A Nomogram model for predicting the occurrence of no-reflow phenomenon after percutaneous coronary intervention using the lncRNA /miR-30e/ biomarkers.

Background: Studies have shown that percutaneous coronary intervention (PCI) is considered as the essential therapeutic strategy for the patients with ST-segment elevation myocardial infarction (STEMI). However; no-reflow could still occur in a few patients after PCI. Studies have reported that biomarkers related to no-reflow pathogenetic components could play a prognostic role in the prediction phenomenon. Hence, this study explored the establishment of nomogram model for predicting the occurrence of no-reflow phenomenon after PCI using the lncRNA /miR-30e/ biomarkers in patients with STEMI after PCI.

Methods: In this observational study, a total of 76 STEMI patients who underwent emergency PCI between January 2018 and December 2021were included. The patients after PCI, were divided into reflow (n=44) and no-reflow groups (n=32). The demographic, environmental and clinical risk factors were assessed and analysed between the groups. Quantitative RT-PCR was used to detect , miR-30e, and messenger RNA (mRNA) expression levels in the plasma of patients after PCI. Bioinformatic methods were used to predict the interaction of the plasma /miR-30e/ axis. The risk factors in the no-reflow group were screened using a logistic-regression analysis, and a nomogram prediction model was constructed and validated. Subsequently, a gene set enrichment analysis revealed the function of lncRNA .

Results: Plasma lncRNA and were more highly expressed and miR-30e was more lowly expressed in the no-reflow group than the normal-reflow group (P<0.001). A negative correlation was observed between lncRNA and miR-30e, and between miR-30e and . However, a positive correlation was observed between lncRNA and mRNA. The bioinformatics analysis predicted multiple binding sites on the lncRNA and miR-30e. LncRNA [odds ratio (OR): 0.163, 95% confidence interval (CI): 0.021-0.944] and hs-CRP (OR: 2.151, 95% CI: 1.536-3.974) found to be as independent predictors. The C-index of this prediction model was 0.982 (95% CI: 0.956-1.000).

Conclusions: could function as an effective biomarker for no-reflow among patients with STEMI after PCT and the proposed nomogram may provide information for individualized treatment in patients with STEMI.