Discussion of Study Findings
In the article’s discussion section, the authors focus on acute myocardial infarction (AMI), other studies’ findings, and how the current research contributes to the field by discovering biomarkers. As defined by the authors, AMI is a necrotic condition with an elevated morbidity and death rate that is brought on by an unstable ischemia state (Kang et al., 2023). The mortality rate and severity of AMI can decrease with early detection and treatment (Kang et al., 2023).
Researchers looked into AMI statistics based on the GEO database to find possibly useful biomarkers (Kang et al., 2023). A total of 272 differentially expressed miRNAs and 92 differentially expressed mRNAs were identified in this investigation (Kang et al., 2023). Based on scale data of 17,044 mRNAs, random forests (RF) evaluation of 26 target differentially expressed mRNAs yielded five critical differentially expressed mRNA biomarkers (Kang et al., 2023).
Random forests, decision trees (DT), and support vector machines (SVM) were used to build classification diagnosis models. The mentioned tools have receiver operating characteristic (ROC) curves with area under curves (AUC) of 0.922, 0.962, and 0.880, respectively (Kang et al., 2023). Moreover, the random forest model has the most fantastic accuracy (Kang et al., 2023).
According to these findings, the mentioned model has a high diagnostic value and may aid in the early detection of AMI (Kang et al., 2023). Additionally, researchers identified five important biomarkers linked to immune cells (Kang et al., 2023). The discovery of novel molecular biomarkers offers possible avenues for further investigation into the molecular causes of AMI.
Limitations
However, there are certain limitations to this study, which the authors emphasize. The study’s data were all taken from open-access databases and were not validated using clinical samples (Kang et al., 2023). Therefore, clinical samples must be gathered to conduct additional studies in the future. Similarly unknown are the precise functions of the identified significant mRNA biomarkers, associated biological pathways, and miRNAs in AMI (Kang et al., 2023). Thus, additional in vitro research is necessary to comprehend the molecular mechanism of AMI.
References
Kang, L., Zhao, Q., Jiang, K., Yu, X., Chao, H., Yin, L., & Wang, Y. (2023). Uncovering potential diagnostic biomarkers of acute myocardial infarction based on machine learning and analyzing its relationship with immune cells. BMC Cardiovascular Disorders, 23(1), 1-12. Web.