Development of a Nomogram to Predict 28-Day Mortality of Patients With Sepsis-Induced Coagulopathy: An Analysis of the MIMIC-III Database - Lu, Zongqing; Zhang, Jin; Hong, Jianchao; Wu, Jiatian; Liu, Yu; Xiao, Wenyan; Hua, Tianfeng; Yang, Min (Frontiers in Medicine, 2021)
Background Sepsis-induced coagulopathy (SIC) is a common cause for inducing poor prognosis in intensive care unit (ICU) patients with sepsis. This study aimed to develop a practical nomogram to predict the risk of 28-day mortality in SIC patients. Methods Data were retrieved from the Medical Information Mart for Intensive Care (MIMIC-III) database, according to predetermined inclusion and exclusion criteria. Sepsis was defined based on Sepsis 3.0 criterion and SIC based on Toshiaki Iba’s criterion. Further, SIC cohort was randomly divided into training or validation set, the predictive nomogram was constructed by using logistic regression analysis, then verified the ability of discrimination and calibration by internal validation. Results 9432 sepsis patients in MIMIC III were enrolled, in which 3280 (34.8%) patients were diagnosed as SIC during the first ICU admission. The multivariate regression analysis found that SIC was independently associated with the 7-day and 28-day mortality of sepsis patients. Parameters eligible for this nomogram including age, combined with liver disease, the administration of norepinephrine, and some clinical variables during the first 24 h since ICU admission, including mean arterial pressure (MAP), mean heart rate, mean respiratory rate, mean temperature, lactate-max, prothrombin time-max (PT-max), red cell distribution width-min (RDW-min), mean corpuscular volume-min (MCV-min) and platelet-min. This nomogram performed a better discrimination indicated by the area under the receiver operating characteristic curve (AUROC) of 0.78 (95%CI 0.76-0.80) and 0.81 (95%CI 0.78-0.84) in training and validation set respectively when predicted the risk of 28-day mortality. Meanwhile, the nomogram was closely related with an acceptable calibration reflected by the fitness of the calibration plot. In the clinical practice, the decision curve analysis of nomogram obtained more net benefit when compared with the sequential organ failure assessment (SOFA) score and the logistic organ dysfunction score (LODS). Conclusions SIC is independently related to the short-time mortality of sepsis patients. The nomogram achieved an optimal prediction of 28-day mortality in SIC patients. Using the model, the 28-day mortality risk of an individual SIC patient can be determined, which can lead to a better prognosis.