Roles of ST2, IL-33 and BNP in predicting major adverse cardiovascular events in acute myocardial infarction after percutaneous coronary intervention.

This study investigated roles of serum ST2, IL-33 and BNP in predicting major adverse cardiovascular events (MACEs) in acute myocardial infarction (AMI) after percutaneous coronary intervention (PCI). Blood samples were collected from the included AMI patients (n = 180) who underwent PCI. All patients were divided into the MACEs and MACEs-free groups. Enzyme-linked immunosorbent assay was performed to measure serum levels of ST2, IL-33 and BNP. Severity of coronary artery lesion was evaluated by Gensini score. Pearson correlation analysis was used. A receiver operating characteristics curve was drawn to evaluate the potential roles of ST2, IL-33 and BNP in predicting MACEs, and Kaplan-Meier curve to analyse the 1-year overall survival rate. Logistic regression analysis was conducted to analyse the independent risk factors for MACEs. Compared with the MACEs-free group, the serum levels of ST2, IL-33 and BNP were significantly higher in the MACEs group. Serum levels of ST2, IL-33 and BNP were positively correlated with each other and positively correlated with Gensini score. The area under curves of ST2, IL-33 and BNP, respectively, were 0.872, 0.675 and 0.902. The relative sensitivity and specificity were, respectively, 76.27% and 85.92%, 69.49% and 58.68%, as well as, 96.61% and 77.69%. Serum levels of ST2, IL-33 and BNP were independent risk factors for MACEs. The 1-year overall survival rate was higher in AMI patients with lower serum levels of ST2, IL-33 and BNP. In conclusion, serum levels of ST2, IL-33 and BNP have potential value in predicting MACEs in AMI patients undergoing PCI.

Artificial Intelligence Algorithm-Based Differential Diagnosis of Crohn's Disease and Ulcerative Colitis by CT Image.

The aim of this study was to investigate the effect of low-dose CT enterography (CTE) based on modified guided image filtering (GIF) algorithm in the differential diagnosis of ulcerative colitis (UC) and Crohn's disease (CD). Methods. One hundred and twenty patients with suspected diagnosis of IBD were studied. They were randomly divided into control group (routine CT examination) and observation group (low-dose CTE examination based on improved GIF algorithm), with 60 cases in each group. Comprehensive diagnosis was used as the standard to assess the diagnostic effect. Results. (1) The peak signal-to-noise ratio (PSNR) (26.02 dB) and structural similarity (SSIM) (0.8921) of the algorithm were higher than those of GIF (17.22 dB/0.8491), weighted guided image filtering (WGIF) (23.78 dB/0.8489), and gradient domain guided image filtering (GGIF) (23.77 dB/0.7567) (P < 0.05); (2) the diagnostic sensitivity (91.49%), specificity (92.31%), accuracy (91.67%), positive predictive value (97.73%), and negative predictive value (75%) of the observation group were higher than those of the control group (P < 0.05); the sensitivity and specificity of CTE in the diagnosis of UD and CD were 96.77% and 81.25% and 98.33% and 93.33%, respectively (P < 0.05); there were significant differences in symmetrical intestinal wall thickening and smooth serosal surface between UD and CD (P < 0.05). Conclusion. (1) The improved GIF algorithm has a more effective application value in the denoising processing of low-dose CT images and can better improve the image quality; (2) the accuracy of CTE in the diagnosis of IBD is high, and CTE is of great value in the differential diagnosis of UD and CD.