author_facet Gong, P.
Zhang, X.
Gong, Y.
Liu, Y.
Wang, S.
Li, Z.
Chen, W.
Zhou, F.
Zhou, J.
Jiang, T.
Zhang, Y.
Gong, P.
Zhang, X.
Gong, Y.
Liu, Y.
Wang, S.
Li, Z.
Chen, W.
Zhou, F.
Zhou, J.
Jiang, T.
Zhang, Y.
author Gong, P.
Zhang, X.
Gong, Y.
Liu, Y.
Wang, S.
Li, Z.
Chen, W.
Zhou, F.
Zhou, J.
Jiang, T.
Zhang, Y.
spellingShingle Gong, P.
Zhang, X.
Gong, Y.
Liu, Y.
Wang, S.
Li, Z.
Chen, W.
Zhou, F.
Zhou, J.
Jiang, T.
Zhang, Y.
European Journal of Neurology
A novel nomogram to predict early neurological deterioration in patients with acute ischaemic stroke
Neurology (clinical)
Neurology
author_sort gong, p.
spelling Gong, P. Zhang, X. Gong, Y. Liu, Y. Wang, S. Li, Z. Chen, W. Zhou, F. Zhou, J. Jiang, T. Zhang, Y. 1351-5101 1468-1331 Wiley Neurology (clinical) Neurology http://dx.doi.org/10.1111/ene.14333 <jats:sec><jats:title>Background and purpose</jats:title><jats:p>Acute ischaemic stroke (AIS) is a vital cause of mortality and morbidity in China. Many AIS patients develop early neurological deterioration (END). This study aimed to construct a nomogram to predict END in AIS patients.</jats:p></jats:sec><jats:sec><jats:title>Methods</jats:title><jats:p>Acute ischaemic stroke patients in Nanjing First Hospital were recruited as the training cohort. Additional patients in Nantong Third People’s Hospital were enrolled as the validation cohort. Multivariate logistic regression was utilized to establish the nomogram. Discrimination and calibration performance of the nomogram were tested by concordance index and calibration plots. Decision curve analysis was employed to assess the utility of the nomogram.</jats:p></jats:sec><jats:sec><jats:title>Results</jats:title><jats:p>In all, 1889 and 818 patients were recruited in the training and validation cohorts, respectively. Age [odds ratio (OR) 1.075; 95% confidence interval (CI) 1.059–1.091], diabetes mellitus (OR 1.673; 95% CI 1.181–2.370), atrial fibrillation (OR 3.297; 95% CI 2.005–5.421), previous antiplatelet medication (OR 0.473; 95% CI 0.301–0.744), hyper‐sensitive C‐reactive protein (OR 1.049; 95% CI 1.036–1.063) and baseline National Institutes of Health Stroke Scale (OR 1.071; 95% CI 1.045–1.098) were associated with END and incorporated in the nomogram. The concordance index was 0.826 (95% CI 0.785–0.885) and 0.798 (95% CI 0.749–0.847) in the training and validation cohorts. By decision curve analysis, the model was relevant between thresholds of 0.06 and 0.90 in the training cohort and 0.08 and 0.77 in the validation cohort.</jats:p></jats:sec><jats:sec><jats:title>Conclusions</jats:title><jats:p>The nomogram composed of hyper‐sensitive C‐reactive protein, age, diabetes mellitus, atrial fibrillation, previous antiplatelet medication and baseline National Institutes of Health Stroke Scale may predict the risk of END in AIS patients.</jats:p></jats:sec> A novel nomogram to predict early neurological deterioration in patients with acute ischaemic stroke European Journal of Neurology
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series European Journal of Neurology
source_id 49
title A novel nomogram to predict early neurological deterioration in patients with acute ischaemic stroke
title_unstemmed A novel nomogram to predict early neurological deterioration in patients with acute ischaemic stroke
title_full A novel nomogram to predict early neurological deterioration in patients with acute ischaemic stroke
title_fullStr A novel nomogram to predict early neurological deterioration in patients with acute ischaemic stroke
title_full_unstemmed A novel nomogram to predict early neurological deterioration in patients with acute ischaemic stroke
title_short A novel nomogram to predict early neurological deterioration in patients with acute ischaemic stroke
title_sort a novel nomogram to predict early neurological deterioration in patients with acute ischaemic stroke
topic Neurology (clinical)
Neurology
url http://dx.doi.org/10.1111/ene.14333
publishDate 2020
physical 1996-2005
description <jats:sec><jats:title>Background and purpose</jats:title><jats:p>Acute ischaemic stroke (AIS) is a vital cause of mortality and morbidity in China. Many AIS patients develop early neurological deterioration (END). This study aimed to construct a nomogram to predict END in AIS patients.</jats:p></jats:sec><jats:sec><jats:title>Methods</jats:title><jats:p>Acute ischaemic stroke patients in Nanjing First Hospital were recruited as the training cohort. Additional patients in Nantong Third People’s Hospital were enrolled as the validation cohort. Multivariate logistic regression was utilized to establish the nomogram. Discrimination and calibration performance of the nomogram were tested by concordance index and calibration plots. Decision curve analysis was employed to assess the utility of the nomogram.</jats:p></jats:sec><jats:sec><jats:title>Results</jats:title><jats:p>In all, 1889 and 818 patients were recruited in the training and validation cohorts, respectively. Age [odds ratio (OR) 1.075; 95% confidence interval (CI) 1.059–1.091], diabetes mellitus (OR 1.673; 95% CI 1.181–2.370), atrial fibrillation (OR 3.297; 95% CI 2.005–5.421), previous antiplatelet medication (OR 0.473; 95% CI 0.301–0.744), hyper‐sensitive C‐reactive protein (OR 1.049; 95% CI 1.036–1.063) and baseline National Institutes of Health Stroke Scale (OR 1.071; 95% CI 1.045–1.098) were associated with END and incorporated in the nomogram. The concordance index was 0.826 (95% CI 0.785–0.885) and 0.798 (95% CI 0.749–0.847) in the training and validation cohorts. By decision curve analysis, the model was relevant between thresholds of 0.06 and 0.90 in the training cohort and 0.08 and 0.77 in the validation cohort.</jats:p></jats:sec><jats:sec><jats:title>Conclusions</jats:title><jats:p>The nomogram composed of hyper‐sensitive C‐reactive protein, age, diabetes mellitus, atrial fibrillation, previous antiplatelet medication and baseline National Institutes of Health Stroke Scale may predict the risk of END in AIS patients.</jats:p></jats:sec>
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author Gong, P., Zhang, X., Gong, Y., Liu, Y., Wang, S., Li, Z., Chen, W., Zhou, F., Zhou, J., Jiang, T., Zhang, Y.
author_facet Gong, P., Zhang, X., Gong, Y., Liu, Y., Wang, S., Li, Z., Chen, W., Zhou, F., Zhou, J., Jiang, T., Zhang, Y., Gong, P., Zhang, X., Gong, Y., Liu, Y., Wang, S., Li, Z., Chen, W., Zhou, F., Zhou, J., Jiang, T., Zhang, Y.
author_sort gong, p.
container_issue 10
container_start_page 1996
container_title European Journal of Neurology
container_volume 27
description <jats:sec><jats:title>Background and purpose</jats:title><jats:p>Acute ischaemic stroke (AIS) is a vital cause of mortality and morbidity in China. Many AIS patients develop early neurological deterioration (END). This study aimed to construct a nomogram to predict END in AIS patients.</jats:p></jats:sec><jats:sec><jats:title>Methods</jats:title><jats:p>Acute ischaemic stroke patients in Nanjing First Hospital were recruited as the training cohort. Additional patients in Nantong Third People’s Hospital were enrolled as the validation cohort. Multivariate logistic regression was utilized to establish the nomogram. Discrimination and calibration performance of the nomogram were tested by concordance index and calibration plots. Decision curve analysis was employed to assess the utility of the nomogram.</jats:p></jats:sec><jats:sec><jats:title>Results</jats:title><jats:p>In all, 1889 and 818 patients were recruited in the training and validation cohorts, respectively. Age [odds ratio (OR) 1.075; 95% confidence interval (CI) 1.059–1.091], diabetes mellitus (OR 1.673; 95% CI 1.181–2.370), atrial fibrillation (OR 3.297; 95% CI 2.005–5.421), previous antiplatelet medication (OR 0.473; 95% CI 0.301–0.744), hyper‐sensitive C‐reactive protein (OR 1.049; 95% CI 1.036–1.063) and baseline National Institutes of Health Stroke Scale (OR 1.071; 95% CI 1.045–1.098) were associated with END and incorporated in the nomogram. The concordance index was 0.826 (95% CI 0.785–0.885) and 0.798 (95% CI 0.749–0.847) in the training and validation cohorts. By decision curve analysis, the model was relevant between thresholds of 0.06 and 0.90 in the training cohort and 0.08 and 0.77 in the validation cohort.</jats:p></jats:sec><jats:sec><jats:title>Conclusions</jats:title><jats:p>The nomogram composed of hyper‐sensitive C‐reactive protein, age, diabetes mellitus, atrial fibrillation, previous antiplatelet medication and baseline National Institutes of Health Stroke Scale may predict the risk of END in AIS patients.</jats:p></jats:sec>
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spelling Gong, P. Zhang, X. Gong, Y. Liu, Y. Wang, S. Li, Z. Chen, W. Zhou, F. Zhou, J. Jiang, T. Zhang, Y. 1351-5101 1468-1331 Wiley Neurology (clinical) Neurology http://dx.doi.org/10.1111/ene.14333 <jats:sec><jats:title>Background and purpose</jats:title><jats:p>Acute ischaemic stroke (AIS) is a vital cause of mortality and morbidity in China. Many AIS patients develop early neurological deterioration (END). This study aimed to construct a nomogram to predict END in AIS patients.</jats:p></jats:sec><jats:sec><jats:title>Methods</jats:title><jats:p>Acute ischaemic stroke patients in Nanjing First Hospital were recruited as the training cohort. Additional patients in Nantong Third People’s Hospital were enrolled as the validation cohort. Multivariate logistic regression was utilized to establish the nomogram. Discrimination and calibration performance of the nomogram were tested by concordance index and calibration plots. Decision curve analysis was employed to assess the utility of the nomogram.</jats:p></jats:sec><jats:sec><jats:title>Results</jats:title><jats:p>In all, 1889 and 818 patients were recruited in the training and validation cohorts, respectively. Age [odds ratio (OR) 1.075; 95% confidence interval (CI) 1.059–1.091], diabetes mellitus (OR 1.673; 95% CI 1.181–2.370), atrial fibrillation (OR 3.297; 95% CI 2.005–5.421), previous antiplatelet medication (OR 0.473; 95% CI 0.301–0.744), hyper‐sensitive C‐reactive protein (OR 1.049; 95% CI 1.036–1.063) and baseline National Institutes of Health Stroke Scale (OR 1.071; 95% CI 1.045–1.098) were associated with END and incorporated in the nomogram. The concordance index was 0.826 (95% CI 0.785–0.885) and 0.798 (95% CI 0.749–0.847) in the training and validation cohorts. By decision curve analysis, the model was relevant between thresholds of 0.06 and 0.90 in the training cohort and 0.08 and 0.77 in the validation cohort.</jats:p></jats:sec><jats:sec><jats:title>Conclusions</jats:title><jats:p>The nomogram composed of hyper‐sensitive C‐reactive protein, age, diabetes mellitus, atrial fibrillation, previous antiplatelet medication and baseline National Institutes of Health Stroke Scale may predict the risk of END in AIS patients.</jats:p></jats:sec> A novel nomogram to predict early neurological deterioration in patients with acute ischaemic stroke European Journal of Neurology
spellingShingle Gong, P., Zhang, X., Gong, Y., Liu, Y., Wang, S., Li, Z., Chen, W., Zhou, F., Zhou, J., Jiang, T., Zhang, Y., European Journal of Neurology, A novel nomogram to predict early neurological deterioration in patients with acute ischaemic stroke, Neurology (clinical), Neurology
title A novel nomogram to predict early neurological deterioration in patients with acute ischaemic stroke
title_full A novel nomogram to predict early neurological deterioration in patients with acute ischaemic stroke
title_fullStr A novel nomogram to predict early neurological deterioration in patients with acute ischaemic stroke
title_full_unstemmed A novel nomogram to predict early neurological deterioration in patients with acute ischaemic stroke
title_short A novel nomogram to predict early neurological deterioration in patients with acute ischaemic stroke
title_sort a novel nomogram to predict early neurological deterioration in patients with acute ischaemic stroke
title_unstemmed A novel nomogram to predict early neurological deterioration in patients with acute ischaemic stroke
topic Neurology (clinical), Neurology
url http://dx.doi.org/10.1111/ene.14333