Development and validation of a novel clinical prediction model to predict the 90-day functional outcome of spontaneous intracerebral hemorrhage - Geng, Zhi; Guo, Tao; Cao, Ziwei; He, Xiaolu; Chen, Jing; Yue, Hong; Wu, Aimei; Wei, Lichao (Frontiers in Neurology, 2023)
Background: Spontaneous Intracerebral hemorrhage (SICH) is associated with high mortality and disability. Accurately predicting adverse prognostic risks of SICH is helpful in developing risk stratification and precision medicine strategies for this phenomenon.: We analyzed 413 patients with SICH admitted to Hefei Second People's Hospital as a training cohort, considering 74 patients from the First Affliated Hospital of Anhui Medical University for external validation. Univariate and multivariate logistic regression analysis were used to select risk factors for 90-day functional outcomes and a nomogram was developed to predict their incidence in patients. Discrimination, fitting performance, and clinical utility of the resulting nomogram were evaluated though receiver operating characteristic (ROC) curves, accuracy, sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV) , calibration plots, and decision curves analysis (DCA) respectively. Results: Of the 413 patients, 180 had a poor prognosis. Univariate analysis showed significant variance of age, systolic pressure, Intraventricular hemorrhage (IVH) , Glasgow Coma Scale (GCS) scores , National Institute of Health stroke scale (NIHSS) scores and hematoma volume between the groups (p<0.05). Logistic multivariate regression analysis showed that age, IVH, NIHSS and hematoma volume were associated with unfavorable outcomes. Based on the results, a nomogram model was developed with an area under the ROC curve of 0.91 (95%CI; 0.88-0.94) and 0.89 (95%CI; 0.80-0.95) in the training and validation sets, respectively.In the validation set, the accuracy, sensitivity, specificity, PPV, and NPV of the model were 0.851, 0.923, 0.812, 0.727, and 0.951, respectively. The calibration plot demonstrates the goodness of fit between the nomogram predictions and actual observations. Finally, DCA indicated significant clinical adaptability. Conclusion: We developed and validated a short-term prognostic nomogram model for patients with SICH including NIHSS scores, age, hematoma volume and IVH.This model has valuable potential in predicting the prognosis of patients with SICH.