[Establishment of a predictive model of septic myocardiopathy based on left ventricular global longitudinal strain]
1Department of Critical Care Medicine, Northern Jiangsu People's Hospital, Yangzhou 225001, China.
Insights
This study identifies key risk factors for septic cardiomyopathy, developing a predictive model using biomarkers like Hs-TnI and NT-proBNP to aid early diagnosis in sepsis patients.
Area of Science:
- Cardiology
- Critical Care Medicine
- Biomarker Research
Background:
- Sepsis can lead to septic cardiomyopathy, a serious complication.
- Early identification of risk factors and predictive markers is crucial for patient outcomes.
Purpose of the Study:
- To identify risk factors for septic cardiomyopathy.
- To develop a predictive model for septic cardiomyopathy using left ventricular global longitudinal strain (LV GLS) and clinical data.
Main Methods:
- Echocardiography was used to measure LV GLS in sepsis patients.
- Patients were categorized into septic cardiomyopathy (LV GLS > -17%) and normal cardiac function (LV GLS ≤ -17%) groups.
- Multivariate logistic regression and ROC curve analysis were employed to identify risk factors and validate the predictive model.
Main Results:
- Elevated levels of high sensitive troponin I (Hs-TnI), procalcitonin (PCT), lactate (Lac), and N-terminal pro-brain atriuretic peptide (NT-proBNP) were significantly higher in the septic cardiomyopathy group.
- Hs-TnI (≥0.131 μg/L), PCT (≥40 μg/L), Lac (≥4.2 mmol/L), and NT-proBNP (≥3270 ng/L) were identified as independent risk factors.
- The predictive model demonstrated good diagnostic performance with an AUC of 0.838.
Conclusions:
- Hs-TnI, PCT, Lac, and NT-proBNP are independent risk factors for septic cardiomyopathy.
- A predictive model incorporating these biomarkers shows strong diagnostic utility for septic cardiomyopathy.
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%CI:2.67-16.88, P<0.001), PCT≥40 μg/L (OR=3.08, 95%CI:1.10-8.59, P=0.032), Lac≥4.2 mmol/L (OR=2.80, 95%CI:1.02-7.69, P=0.045), NT-proBNP≥3 270 ng/L (OR=2.67, 95%CI:1.06-6.74, 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%CI:0.766-0.910), and the C-index was 0.822 (95%CI:0.750-0.894) 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.
