Dataset Information

A SCANO Nomogram for Individualized Prediction of the Probability of 1-Year Unfavorable Outcomes in Chinese Acute Ischemic Stroke Patients.

ABSTRACT: Background and Purpose: Accurate prediction of functional outcomes after stroke would provide evidence for reasonable poststroke management. This study aimed to develop and validate a nomogram for individualized prediction of 1-year unfavorable outcomes in Chinese acute ischemic stroke (AIS) patients. Methods: We gathered AIS patients at the National Advanced Stroke Center of Nanjing First Hospital (China) between August 2014 and May 2017 within 12 h of symptom onset. The outcome measure was 1-year unfavorable outcomes (modified Rankin Scale 3-6). The patients were randomly stratified into the training (66.7%) and testing (33.3%) sets. With the training data, pre-established predictors were entered into a logistic regression model to generate the nomogram. Predictive performance of the nomogram model was evaluated in the testing data by calculating the area under the receiver operating characteristic curve (AUC-ROC), Brier score, and a calibration plot. Results: A total of 807 patients were included into this study, and 262 (32.5%) of them had unfavorable outcomes. Systolic blood pressure, Creatinine, Age, National Institutes of Health Stroke Scale (NIHSS) score on admission, and fasting blood glucose were significantly associated with unfavorable outcomes and entered into the SCANO nomogram. The AUC-ROC of the SCANO nomogram in the testing set was 0.781 (Brier score: 0.166; calibration slope: 0.936; calibration intercept: 0.060). Conclusions: The SCANO nomogram is developed and validated in Chinese AIS patients to firstly predict 1-year unfavorable outcomes, which is simple and convenient for the management of stroke patients.

SUBMITTER: Li X

PROVIDER: S-EPMC7338753 | biostudies-literature | 2020

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

A SCANO Nomogram for Individualized Prediction of the Probability of 1-Year Unfavorable Outcomes in Chinese Acute Ischemic Stroke Patients.

Li Xiang X Wang Fusang F Zhao Zhihong Z Sun Chao C Liao Jun J Li Xuemei X Huang Chaoping C Nyame Linda L Zhao Zheng Z Zheng Xiaohan X Zhou Junshan J Li Ming M Zou Jianjun J

Frontiers in neurology 20200630

<b>Background and Purpose:</b> Accurate prediction of functional outcomes after stroke would provide evidence for reasonable poststroke management. This study aimed to develop and validate a nomogram for individualized prediction of 1-year unfavorable outcomes in Chinese acute ischemic stroke (AIS) patients. <b>Methods:</b> We gathered AIS patients at the National Advanced Stroke Center of Nanjing First Hospital (China) between August 2014 and May 2017 within 12 h of symptom onset. The outcome m ...[more]

PMID: 32695060

Similar Datasets

Project description:BACKGROUND:Early prediction of unfavorable outcome after ischemic stroke is of great significance to the clinical and therapeutic management. A nomogram is a better visual tool than earlier models and prognostic scores to predict clinical outcomes, which incorporates different factors to develop a graphic continuous scoring system and calculates accurately the risk probability of poor outcome entirely based on individual characteristics. However, to date, no nomogram models have been found to predict the probability of 6-month poor outcome after ischemic stroke. We aimed to develop and validate a nomogram for individualized prediction of the probability of 6-month unfavorable outcome in Chinese patients with ischemic stroke. METHODS:Based on the retrospective stroke registry, a single-center study which included 499 patients from May, 2013 to May, 2018 was conducted in Nanjing First Hospital (China) for ischemic stroke within 12?h of symptoms onset. The main outcome measure was 6-month unfavorable outcome (mRS?>?2). To generate the nomogram, NIHSS score on admission, Age, previous Diabetes mellitus and crEatinine (NADE) were integrated into the model. We assessed the discriminative performance by using the area under the curve (AUC) of receiver-operating characteristic (ROC) and calibration of risk prediction model by using the Hosmer-Lemeshow test. RESULTS:A visual NADE nomogram was constructed that NIHSS score on admission (OR: 1.190, 95%CI: 1.125-1.258), age (OR: 1.068, 95%CI: 1.045-1.090), previous diabetes mellitus (OR: 1.995, 95%CI: 1.236-3.221) and creatinine (OR: 1.010, 95%CI: 1.002-1.018) were found to be significant predictors of 6-month unfavorable outcome after acute ischemic stroke in Chinese patients. The AUC-ROC of nomogram was 0.791. Calibration was good (p?=?0.4982 for the Hosmer-Lemeshow test). CONCLUSION:The NADE is the first nomogram developed and validated in Chinese ischemic stroke patients to provide an individual, visual and precise prediction of the risk probability of 6-month unfavorable outcome.

Project description:BACKGROUND:A reliable scoring tool to detect the risk of intracerebral hemorrhage (ICH) after intravenous thrombolysis for ischemic stroke is warranted. The present study was designed to develop and validate a new nomogram for individualized prediction of the probability of hemorrhagic transformation (HT) in patients treated with intravenous (IV) recombinant tissue plasminogen activator (rt-PA). METHODS:We enrolled patients who suffered from acute ischemic stroke (AIS) with IV rt-PA treatment in our emergency green channel between August 2016 and July 2018. The main outcome was defined as any type of intracerebral hemorrhage according to the European Cooperative Acute Stroke Study II (ECASS II). All patients were randomly divided into two cohorts: the primary cohort and the validation cohort. On the basis of multivariate logistic model, the predictive nomogram was generated. The performance of the nomogram was evaluated by Harrell's concordance index (C-index) and calibration plot. RESULTS:A total of 194 patients with complete data were enrolled, of whom 131 comprised the primary cohort and 63 comprised the validation cohort, with HT rate 12.2, 9.5% respectively. The score of chronic disease scale (CDS), the global burden of cerebral small vascular disease (CSVD), National Institutes of Health Stroke Scale (NIHSS) score???13, and onset-to-treatment time (OTT)???180 were detected important determinants of ICH and included to construct the nomogram. The nomogram derived from the primary cohort for HT had C- Statistics of 0.9562 and the calibration plot revealed generally fit in predicting the risk of HT. Furthermore, we made a comparison between our new nomogram and several other risk-assessed scales for HT with receiver operating characteristic (ROC) curve analysis, and the results showed the nomogram model gave an area under curve of 0.9562 (95%CI, 0.9221-0.9904, P?<?0.01) greater than HAT (Hemorrhage After Thrombolysis), SEDAN (blood Sugar, Early infarct and hyper Dense cerebral artery sign on non-contrast computed tomography, Age, and NIHSS) and SPAN-100 (Stroke Prognostication using Age and NIHSS) scores. CONCLUSIONS:This proposed nomogram based on the score of CDS, the global burden of CSVD, NIHSS score???13, and OTT???180 gives rise to a more accurate and more comprehensive prediction for HT in patients with ischemic stroke receiving IV rt-PA treatment.

Project description:ObjectiveWe compared the accuracy of clinicians and a risk score (iScore) to predict observed outcomes following an acute ischemic stroke.MethodsThe JURaSSiC (Clinician JUdgment vs Risk Score to predict Stroke outComes) study assigned 111 clinicians with expertise in acute stroke care to predict the probability of outcomes of 5 ischemic stroke case scenarios. Cases (n = 1,415) were selected as being representative of the 10 most common clinical presentations from a pool of more than 12,000 stroke patients admitted to 12 stroke centers. The primary outcome was prediction of death or disability (modified Rankin Scale [mRS] ≥3) at discharge within the 95% confidence interval (CI) of observed outcomes. Secondary outcomes included 30-day mortality and death or institutionalization at discharge.ResultsClinicians made 1,661 predictions with overall accuracy of 16.9% for death or disability at discharge, 46.9% for 30-day mortality, and 33.1% for death or institutionalization at discharge. In contrast, 90% of the iScore-based estimates were within the 95% CI of observed outcomes. Nearly half (n = 53 of 111; 48%) of participants were unable to accurately predict the probability of the primary outcome in any of the 5 rated cases. Less than 1% (n = 1) provided accurate predictions in 4 of the 5 cases and none accurately predicted all 5 case outcomes. In multivariable analyses, the presence of patient characteristics associated with poor outcomes (mRS ≥3 or death) in previous studies (older age, high NIH Stroke Scale score, and nonlacunar subtype) were associated with more accurate clinician predictions of death at 30 days (odds ratio [OR] 2.40, 95% CI 1.57-3.67) and with a trend for more accurate predictions of death or disability at discharge (OR 1.85, 95% CI 0.99-3.46).ConclusionsClinicians with expertise in stroke performed poorly compared to a validated tool in predicting the outcomes of patients with an acute ischemic stroke. Use of the risk stroke outcome tool may be superior for decision-making following an acute ischemic stroke.

Dataset Information

A SCANO Nomogram for Individualized Prediction of the Probability of 1-Year Unfavorable Outcomes in Chinese Acute Ischemic Stroke Patients.

Publications

A SCANO Nomogram for Individualized Prediction of the Probability of 1-Year Unfavorable Outcomes in Chinese Acute Ischemic Stroke Patients.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets