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A NADE nomogram to predict the probability of 6-month unfavorable outcome in Chinese patients with ischemic stroke.

ABSTRACT: 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.

SUBMITTER: Sun C

PROVIDER: S-EPMC6839074 | biostudies-literature | 2019 Nov

REPOSITORIES: biostudies-literature

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A NADE nomogram to predict the probability of 6-month unfavorable outcome in Chinese patients with ischemic stroke.

Sun Chao C Li Xiang X Song Baili B Chen Xiangliang X Nyame Linda L Liu Yukai Y Tang Dan D Ibrahim Mako M Zhao Zheng Z Liu Chao C Yan Miao M Pan Xiding X Yang Jie J Zhou Junshan J Zou Jianjun J

BMC neurology 20191107 1

<h4>Background</h4>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 fou ...[more]

PMID: 31699038

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Project description:BackgroundHemorrhagic transformation (HT) is the most serious complication of ischemic stroke patients after intravenous thrombolysis and leads to a poor clinical prognosis. This study aimed to determine the independent predictors associated with HT in stroke patients with intravenous thrombolysis and to establish and validate a nomogram that combines with predictors to predict the probability of HT after intravenous thrombolysis in patients with ischemic stroke.MethodThis study enrolled ischemic stroke patients with intravenous thrombolysis from December 2016 to June 2022. All the patients were divided into training and validation cohorts. The nomogram was composed of the significant predictors for HT in the training cohort as obtained by the multivariate logistic regression analysis. The area under the receiver operating characteristic curve was used to assess the discriminative performance of the nomogram. The calibration performance of the nomogram was assessed by the Hosmer-Lemeshow goodness-of-fit test and calibration plots. Decision curve analysis was used to test the clinical validity of the nomogram.ResultsA total of 394 patients with intravenous thrombolysis were enrolled in the study. In the training cohort (n = 257), 45 patients had HT after intravenous thrombolysis. Multivariate logistic regression analysis demonstrated early infarct signs (OR, 7.954; 95% CI, 3.553-17.803; P < 0.001), NIHSS scores (OR, 1.110; 95% CI, 1.054-1.168; P < 0.001), uric acid (OR, 0.993; 95% CI, 0.989-0.997; P = 0.001), and albumin-to-globulin ratio (OR, 0.109; 95% CI, 0.023-0.508; P = 0.005) were independent predictors for HT and constructed the nomogram. In the training and validation cohorts, the AUC of the nomogram was 0.859 and 0.839, respectively. The Hosmer-Lemeshow goodness-of-fit test and calibration plot showed good concordance between predicted and observed probability in the training and validation cohorts. Decision curve analysis indicated that the nomogram was significantly useful for predicting HT in the training and further confirmed in the validation cohort.ConclusionThis study proposes a novel and practical nomogram based on early infarct signs, NIHSS scores, uric acid, and albumin-to-globulin ratio that can well predict the probability of HT after intravenous thrombolysis in patients with ischemic stroke.

Project description:IntroductionStroke remains a leading cause of death and disability worldwide. Effective and prompt prognostic evaluation is vital for determining the appropriate management strategy. Radiomics is an emerging noninvasive method used to identify the quantitative imaging indicators for predicting important clinical outcomes. This study was conducted to investigate and validate a radiomics nomogram for predicting ischemic stroke prognosis using the modified Rankin scale (mRS).MethodsA total of 598 consecutive patients with subacute infarction confirmed by diffusion-weighted imaging (DWI), from January 2018 to December 2019, were retrospectively assessed. They were assigned to the good (mRS ≤ 2) and poor (mRS > 2) functional outcome groups, respectively. Then, 399 patients examined by MR scanner 1 and 199 patients scanned by MR scanner 2 were assigned to the training and validation cohorts, respectively. Infarction lesions underwent manual segmentation on DWI, extracting 402 radiomic features. A radiomics nomogram encompassing patient characteristics and the radiomics signature was built using a multivariate logistic regression model. The performance of the nomogram was evaluated in the training and validation cohorts. Ultimately, decision curve analysis was implemented to assess the clinical value of the nomogram. The performance of infarction lesion volume was also evaluated using univariate analysis.ResultsStroke lesion volume showed moderate performance, with an area under the curve (AUC) of 0.678. The radiomics signature, including 11 radiomics features, exhibited good prediction performance. The radiomics nomogram, encompassing clinical characteristics (age, hemorrhage, and 24 h National Institutes of Health Stroke Scale score) and the radiomics signature, presented good discriminatory potential in the training cohort [AUC = 0.80; 95% confidence interval (CI) 0.75-0.86], which was validated in the validation cohort (AUC = 0.73; 95% CI 0.63-0.82). In addition, it demonstrated good calibration in the training (p = 0.55) and validation (p = 0.21) cohorts. Decision curve analysis confirmed the clinical value of this nomogram.ConclusionThis novel noninvasive clinical-radiomics nomogram shows good performance in predicting ischemic stroke prognosis.

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A NADE nomogram to predict the probability of 6-month unfavorable outcome in Chinese patients with ischemic stroke.

Publications

A NADE nomogram to predict the probability of 6-month unfavorable outcome in Chinese patients with ischemic stroke.

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