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A New Nomogram Model for Individualized Prediction of Cognitive Impairment in Patients With Acute Ischemic Stroke

Volume 6, Issue 6, December 2021    |    PP. 433-447    |PDF (526 K)|    Pub. Date: October 7, 2021
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Author(s)
Anqi Tang, Department of Neurology, The First Affiliated Hospital of Soochow University, No.899 Pinghai Road, Suzhou, Jiangsu 215006, China
Sanjiao Liu, Department of Neurology, Xiangyang Central Hospital, Affiliated Hospital of Hubei University of Arts and Science, No. 136 Jingzhou Road, Xiangyang, Hubei 441000, China
Zhi Wang, Department of Neurology, The First Affiliated Hospital of Soochow University, No.899 Pinghai Road, Suzhou, Jiangsu 215006, China
Han Shao, Department of Neurology, The First Affiliated Hospital of Soochow University, No.899 Pinghai Road, Suzhou, Jiangsu 215006, China
Xiuying Cai, Department of Neurology, The First Affiliated Hospital of Soochow University, No.899 Pinghai Road, Suzhou, Jiangsu 215006, China
Tan Li, Department of Neurology, The First Affiliated Hospital of Soochow University, No.899 Pinghai Road, Suzhou, Jiangsu 215006, China

Abstract
Background: Cognitive impairment is common after ischemic stroke, which significantly affects patients’ quality of life and rehabilitation. A reliable scoring tool to detect the risk of cognitive impairment after stroke is imperative. The present study was designed to investigate the risk factors of cognitive impairment in the acute phase and to develop and validate a new nomogram for individualized prediction of cognitive impairment in patients with acute ischemic stroke (AIS).
Methods: We enrolled patients who suffered from AIS and were hospitalized at the First Affiliated Hospital of Soochow University between October 2018 and June 2020. All patients were assessed for cognitive impairment by the Montreal Cognitive Assessment (MoCA) scales within 14 days after the onset of AIS and MoCA score < 26 was defined as having cognitive impairment. The main outcome was the cognitive impairment. All patients were randomly (7:3) divided into two cohorts: the primary cohort and the validated cohort. On the basis of multivariate logistic model, the independent predictors of cognitive impairment in the acute phase were identified and the predictive nomogram was generated. The performance of the nomogram was evaluated by Harrell’s concordance index (C-index) and calibration plot both in the training cohort and validation cohort, respectively.
Results: A total of 191 patients with complete data were enrolled, of whom 135 comprised the primary cohort and 56 comprised the validated cohort. Of pooled analyses, gender, age, baseline NIHSS score, hyperhomocysteinemia (HHcy) and multiple lesions were independently associated with acute cognitive impairment after stroke and included to construct the nomogram. The nomogram derived from the primary cohort had an Area Under Curve (AUC) of 0.764 and the validated cohort had AUC of 0.867. Besides, calibration plot revealed adequate fit of the nomogram in predicting the risk of immediate cognitive impairment in patients with ischemic stroke.
Conclusion: The new nomogram based on gender, age, baseline NIHSS score, HHcy and multiple lesions gave rise to an accurate and comprehensive prediction for cognitive impairment in AIS patients. After further validation, it could be potentially a simple and pragmatic tool for prediction of immediate cognitive impairment of patients suffered from AIS.

Keywords
Cognitive impairment; Ischemic stroke; Nomogram; Prediction

Cite this paper
Anqi Tang, Sanjiao Liu, Zhi Wang, Han Shao, Xiuying Cai, Tan Li, A New Nomogram Model for Individualized Prediction of Cognitive Impairment in Patients With Acute Ischemic Stroke, SCIREA Journal of Clinical Medicine. Vol. 6 , No. 6 , 2021 , pp. 433 - 447 .

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