Prediction of traumatic hemorrhagic shock using a Multi-scale exogenous variable model (MS-TimeXer-MoE).

objectiveTo predict the likelihood of hemorrhagic shock in trauma patients using a multi-scale exogenous variable model, MS-TimeXer-MoE.

methodsThis study is the first to use the TimeXer method incorporating exogenous variables to establish a predictive model for traumatic hemorrhagic shock, achieving notable prediction results. Data from trauma patients were extracted from the MIMIC IV database according to inclusion and exclusion criteria. After data processing, the most relevant indicators were selected, including endogenous variables (e.g., vital signs, laboratory indicators) and exogenous variables (e.g., cause of trauma, gender, age, injury site). By integrating exogenous variables and multi-scale feature learning, and innovatively combining the multi-expert mechanism with the TimeXer method, a multi-expert mixed model, MS-TimeXer-MoE, was developed to predict hemorrhagic shock occurrence with higher accuracy and specificity. A total of 4,870 patients were included, divided into an experimental group of 2,432 cases and a control group of 2,438 cases based on the occurrence of hemorrhagic shock post-admission. The dataset was split into training, validation, and testing sets in a 60%:20%:20% ratio

resultsThe AUC value of the MS-TimeXer-MoE model in predicting hemorrhagic shock in trauma patients was 0.8995, with a recall rate of 0.8607, demonstrating high efficiency in shock identification, indicating that the model can distinguish positive and negative samples with high accuracy and recall rate. In regression tasks, the MS-TimeXer-MoE model's mean absolute error (MAE) was 3.4397, mean squared error (MSE) was 8.2735, mean absolute percentage error (MAPE) was 5.9933%, and the coefficient of determination (R

conclusionCompared to existing mainstream modeling methods for predicting shock occurrence, the MS-TimeXer-MoE model can more accurately predict the occurrence of hemorrhagic shock in trauma patients.