CircSamd4: A novel biomarker for predicting vascular calcification.

BACKGROUND: Vascular calcification (VC) is usually associated with cardiovascular diseases (CVDs), which are one of the main causes of mortality in the world. This study aimed to analyze the expression of circular RNAs (circRNAs) in patients with VC and to evaluate biomarkers for the diagnosis of VC. METHODS: Calcified human aortic endothelial cells (HAECs) and the calcification in mouse aorta were detected by qRT-PCR. Subsequently, this was verified in the plasma of patients with coronary artery calcification (CAC). The plasma of 40 patients in the control group and 31 patients in the calcified group were detected by quantitative reverse transcription polymerase chain reaction (qRT-PCR) to detect the level of circSamd4a in the blood. The diagnostic value was evaluated by logistic regression analysis and the working characteristics of subjects. RESULTS: In the HAECs, the qRT-PCR showed a significant decrease in the level of circSamd4a expression in the calcification group compared to the control group (p < 0.05). The calcified mouse aorta showed the same trend for circSamd4a expression, wherein the difference was statistically significant (p < 0.05); the expression of circSamd4a was significantly downregulated in the plasma of patients with VC (p < 0.01). The receiver operating characteristic (ROC) curves of circSamd4a in patients with VC and control group showed that the area under the curve (AUC) was 0.81 (95% CI: 0.707-0.913; p < 0.001). CONCLUSION: CircSamd4a showed a stable downward trend in different specimens, and had significant advantages as a biomarker for diagnosis of VC.

Slow-Reflow and Prognosis in Patients with High Parathyroid Hormone Levels Undergoing Primary Percutaneous Coronary Intervention for Acute ST-Segment Elevation Myocardial Infarction.

We aimed to evaluate the correlation among serum parathyroid hormone (PTH) and slow-reflow during primary percutaneous coronary intervention (PCI) and prognosis in patients with ST-segment elevation myocardial infarction (STEMI). A total of 262 patients were enrolled and divided into a slow-reflow group (n = 61) and a control group (n = 201). PTH was an independent risk factor for slow-reflow (P < 0.05), and the regression model had good discrimination and calibration. ROC curve analysis showed that PTH (≥ 63.65 pg/ml) had a predictive value for slow-reflow (P < 0.001). During the 1-year follow-up, the patients were divided into a PTH-h group (≥ 63.65 pg/ml, n = 100) and a PTH-l group (< 63.65 pg/ml, n = 162). Readmission for HF was independently associated with PTH levels (P < 0.05). KM survival analysis suggested that PTH-h had a predictive value for MACEs, especially for readmission for HF (P < 0.05). PTH levels were associated with slow-reflow during PCI and MACEs during follow-up in patients with STEMI.

PTH Predicts the in-Hospital MACE After Primary Percutaneous Coronary Intervention for Acute ST-Segment Elevation Myocardial Infarction.

Objective: To investigate the correlation between serum parathyroid hormone (PTH) levels and in-hospital major adverse cardiovascular events (MACE) in patients with acute ST-segment elevation myocardial infarction (STEMI) after primary percutaneous coronary intervention (PCI), and establish a risk prediction model based on parameters such as PTH for in-hospital MACE. Methods: This observational retrospective study consecutively enrolled 340 patients who underwent primary PCI for STEMI between January 2016 and December 2020, divided into a MACE group (n=92) and a control group (n=248). The least absolute shrinkage and selection operator (LASSO) and logistic regression analyses were used to determine the risk factors for MACE after primary PCI. The rms package in R-studio statistical software was used to construct a nomogram, to detect the line chart C-index, and to draw a calibration curve. The decision curve analysis (DCA) method was used to evaluate the clinical application value and net benefit. Results: Correlation analysis revealed that PTH level positively correlated with the occurrence of in-hospital MACE. Receiver operating characteristic curve analyses revealed that PTH had a good predictive value for in-hospital MACE. Multivariate logistic regression analysis indicated that Killip class II-IV, and FBG were independently associated with in-hospital MACE after primary PCI. A nomogram model was constructed using the above parameters. The model C-index was 0.894 and the calibration curve indicated that the model was well calibrated. The DCA curve suggested that the nomogram model was better than TIMI score model in terms of net clinical benefit. Conclusion: Serum PTH levels in patients with STEMI are associated with in-hospital MACE after primary PCI, and the nomogram risk prediction model based on PTH demonstrated good predictive ability with obvious clinical practical value.