The Predictive Value of Myoglobin for Sepsis-Induced Cardiomyopathy

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The Predictive Value of Myoglobin for Sepsis-Induced Cardiomyopathy

https://doi.org/10.21203/rs.3.rs-5130613/v1

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Myoglobin (MYO) levels can be detected in the early stages of sepsis and may serve as a potential biomarker for assessing the severity and prognosis of sepsis. Our study aims to explore the predictive value of MYO for sepsis-induced cardiomyopathy (SICM) in patients with sepsis. A single-center prospective cohort study was conducted, collecting demographic data, admission Sequential organ failure assessment (SOFA) scores, echocardiography results, MYO, N-terminal pro-B-type natriuretic peptide (NT-proBNP) results, and other related records from 158 patients with sepsis. Patients were divided into SICM and non-SICM groups based on the left ventricular ejection fraction (LEVF) results from echocardiography. Propensity score matching (PSM) was used to control for the confounding effects of age, gender, and BMI. Univariate and multivariate Logistic regression analyses were performed to identify factors associated with the occurrence of SICM; the receiver operating characteristic (ROC) curve was used to evaluate the predictive ability of MYO for SICM. MYO levels were higher in the SICM group than in the non-SICM group (395.7 ng/ml vs 108.7 ng/ml, P < 0.05). Multivariate binary Logistic regression analysis showed that MYO is an independent risk factor for SICM in patients with sepsis (95% CI = 0.580–0.782, P < 0.05), with an area under the ROC curve (AUC) of 0.681 (95% CI: 0.580-0.782). MYO has good predictive value for SICM in patients with sepsis.

Health sciences/Biomarkers/Predictive markers

Health sciences/Risk factors

Sepsis is a life-threatening organ dysfunction clinical syndrome caused by the body's dysregulated response to infection, with a high incidence and mortality rate, and poses a serious threat to human life and health worldwide. In the Intensive Care Unit (ICU), sepsis is also a major cause of death among critically ill patients ^[1]. SICM is a severe complication in sepsis that significantly affects patient prognosis, but there is still uncertainty about the exact definition of SICM. Different studies have used different definitions and criteria, leading to differences in understanding the epidemiology, clinical significance, and treatment strategies for SICM. In clinical application, we need clearer biomarkers to predict SICM ^[2-3]. MYO is a small molecular oxygen-binding protein found in cardiac and skeletal muscle, and its main function is to promote the diffusion and storage of oxygen in muscle tissue. Yao et al. found in their 2016 study that MYO levels can be detected in the early stages of sepsis and may serve as a potential biomarker for assessing the severity and prognosis of sepsis^[4]. In this study, SICM is defined as a LEVF of less than 50% with a decrease of at least 10% from the baseline LEVF in patients with sepsis or septic shock, and recovery within two weeks^[5-6]. The author speculates that MYO may serve as a biomarker of myocardial injury in patients with SICM. The main purpose of this article's study is to determine the effectiveness and accuracy of MYO as a biomarker in the early diagnosis of SICM. The secondary purpose is to evaluate the combined use of MYO+NT-pro BNP+SOFA to improve the diagnostic efficiency of sepsis cardiomyopathy.

Patient characteristics。The study was conducted from April 2022 to May 2024, with patients with sepsis admitted to the emergency department of Fujian Medical University Union Hospitall as the subjects. A total of 158 patients were included in the analysis, of which 94 were male (59.5%) and 64 were female (40.5%), with an age range of (64±15) years. (Table 1) Due to the significant difference in age distribution between the two groups, PSM was performed to reduce the confounding effects of age, gender, and BMI, resulting in 110 matched sepsis patients. Among them, there were 55 patients in the SICM group, with 32 males (58.1%) and an age of (66.3±14.0) years, and 55 patients in the non-SICM group, with 39 males (70.9%) and an age of (64.9±14.4) years. There were no statistically significant differences in age, gender, and body mass index (BMI) between the two groups, indicating comparability (all P>0.05).(Table 2)

Patients in the SICM group had significantly elevated MYO levels. Upon comparison between the two groups, it was found that platelet (PLT) count and estimated glomerular filtration rate (eGFR) were higher in the SICM group (P < 0.05), while procalcitonin (PCT), lactate (Lac), MYO, NT-proBNP, troponin I (TnI), and SOFA scores were all lower in the SICM group compared to the non-SICM group (P < 0.05). In particular, the average MYO level in the SICM group was significantly higher than that in the non-SICM group (395.7 ng/mL vs 108.7 ng/mL, P < 0.05). The average NT-proBNP level in the SICM group was also significantly higher than that in the non-SICM group (3983 pg/mL vs 1005 pg/mL, P < 0.05).

MYO and NT-proBNP are independent risk factors for SICM. Univariate binary logistic regression analysis of the aforementioned indicators suggests that PLT, MYO, PCT, NT-proBNP, and TnI may be risk factors for septic cardiomyopathy, and a collinearity diagnosis was performed for these factors. There was no collinearity among the indicators. Multivariate binary logistic regression analysis indicates that MYO and NT-proBNP are independent risk factors for SICM.(Table 3)

The Predictive Value of MYO and NT-proBNP for SICM. To further analyze whether NT-proBNP and MYO are independent risk factors for SICM, the aforementioned indicators were subjected to ROC analysis. The results indicate that NT-proBNP and MYO can serve as good predictive factors for SICM (P < 0.05). The AUC (95% CI) for NT-proBNP is 0.633 to 0.820, the Youden index is 0.364, the sensitivity is 0.764, the specificity is 0.600, and the cutoff value is 1337.5 pg/ml. For MYO the AUC (95% CI) is 0.681 (0.580 to 0.782), the Youden index is 0.309, the sensitivity is 0.727, the specificity is 0.582, and the cutoff value is 155.25 ng/ml, which is clinically reliable for reference. (Figure 1, Table 4)

MYO+NT-proBNP+SOFA Joint Prediction of SICM. To further construct a predictive model for SICM and enhance diagnostic efficacy, the factors with significant differences between the two groups, including SOFA score, PLT, MYO, NT-proBNP, and PCT, were included in the logistic regression to build a predictive model. The method used was forward selection with a conditional approach. The combined variable model produced by the SOFA score, MYO, and NT-proBNP can serve as a good predictive variable. The combined variable model of MYO+NT-proBNP+SOFA at admission was used as the detection variable, and the ROC curve was plotted. (Figure 2). The AUC (95% CI) is 0.820 (0.744 to 0.897), the Youden index is 0.527, the sensitivity is 0.909, the specificity is 0.618, and the cutoff value is 0.691. Therefore, it is indicated that the combined prediction of the three has relatively good predictive value. (Table 4)

Patients with SICM have poor prognosis, and the mechanisms underlying its occurrence are related to toxins, cytokines, nitric oxide, complement activation, apoptosis, and disordered energy metabolism ^[7-9]. We conducted a prospective cohort study and discovered the relationship between MYO and SICM. When patients' MYO levels are higher than 155.25 ng/ml, it indicates a higher likelihood of SICM occurrence. The combined use of MYO, NT-proBNP, and SOFA is even more effective in predicting SICM.

In the study by Yao et al., elevated MYO levels in sepsis patients were also mentioned. MYO is correlated with disease severity and prognosis ^[4].In this article, MYO can predict the occurrence of SICM, which illustrates the importance of MYO in sepsis. The presence of systemic inflammatory response and inadequate tissue perfusion can lead to mitochondrial dysfunction and direct damage to neuromuscular tissue ^[10-12]. After fluid resuscitation, ischemia-reperfusion injury may occur. This complex cascade of damage may induce muscle fiber rupture and cell death. At this point, MYO is released into the bloodstream, leading to increased MYO levels ^[13].

BNP can reflect the status of cardiac load. When the loading conditions shift towards the unfavorable part of the Frank-Starling curve, the rise in BNP can provide indirect information about cardiac function. BNP levels can reflect the condition of myocardial damage, making NT-proBNP an excellent prognostic indicator ^[14-16]. Our results are consistent with those of Jeong et al., where elevated NT-proBNP is a risk factor for septic cardiomyopathy ^[17].

The SOFA score has been confirmed as an independent risk factor for the occurrence of SICM, which is consistent with the research findings of Narváez et al. ^[18]. In this study, we proposed for the first time a combined predictive model incorporating MYO, NT-proBNP, and SOFA scores to predict the onset of SICM. The SOFA score is a tool for comprehensively assessing the function of multiple organ systems, including the respiratory, hematologic, hepatic, cardiovascular, neurological, and renal systems.This indicates that the predictive model we have developed is capable of more fully reflecting the patient's condition.

We employed a prospective cohort study method and utilized propensity PSM to reduce the impact of confounding factors. This method is particularly important in observational studies because it helps to mitigate data bias and the influence of confounding variables, making the comparison between the experimental and control groups more reasonable. In this way, we revealed for the first time the relationship between MYO and septic cardiomyopathy.

However, our study also has some limitations. As a single-center study, the case source is mainly limited to internal medicine patients, which may limit the generalizability of the results. In addition, we used the change in LEVF to define SICM, but the measurement of LEVF may be affected by loading conditions, especially afterload, and therefore may not be a sensitive indicator of the intrinsic contractility of the myocardium ^[19-21]. Speckle tracking echocardiography (STE) is an emerging echocardiographic technique that can predict cardiovascular outcomes and provide prognostic data independent of LEVF^[22-23]. STE, by tracking speckles in myocardial regions, can more accurately reflect left ventricular function and thus may be a more effective tool for assessing SICM.

In future research, we recommend expanding the sample size and adopting multicenter studies to further validate our findings. Moreover, considering the relationship between MYO levels and the prognosis of septic patients^[4]. Future studies could include patient outcomes in their considerations to assess the predictive value of MYO for the prognosis of SICM patients. This may involve using advanced techniques such as STE to more accurately assess myocardial function and exploring other potential biomarkers to improve the accuracy of diagnosis and prognosis assessment of SICM. The Global Longitudinal Strain (GLS), derived from STE, is a powerful indicator of left ventricular contractility. It measures the change in length relative to the diastolic period during systole, providing a comprehensive assessment of the left ventricle's performance. GLS represents the average of the peak longitudinal strain values across all left ventricular segments, making it a sensitive and robust parameter for evaluating left ventricular function and detecting subclinical abnormalities^[24-26]. With these methods, we can look forward to making greater progress in the prediction and treatment of septic cardiomyopathy.

Study patients and design. This single-center prospective study collected clinical data from Fujian Medical University Union Hospital between April 2022 and May 2024. A total of 158 patients were included in the analysis, consisting of 94 males (59.5%) and 64 females (40.5%), with an average age of 64 years and a standard deviation of 15 years. All participants underwent a transthoracic echocardiography

examination within 24 hours of admission to diagnose the presence of SICM.The inclusion criteria for the study were: (1) age over 18 years; (2) meeting the diagnostic criteria for Sepsis 3.0, which includes the presence of infection and an increase of 2 or more points in the SOFA score^[1]. The exclusion criteria included: (1) severe arrhythmias, such as persistent or permanent atrial fibrillation; (2) pregnancy; (3) congenital heart disease; (4) moderate to severe valvular disease and post-valve replacement surgery; (5) history of acute myocardial infarction, myocarditis, or chronic heart failure; (6) end-stage malignant tumors; (7) patients diagnosed with sepsis in other wards and transferred after more than 24 hours; (8) patients participating in other studies or who had previously been included in this study. The exclusion criteria for analysis were: patients who died within 72 hours and had not completed the echocardiography examination and MYO testing. Based on the results of the echocardiography, patients were divided into two groups: one group diagnosed with SICM and the other group without SICM.

Data Collection Patient data was collected upon admission to the emergency department of Fujian Medical University Union Hospital, including age, gender, BMI, and initial laboratory test results such as hemoglobin, white blood cell count, neutrophil-to-lymphocyte ratio (NLR), PLT, C-reactive protein (CRP), MYO, PCT, NT-proBNP, Lac, alanine aminotransferase (ALT), aspartate aminotransferase (AST), eGFR, glucose (GLU), lactate dehydrogenase (LDH), TnI, interleukin-6 (IL-6), and the SOFA score at admission.

Definition：SICMS. SICM is defined as a LEVF of less than 50% with a decrease of at least 10% from the baseline LEVF in patients with sepsis or septic shock, and recovery within two weeks^[5-6]. If the baseline is unknown, it is defined as an increase of more than 10% from the initial ejection fraction assessed at admission.

Statistical Analysis Data was statistically analyzed using SPSS 26.0 software. Quantitative data conforming to a normal distribution and with homogeneity of variances were expressed as mean ± standard deviation (±s), and intergroup comparisons were made using independent samples t-tests. Non-normally distributed data were represented by medians (IQR) and analyzed using non-parametric tests (Mann-Whitney U tests). Categorical data were expressed as counts and percentages (%) and analyzed using chi-square tests. To minimize the confounding effects of age, gender, and BMI between the SICM and non-SICM groups, PSM was performed. The predictive value of various risk factors and imaging findings on clinical outcomes was assessed using multivariate binary logistic regression analysis. ROC curves were plotted, the Youden index was calculated, and the optimal cutoff values for predicting adverse outcomes were determined, along with the corresponding sensitivity and specificity. Statistical significance was set at P<0.05 for all methods mentioned above.

AUC Area under the ROC curve

ALT Alanine aminotransferase

AST Aspartate aminotransferase

BMI Body mass index

CRP C-reactive protein

eGFR Estimated glomerular filtration rate

GLS Global Longitudinal Strain

ICU Intensive Care Unit

IL-6 Interleukin-6

Lac Lactate

LDH Lactate dehydrogenase

LEVF Left ventricular ejection fraction

MYO Myoglobin

NLR Neutrophil-to-lymphocyte ratio

NT-proBNP N-terminal pro-B-type natriuretic peptide

PCT Procalcitonin

PLT Platelet

PSM Propensity score matching

ROC Receiver operating characteristic

SICM Sepsis-induced cardiomyopathy

SOFA Sequential organ failure assessment

STE Speckle tracking echocardiography

TnI Troponin I

WBC White blood cell countAbbreviations

Ethics approval and consent to participate.Tis study was conducted in accordance with the Declaration of Helsinki and was approved by the research ethics committee of Fuzhou First Hospital (Ethics Code: 202209046). This study is registered with the Chinese Clinical Trial Registry (https://www.chictr.org.cn/) (Protocol No. ChiCTR2200058007). For this study, informed consent was obtained from all individual participants included in the study or their legal representatives. The informed consent process involved a comprehensive explanation of the study's objectives, procedures, potential risks, and benefits. Participants were assured of their right to withdraw from the study at any time without any consequences to their current or future medical care.

Data Accessibility

All data and analytical results from this study are comprehensively included within the published article and its accompanying supplementary files.

Author contributions

Y.C. and G.Y.conceived and designed the study. Y.C. performed statistical analyses. Y.C. collected and interpreted data. Y.C. drafted the manuscript. G.Y. and X.L. critically revised the manuscript. All authors read and approved the final manuscript.

Competing interests

The authors declare no competing interests.

Funding

This study was supported by the Fujian Province Natural Science Foundation General Project (2022J01728), Fujian Province Science and Technology Innovation Joint Fund Project (2023Y9207)granted to Dr. Guangwei Yu. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.

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Tables 1 to 4 are available in the Supplementary Files section

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The Predictive Value of Myoglobin for Sepsis-Induced Cardiomyopathy

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