[Correlation analysis of macrophage migration inhibitory factor with related markers of septic myocardial injury and its prognostic predictive value].

OBJECTIVE

To explore the association between macrophage migration inhibitory factor (MIF) and sepsis-induced myocardial injury (SIMI), as well as its predictive value for the prognosis of septic patients.

METHODS

A prospective observational study was conducted. Sixty-three adult patients with confirmed sepsis admitted to the department of critical care medicine of The First Affiliated Hospital of Xinjiang Medical University from July 2024 to June 2025 were consecutively enrolled. According to the cardiac troponin I (cTnI) level on the first day of admission, the patients were divided into SIMI group (cTnI≥0.04 μg/L) and sepsis without myocardial injury group (cTnI<0.04 μg/L). The demographic data, admission-related scores, and laboratory indicators of septic patients, measured indicators such as MIF and interleukin-18 (IL-18) within 24 hours of patients' admission to the intensive care unit (ICU) were collected, and the indicators such as Acute Physiology And Chronic Health Evaluation II (APACHE II) score, Sequential Organ Failure Assessment (SOFA) score, oxygenation index, and echocardiographic indicators within 24 hours of patients' admission to the ICU were recorded. The clinical data of the two groups of patients were compared. The correlation between indicators was analyzed by using Pearson or Spearman rank correlation method. A receiver operator characteristic curve (ROC curve) was drawn to evaluate the predictive performance of MIF, IL-18, and their combination for 28-day death in septic patients. Multivariate Logistic regression analysis was used to screen independent risk factors for 28-day death in septic patients, and a nomogram model was constructed. The discrimination, calibration, and clinical utility of the model were evaluated using ROC curve, calibration curve, and decision curve analysis (DCA).

RESULTS

A total of 63 septic patients were finally enrolled in the study, including 23 patients in the SIMI group and 40 patients in the non-SIMI group. The APACHE II score, alanine aminotransferase (ALT), aspartate aminotransferase (AST), N-terminal pro-brain natriuretic peptide (NT-proBNP), cTnI, MB isoenzyme of creatine kinase (CK-MB), IL-18, and MIF were all higher in the SIMI group compared to the non-SIMI group (all P<0.05). There were no statistically significant differences in demographic data, other laboratory indicators, and echocardiographic parameters between the two groups. Correlation analysis revealed a positive correlation between MIF and downstream inflammatory factor IL-18 and APACHE II score in septic patients (r values were 0.523 and 0.556, respectively, both P<0.05). Among echocardiographic indicators, MIF was negatively correlated with left ventricular ejection fraction (LVEF; r=-0.265, P<0.05), while there was no significant correlation between MIF and left ventricular posterior wall thickness at end-diastole or left atrial diameter at end-diastole (both P>0.05). ROC curve analysis revealed that both MIF and IL-18 possessed predictive value for 28-day death in septic patients [the area under the ROC curve (AUC) and 95% confidence interval (95%CI) were 0.745 (0.563-0.933) and 0.751 (0.614-0.892), respectively], and the combined prediction of the two had an AUC of 0.784 (95%CI was 0.629-0.940), with a sensitivity of 78.6% and a specificity of 79.6%. Multivariate Logistic regression analysis revealed that an elevated SOFA score [odds ratio (OR)=1.381, 95%CI was 1.067-1.787, P=0.014], increased IL-18 (OR=1.000, 95%CI was 1.000-1.001, P=0.023), elevated MIF (OR=1.000, 95%CI was 1.000-1.000, P=0.036), and decreased oxygenation index (OR=0.989, 95%CI was 0.978-1.000, P=0.046) were independent risk factors for 28-day death in patients with sepsis. Based on these variables, a nomogram model for predicting 28-day death in septic patients was constructed. ROC curve analysis indicated that the AUC of the nomogram model for predicting 28-day death in septic patients was 0.894 (95%CI was 0.766-1.000). Further analysis revealed that the model's C-index reached 0.894, and both the calibration curve and DCA curve suggested good discriminatory power, calibration capability and clinical utility of the model.

CONCLUSIONS

MIF can serve as a sensitive biomarker for early identification of SIMI, and the combined detection of MIF and IL-18 can enhance the predictive efficacy of prognosis for sepsis patients.