[Establishment of a predictive model of septic myocardiopathy based on left ventricular global longitudinal strain].

ABSTRACT

Objectives: To explore the risk factors associated with septic cardiomyopathy and establish a predictive model of the disease based on left ventricular global longitudinal strain (LV GLS). Methods: Data from sepsis patients without a history of cardiac dysfunction who were treated in the Critical Care Department of the Northern Jiangsu People's Hospital from September, 2019 to January, 2021 were included in the analysis. The LV GLS was measured by echocardiography within 72 hours and the patients were divided into a septic myocardiopathy group (LV GLS>-17%) and a normal cardiac function group (LV GLS≤-17%). Clinical data from two groups of patients were collected for univariate analysis. The receiver operating characteristic (ROC) curves of the factors that were statistically different were drawn for exploring the diagnostic and cut-off values. The continuous variable was converted to a dichotomous variable according to the cut-off value. Multivariate logistic regression analysis of sepsis cardiomyopathy was performed to screen the risk factors and create a predictive model. The predictive model was evaluated by ROC curve analysis and the Bootstrap method and shown as a nomograph. Results: Patients in the sepsis cardiomyopathy group had higher levels of high sensitive troponin I (Hs-TnI), procalcitonin (PCT), lactate (Lac), N-terminal pro-brain atriuretic peptide (NT-proBNP), vasopressor dosing intensity (VDI) and sequential organ failure assessment (SOFA) when compared to those in the normal cardiac function group (all P<0.05). The multivariate logistic regression analysis showed that Hs-TnI≥0.131 µg/L (OR=6.71, 95%CI2.67-16.88, P<0.001), PCT≥40 µg/L (OR=3.08, 95%CI1.10-8.59, P=0.032), Lac≥4.2 mmol/L (OR=2.80, 95%CI1.02-7.69, P=0.045), NT-proBNP≥3 270 ng/L (OR=2.67, 95%CI1.06-6.74, P=0.038) were independent risk factors for septic myocardiopathy. The area under the ROC curve of the predictive model based on the four indexes up-mentioned was 0.838 (95%CI0.766-0.910), and the C-index was 0.822 (95%CI0.750-0.894) which indicated the utility of the nomogram. The model had a good predictive ability, accuracy and discrimination. Conclusions: Hs-TnI≥0.131 µg/L, PCT≥40 µg/L, Lac≥4.2 mmol/L and NT-proBNP≥3 270 ng/L are independent risk factors for septic myocardiopathy, and the septic cardiomyopathy predictive model constructed based on these factors has a good diagnostic performance.