A COACHS Nomogram to Predict the Probability of Three-Month Unfavorable Outcome after Acute Ischemic Stroke in Chinese Patients

BaiLi Song; YuKai Liu; Linda Nyame; XiangLiang Chen; Teng Jiang; Wei Wang; Chao Sun; Dan Tang; Chen Chen; Mako Ibrahim; Jie Yang; JunShan Zhou; JianJun Zou

doi:10.1159/000497243

A COACHS Nomogram to Predict the Probability of Three-Month Unfavorable Outcome after Acute Ischemic Stroke in Chinese Patients

Cerebrovasc Dis. 2019;47(1-2):80-87. doi: 10.1159/000497243. Epub 2019 Mar 21.

Authors

BaiLi Song^{1

2}, YuKai Liu³, Linda Nyame^{1

2}, XiangLiang Chen³, Teng Jiang³, Wei Wang³, Chao Sun^{1

2}, Dan Tang², Chen Chen¹, Mako Ibrahim^{1

2}, Jie Yang⁴, JunShan Zhou⁵, JianJun Zou¹

Affiliations

¹ Department of Clinical Pharmacology, Nanjing First Hospital, Nanjing Medical University, Nanjing, China.
² School of Basic Medicine and Clinical Pharmacy, China Pharmaceutical University, Nanjing, China.
³ Department of Neurology, Nanjing First Hospital, Nanjing Medical University, Nanjing, China.
⁴ Department of Neurology, The First Affiliated Hospital of Chengdu Medical College, Chengdu, China.
⁵ Department of Neurology, Nanjing First Hospital, Nanjing Medical University, Nanjing, China, zhjsh333@126.com.

PMID: 30897564
DOI: 10.1159/000497243

Abstract

Background: Accurate prognostication of unfavorable outcome made at the early onset of stroke is important to both the clinician and the patient management. This study was aimed to develop a nomogram based on the integration of parameters to predict the probability of 3-month unfavorable functional outcome in Chinese acute ischemic stroke patients.

Methods: We retrospectively collected patients who underwent acute ischemic stroke at Stroke Center of the Nanjing First Hospital (China) between May 2013 and May 2018. After exclusion, the study population includes 1,025 patients for nomogram development. The main outcome measure was 3-month unfavorable outcome (modified Rankin Scale > 2). Multivariable logistic regression analysis was used to develop the predicting model, and stepwise logistic regression with the Akaike information criterion was utilized to find best-fit nomogram model. We incorporated the creatinine, fast blood glucose, age, previous cerebral hemorrhage, previous valvular heart disease, and NHISS score (COACHS), and these factors were presented with a nomogram. We assessed the discriminative performance by using the area under curve (AUC) of receiver-operating characteristic (ROC) and calibration of risk prediction model by using the Hosmer-Lemeshow test.

Results: Multivariate analysis of the 1,025 patients for logistic regression helped identify the independent factors as National Institutes of Health Stroke Scale score on admission, age, previous valvular heart disease, fasting blood glucose, creatinine, and previous cerebral hemorrhage, which were included in the COACHS nomogram. The AUC-ROC of nomogram was 0.799. Calibration was good (p = 0.1376 for the Hosmer-Lemeshow test).

Conclusions: The COACHS nomogram may be used to predict unfavorable outcome at 3 months after acute ischemic stroke in Chinese population. It may be also a reliable tool that is effective in its clinical utilization to risk-stratify acute stroke patients.

Keywords: Cerebral ischemia; Nomogram; Prediction; Stroke; Unfavorable outcome.

Publication types

Research Support, Non-U.S. Gov't

MeSH terms

Aged
Aged, 80 and over
Asian People
Brain Ischemia / diagnosis*
Brain Ischemia / epidemiology
Brain Ischemia / physiopathology
Brain Ischemia / therapy
China / epidemiology
Decision Support Techniques*
Disability Evaluation
Female
Humans
Male
Middle Aged
Nomograms*
Predictive Value of Tests
Prognosis
Recovery of Function
Retrospective Studies
Risk Assessment
Risk Factors
Stroke / diagnosis*
Stroke / epidemiology
Stroke / physiopathology
Stroke / therapy
Time Factors