Prediction of venous thromboembolism using clinical and serum biomarker data from a military cohort of trauma patients

Abstract

IntroductionVenous thromboembolism (VTE) is a frequent complication of trauma associated with high mortality and morbidity. Clinicians lack appropriate tools for stratifying trauma patients for VTE, thus have yet to be able to predict when to intervene. We aimed to compare random forest (RF) and logistic regression (LR) predictive modelling for VTE using (1) clinical measures alone, (2) serum biomarkers alone and (3) clinical measures plus serum biomarkers.MethodsData were collected from 73 military casualties with at least one extremity wound and prospectively enrolled in an observational study between 2007 and 2012. Clinical and serum cytokine data were collected. Modelling was performed with RF and LR based on the presence or absence of deep vein thrombosis (DVT) and/or pulmonary embolism (PE). For comparison, LR was also performed on the final variables from the RF model. Sensitivity/specificity and area under the curve (AUC) were reported.ResultsOf the 73 patients (median Injury Severity Score=16), nine (12.3%) developed VTE, four (5.5%) with DVT, four (5.5%) with PE, and one (1.4%) with both DVT and PE. In all sets of predictive models, RF outperformed LR. The best RF model generated with clinical and serum biomarkers included five variables (interleukin-15, monokine induced by gamma, vascular endothelial growth factor, total blood products at resuscitation and presence of soft tissue injury) and had an AUC of 0.946, sensitivity of 0.992 and specificity of 0.838.ConclusionsVTE may be predicted by clinical and molecular biomarkers in trauma patients. This will allow the development of clinical decision support tools which can help inform the management of high-risk patients for VTE.

Prevention of Venous Thromboembolism in 2020 and Beyond

“…Early successes with predicting VTE risk using biomarkers should prompt further research into the use of biomarkers in new situations. The discovery and evaluation of novel biomarkers to risk-stratify patients may be an area of significant interest going forward, and serum biomarkers such as Vascular Endothelial Growth Factor (VEGF), Interferon-alpha (IFN-α), Interleukin-15 (IL-15), and Citrullinated histone H3 (H3cit) may see further investigation for this purpose [182][183][184].…”

Predicting the occurrence of venous thromboembolism: construction and verification of risk warning model

“…The VTE prediction model were established with purpose of making accurate assessment and diagnosis of VTE in the first time and avoiding adulterating human factors as much as possible. We know that there is a lot of VTE-related information in the electronic medical record system [27,[33][34][35][39][40][41], and such information needs to be further explored and fully utilized in the clinical VTE warning. The VTE risk warning model made full use of Caprini risk assessment scale, which was widely used in clinical medicine and surgery, with the important clinical symptoms and signs of VTE patients and laboratory examination indicators, to carry out comprehensive and multi-dimensional warning and achieve higher prediction efficiency.…”

“…Medical records which contain rich information about disease progression, are useful in mining new risk factors related to VTE patients. Each patient will undergo a series of laboratory tests upon admission, and the blood test indicators of VTE patients will be abnormal in varying degrees [26][27][28]. The timely detection of abnormal change will facilitate the VTE occurrence risk assessment and enable early warning and intervention.…”

Predicting the occurrence of venous thromboembolism: construction and verification of Risk Warning Model

“…The VTE prediction model are established with the purpose of making accurate assessment and diagnosis of VTE in the first time and avoiding adulterating human factors as much as possible. We know that there is a lot of VTE-related information in the electronic medical record system [27,[33][34][35][40][41][42], and this information needs to be further explored and fully utilized in the clinical warning of VTE. The VTE risk warning model makes full use of the Caprini risk assessment scale, which is widely used in clinical medicine and surgery, with the important clinical symptoms and signs of VTE patients and laboratory examination indicators, to carry out comprehensive and multidimensional comprehensive warning and achieve higher prediction efficiency.…”

“…Medical records which contain rich information about disease progression, are useful in mining new risk factors related to VTE patients. Each patient will undergo a series of laboratory tests upon admission, and the blood test indicators of VTE patients will be abnormal to varying degrees [26][27][28]. The timely detection of these abnormal changes will help to assess the risk of VTE occurrence and enable early warning and intervention.…”