关键词:

脓毒症休克, 心肌病, 休克指数, 心脏磁共振特征追踪技术, 心脏功能参数, 列线图, 预测模型

Abstract:

Objective　To establish and validate a predictive model for septic shock cardiomyopathy based on the shock index (SI) and cardiac magnetic resonance feature tracking (FT-CMR) parameters, aiming to provide clinical guidance for reducing the incidence of cardiomyopathy in patients with septic shock. Methods　A retrospective analysis was conducted on the clinical data of 137 patients with septic shock admitted to Xi'an Ninth Hospital from May 2020 to October 2023. Patients were divided into a cardiomyopathy group (42 cases) and a non-cardiomyopathy group (95 cases) based on the presence of cardiomyopathy within 72 hours of enrollment. In the cardiomyopathy group, there were 23 males and 19 females, aged (66.52±5.54) years and a body mass index (BMI) of (22.77±1.18) kg/m². In the non-cardiomyopathy group, there were 48 males and 47 females, aged (58.74±4.89) years and a BMI of (22.48±1.16) kg/m². All patients underwent FT-CMR examination and SI assessment at enrollment. Factors influencing the occurrence of cardiomyopathy were analyzed, and a nomogram was constructed to predict the risk of cardiomyopathy. The predictive efficacy of the model for the occurrence of cardiomyopathy was analyzed using receiver operating characteristic (ROC) curves. Statistical analyses were performed using the χ² test and t test. Results　Univariate analysis showed that the age, cardiac troponin (cTnI), lactic acid, N-terminal pro-brain natriuretic peptide (NTpro-BNP) and SI levels in the cardiomyopathy group were higher than those in the non-cardiomyopathy group, while the total left atrial strain (Es), overall longitudinal strain of the left atrium (PLAS), and peak positive strain rate (SRs) were lower in the cardiomyopathy group (all P<0.05). Binary logistic regression analysis revealed that age [odds ratio (OR)=2.769, 95% confidence interval (CI) 1.151-6.663], lactate (OR=4.661, 95% CI 2.645-8.212), cTnI (OR=6.234, 95% CI 3.096-12.550), and SI (OR=4.165, 95% CI 1.526-11.361) were independent risk factors for the development of cardiomyopathy in patients with septic shock, while PLAS (OR=0.186, 95% CI 0.081-0.423) was an independent protective factor. The nomogram prediction model constructed based on these influencing factors showed a C-index of 0.821 (95% CI 0.743-0.925) upon internal validation using the Bootstrap method, with the calibration curve for predicting the occurrence of cardiomyopathy approaching the ideal curve (P>0.05). ROC analysis indicated that the nomogram model had a sensitivity of 85.70% and specificity of 86.60%, with an area under the curve (AUC) of 0.872 (95% CI 0.783-0.960). Conclusion　SI is an independent risk factor for the development of cardiomyopathy in patients with septic shock, and PLAS is an independent protective factor. The nomogram prediction model based on SI and PLAS can better evaluate the risk of cardiomyopathy in patients with septic shock.

Key words:

Septic shock, Cardiomyopathy, Shock index, Cardiac magnetic resonance feature tracking technology, Cardiac function parameters,  , Nomogram, Prediction model