Value of constructing a non-invasive diagnostic model based on serum heme oxygenase-1 and glucose regulatory protein 78 for non-alcoholic fatty liver disease

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Objective: To analyze the clinical application value of serum heme oxygenase (HO)-1expression level in non-alcoholic fatty liver disease (NAFLD) and, based on that, establish a diagnostic model combined with glucose regulatory protein 78 (GRP78) so as to clarify its diagnostic effectiveness and application value. Methods: A total of 210 NAFLD patients diagnosed by abdominal B-ultrasound and liver elastography were included, and at the same time, 170 healthy controls were enrolled. The general clinical data, peripheral blood cell counts, and biochemical indicators of the research subjects were collected. The expression levels of HO-1 and GRP78 were detected using an enzyme-linked immunosorbent assay. Multivariate analysis was used to screen independent risk factors for NAFLD. Visual output was performed through nomogram diagrams, and the diagnostic model was constructed. Receiver operating characteristic curve (ROC), calibration curve, and decision curve analysis (DCA) were used to evaluate the diagnostic effectiveness of NAFLD. Measurement data were analyzed using a t-test or Mann-Whitney U rank sum test to detect data differences between groups. Enumeration data were analyzed using the Fisher's exact probability test or the Pearson χ(2) test. Results: Compared with the healthy control group, the white blood cell count, aspartate aminotransferase (AST), alanine aminotransferase, gamma-glutamyl transferase (GTT), fasting blood glucose (Glu), triglyceride (TG), low-density lipoprotein cholesterol (LDL-C), serum HO-1, and GRP78 levels were significantly increased in the NAFLD group patients (P < 0.05). Binary logistic analysis results showed that AST, TG, LDL-C, serum HO-1, and GRP78 were independent risk factors for NAFLD (P < 0.05). A nomogram clinical predictive model HGATL was established using HO-1 (H), GRP78 (G) combined with AST (A), TG (T), and LDL-C (L), with the formula P=-21.469+3.621×HO-1+0.116 ×GRP78+0.674×AST+6.250×TG+4.122 ×LDL-C. The results confirmed that the area under the ROC curve of the HGATL model was 0.965 8, with an optimal cutoff value of 81.69, a sensitivity of 87.06%, a specificity of 92.82%, a P < 0.05, and the diagnostic effectiveness significantly higher than that of a single indicator. The calibration curve and DCA both showed that the model had good diagnostic performance. Conclusion: The HGATL model can be used as a novel, non-invasive diagnosis model for NAFLD and has a positive application value in NAFLD diagnosis and therapeutic effect evaluation. Therefore, it should be explored and promoted in clinical applications.