyzed patients with first-ever acute ischemic stroke who were admitted to a comprehensive stroke center in the Minhang district, Shanghai, from January 1, 2019, to December 31, 2020. All patient's demographic data and medical histories were prospectively collected and they were followed up for at least 3 months. The Indigenous population of Shanghai was defined as patients with an identification number starting with 310. All others were treated as floating population. The primary outcome was defined as an unfavorable prognosis at 3 months, with a modified Rankin Scale (mRS) score above 1. Secondary outcomes included the use of emergency medical service (EMS), 3 h arrival rate, and endovascular therapy in eligible patients. Logistic regression analysis was applied to investigate the differences.Results: Finally, 698 patients with first-ever acute ischemic stroke were included (with mean age of 65.32 years, 74.6% men). Of these, 302 patients belonged to the floating population group. Indigenous populations with ischemic stroke were older than the floating population (68.26 years vs. 61.47 years, P &lt; 0.001). The floating population was more likely to achieve favorable outcomes at 3 months compared with the indigenous population in multivariable logistic regression analysis [Odds ratio (OR): 0.49, 95% CI: 0.32–0.75, P = 0.001]. The use of EMS, 3 h arrival rate, and the application of endovascular therapy were comparable between the floating population and indigenous population (OR: 0.89, 95% CI: 0.62–1.27, P = 0.519; OR: 0.78, 95% CI: 0.56–1.09, P = 0.14; and OR: 0.82, 95% CI: 0.54–1.26, P = 0.365, respectively).Conclusion: Compared with the indigenous population, the floating population with the first-ever ischemic stroke was more likely to have a favorable outcome at 3 months.

scholarly journals Relationship between admission coagulopathy and prognosis in children with traumatic brain injury: a retrospective study

2021 ◽  
Vol 29 (1) ◽  
Author(s):  
Cheng-yan You ◽  
Si-wei Lu ◽  
Yue-qiang Fu ◽  
Feng Xu
Keyword(s):  
Traumatic Brain Injury ◽  
Logistic Regression ◽  
Regression Analysis ◽  
Brain Injury ◽  
Logistic Regression Analysis ◽  
Multiple Logistic Regression Analysis ◽  
Cart Analysis ◽  
Severe Tbi ◽  
Pediatric Tbi ◽  
The Impact

Abstract Background Coagulopathy in adult patients with traumatic brain injury (TBI) is strongly associated with unfavorable outcomes. However, few reports focus on pediatric TBI-associated coagulopathy. Methods We retrospectively identified children with Glasgow Coma Scale ≤ 13 in a tertiary pediatric hospital from April 2012 to December 2019 to evaluate the impact of admission coagulopathy on their prognosis. A classification and regression tree (CART) analysis using coagulation parameters was performed to stratify the death risk among patients. The importance of these parameters was examined by multivariate logistic regression analysis. Results A total of 281 children with moderate to severe TBI were enrolled. A receiver operating characteristic curve showed that activated partial thromboplastin time (APTT) and fibrinogen were effective predictors of in-hospital mortality. According to the CART analysis, APTT of 39.2 s was identified as the best discriminator, while 120 mg/dL fibrinogen was the second split in the subgroup of APTT ≤ 39.2 s. Patients were stratified into three groups, in which mortality was as follows: 4.5 % (APTT ≤ 39.2 s, fibrinogen > 120 mg/dL), 20.5 % (APTT ≤ 39.2 s and fibrinogen ≤ 120 mg/dL) and 60.8 % (APTT > 39.2 s). Furthermore, length-of-stay in the ICU and duration of mechanical ventilation were significantly prolonged in patients with deteriorated APTT or fibrinogen values. Multiple logistic regression analysis showed that APTT > 39.2 s and fibrinogen ≤ 120 mg/dL was independently associated with mortality in children with moderate to severe TBI. Conclusions We concluded that admission APTT > 39.2 s and fibrinogen ≤ 120 mg/dL were independently associated with mortality in children with moderate to severe TBI. Early identification and intervention of abnormal APTT and fibrinogen in pediatric TBI patients may be beneficial to their prognosis.

scholarly journals Early prediction of the 3-month outcome for individual acute ischemic stroke patients who received intravenous thrombolysis using the N2H3 nomogram model

2020 ◽  
Vol 13 ◽  
pp. 175628642095305
Author(s):  
Shan Lv ◽  
Yu Song ◽  
Fu-Liang Zhang ◽  
Xiu-Li Yan ◽  
Jie Chen ◽  
...  
Keyword(s):  
Logistic Regression ◽  
Regression Analysis ◽  
Ischemic Stroke ◽  
Acute Ischemic Stroke ◽  
Logistic Regression Analysis ◽  
Density Lipoprotein ◽  
Unfavorable Outcome ◽  
Early Prediction ◽  
Training Cohort ◽  
Nihss Score

Background: The aim of this study was to establish a nomogram model for individualized early prediction of the 3-month prognosis in patients with acute ischemic stroke (AIS) who were treated with intravenous recombinant tissue plasminogen activator (rt-PA) thrombolysis. Methods: A total of 691 patients were included in this study; 564 patients were included in the training cohort, while 127 patients were included in the test cohort. The main outcome measure was a 3-month unfavorable outcome (modified Rankin Scale 3–6). To construct the nomogram model, stepwise logistic regression analysis was applied to select the significant predictors of the outcome. The discriminative performance of the model was assessed by calculating the area under the receiver operating characteristic curve (AUC-ROC). A decision curve analysis was used to evaluate prognostic value of the model. Results: The initial National Institutes of Health Stroke Scale [NIHSS, odds ratio (OR), 1.35; 95% confidence interval (CI), 1.28–1.44; p < 0.001], delta NIHSS (changes in the NIHSS score from baseline to 24 h, OR, 0.75; 95% CI, 0.70–0.79; p < 0.001), hypertension (OR, 2.07; 95% CI, 1.32–3.31; p = 0.002), hyperhomocysteinemia (Hhcy, OR, 2.18; 95% CI, 1.20–4.11; p = 0.013), and the ratio of high-density lipoprotein cholesterol (HDL-C) to low-density lipoprotein cholesterol (LDL-C) (HDL-C/LDL-C, OR, 3.29; 95% CI, 1.00–10.89; p = 0.049) (N2H3) were found to be independent predictors of a 3-month unfavorable outcome from multivariate logistic regression analysis and were incorporated in the N2H3 nomogram model. The AUC-ROC of the training cohort was 0.872 (95% CI, 0.841–0.902), and the AUC-ROC of the test cohort was 0.900 (95% CI, 0.848–0.953). Conclusion: The study presented the N2H3 nomogram model, with initial NIHSS score, delta NIHSS, hypertension, Hhcy, and HDL-C/LDL-C as predictors. It therefore provides an individualized early prediction of the 3-month unfavorable outcome in AIS patients treated with intravenous rt-PA thrombolysis.

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