Development and Validation of a Website to Guide Decision-Making for Disorders of Consciousness - Kang, Junwei; Zhong, Yuan; Chen, Gengfa; Huang, Lianghua; Tang, Yunliang; Ye, Wen; Feng, Zhen (Frontiers in Aging Neuroscience, 2022)
Abstract Background: This study aimed to develop and validate a nomogram and present it on a website to be used to predict the overall survival at 16, 32, and 48 months in patients with prolonged disorder of consciousness. Methods: We retrospectively analyzed the data of 381 patients with prolonged disorder of consciousness at two centers. The data were randomly divided into training and validation sets using a ratio of 6:4. On the training set, Cox proportional hazard analyses were used to identify the predictive variables. Results: The final model included age, Glasgow coma scale score, serum albumin level, and computed tomography midline shift, all of which had a significant effect on survival after disorders of consciousness. For the 16-, 32-,and 48-month survival on the training set, the model had good discriminative power, with areas under the curve of 0. 791, 0. 760,and 0. 886,respectively. For the validation set, the areas under the curve for the 16-month, 32-month, and 48-month survival predictions were 0.806 and 0.789, 0.867, respectively. Model performance was good for both training and validation sets according to calibration plots and decision curve analysis. Conclusion: We developed an accurate , efficient nomogram and a corresponding website based on four correlated factors to help clinicians improve their assessments of patient outcomes and help personalize the treatment process and clinical decisions.