Therapeutics and Clinical Risk Management (Nov 2021)
A Prognostic Model Incorporating Red Cell Distribution Width to Platelet Ratio for Patients with Traumatic Brain Injury
Abstract
Ruoran Wang,1 Min He,2 Jing Zhang,1 Shaobo Wang,3 Jianguo Xu1 1Department of Neurosurgery, West China Hospital, Sichuan University, Chengdu, Sichuan Province, People’s Republic of China; 2Department of Critical Care Medicine, West China Hospital, Sichuan University, Chengdu, Sichuan Province, People’s Republic of China; 3Department of Infectious Diseases, Xi’an Hospital of Traditional Chinese Medicine, Xi’an, Shannxi Province, People’s Republic of ChinaCorrespondence: Jianguo XuDepartment of Neurosurgery, West China Hospital, Sichuan University, No. 37, Guoxue Alley, Chengdu, 610041, People’s Republic of ChinaEmail [email protected] WangDepartment of Infectious Diseases, Xi’an Hospital of Traditional Chinese Medicine, No. 69, Fengcheng 8th Road, Xi’an, 710016, People’s Republic of ChinaEmail [email protected]: As an inflammation-based marker, red cell distribution width to platelet ratio (RPR) has been verified to be associated with disease severity and outcome in many clinical settings. We designed this study to evaluate the prognostic value of RPR in patients with traumatic brain injury (TBI).Methods: A total of 420 patients admitted with TBI were included in this study. Laboratory and clinical data were collected from an electronic medical record system. Univariate and multivariate logistic regression analyses were sequentially performed to discover risk factors of in-hospital mortality. Receiver operating characteristic (ROC) curves were drawn to confirm the predictive value of different markers including RPR in training set and testing set.Results: Non-survivors had higher level of RPR than survivors (P< 0.001). Logistic regression analysis showed that RPR was significantly associated with mortality even after adjusting for confounding factors (P< 0.001). The area under the ROC curve (AUC) value of Glasgow Coma Scale (GCS) for predicting mortality was 0.761 and 0775 in training set and testing set, respectively. And the constructed predictive model incorporating RPR had the highest AUC value of 0.858 and 0.884 in training set and testing set.Conclusion: RPR is significantly associated with mortality in TBI patients. Utilizing RPR to construct a predictive model is valuable to evaluate prognosis of TBI patients.Keywords: red cell distribution to platelet ratio, traumatic brain injury, prognosis, marker
