Prediction of the central venous pressure in trauma patients on the basis of non-invasive parameters using artificial neural network

Abstract

Background: Generally, in traumatic patients, uncontrolled bleeding leads to shock and ultimately death. So, any early detection of shock can reduce the likelihood of a patient’s death. At present, the precise method for estimating the body’s need for fluids is to measure central venous pressure (CVP). However, this method is invasive and time consuming. Objective: This study aimed to predict the central venous pressure value and range of trauma patients through non-invasive parameters such as caval index, lactate clearance, base excess and shock index. Methods: A prospective observational study was performed in 100 trauma patients. Written informed consent was obtained from patient(s) or relatives for their anonymized information to be published in any article. Results: It indicated that parameters such as caval index (at a proposed cutoff point of 35%), lactate clearance (at a cutoff point of 6%) and base excess (at a proposed cutoff point of 6 mmol/L) are approximately of the same level of accuracy for estimating the central venous pressure range, while parameter shock index (at a cutoff point of 1.25) is of the least level of accuracy to predict the central venous pressure range. Results also showed that among all proposed predictive models for estimating the central venous pressure value, which were on the basis of either non-linear regression or artificial neural network, the most accurate model was the one on the basis of the artificial neural network. Among parameters lactate clearance, base excess and shock index used to form the artificial neural network-based model, parameters base excess and lactate clearance were of the highest and lowest level of importance, respectively. Conclusion: Among all proposed models and non-invasive parameters to predict the central venous pressure range, CVPLC model (at a cutoff point of 9), which is a non-linear regression model and is in terms of parameter lactate clearance, was the most accurate model.

Correlation between Glasgow Coma Scale with central venous pressure and near-infrared spectroscopy in patients with acquired brain injury in the intensive care unit of Adam Malik Hospital Medan

“…However, so far, many studies have been carried out to determine noninvasive parameters as representative of the CVP range, but the level of accuracy of these parameters remains unclear. [28] The effect of a high CVP may be more pronounced in the presence of elevated ICP. However, this is under special conditions in Fontan circulation.…”

Estimation of Physiologic Pressures: Invasive and Non-Invasive Techniques, AI Models, and Future Perspectives

“…An ANN model constructed by Moinadini et al in 2019 used several clinical parameters, including the heart rate, SBP, caval index, lactate clearance and shock index, all of which showed an individual positive correlation with invasive CVP monitoring measurements. This model showed a sensitivity of 100% for normal CVP and 91% for elevated CVP (>8 mmHg) [ 228 ].…”