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

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. (c) 2019 S. Karger AG, Basel