Dyslipidemia is one of the most important factors for coronary artery disease (CAD). Atherogenic index of plasma (AIP) is a novel indicator involved in dyslipidemia. However, the relation between AIP and CAD in postmenopausal women remains unclear. We hypotheses that AIP is a strong predictive indicator of CAD in postmenopausal women. A propensity score matching case–control study including 348 postmenopausal CAD cases and 348 controls was conducted in the present study. Compared with controls, CAD patients had higher levels of total cholesterol (TC), triglyceride (TG), low-density lipoprotein cholesterol (LDL-C) and apolipoprotein B (APOB), but lower high-density lipoprotein cholesterol (HDL-C) and apolipoprotein A-1 (APOA-1). The values of nontraditional lipid profiles, including non-HDL-C, TC/HDL-C, LDL-C/HDL-C, non-HDL-C/HDL-C (atherogenic index, AI), TC∗TG∗LDL/HDL-C (lipoprotein combine index, LCI), log(TG/HDL-C) (atherogenic index of plasma, AIP) and APOB/APOA-1 were all significantly higher in the CAD patients. The results of Pearson correlation analyses showed AIP was positively and significantly correlated with TC (r = 0.092, P < 0.001), TG (r = 0.775, P = 0.015), APOB (r = 0.140, P < 0.001), non-HDL-C (r = 0.295, P < 0.001), TC/HDL-C (r = 0.626, P < 0.001), LDL-C/HDL-C (r = 0.469, P < 0.001), AI (r = 0.626, P < 0.001), LCI (r = 0.665, P < 0.001), APOB/APOA-1(r = 0.290, P < 0.001) and was negatively correlated with APOA-1 (r = − 0.278, P < 0.001) and HDL-C (r = − 0.665, P < 0.001). In the multivariate logistic regression analysis, AIP was an independent predictor of CAD. After adjusting for the traditional clinical prognostic factors including diabetes and hypertension, we found AIP could be an independent risk factor for CAD (odds ratio [OR], 3.290; 95% confidence interval [CI], 1.842–5.877, P < 0.001). After adjusting for multiple clinical factors include diabetes, hypertension, smoking, heart ratio, fasting blood glucose, we found AIP also could a powerful risk factor, OR = 3.619, 95%CI (2.003–6.538), P < 0.001. The present study indicated that AIP might be a strong marker for predicting the risk of CAD in postmenopausal women.

Objective: Gensini score is an effective tool used to evaluate the severity of coronary artery disease (CAD). Whether the Gensini score has predictive value for the clinical outcomes of patients with CAD after percutaneous coronary intervention (PCI) has not been investigated.Methods: All patients were from the Clinical Outcomes and Risk Factors of Patients with Coronary Heart Disease after PCI (CORFCHD-PCI), a retrospective cohort study involving 5,672 patients with CAD who underwent PCI, such as 2,110 patients with diabetes and 3,562 patients without diabetes, from January 2008 to December 2017. Patients were divided into three groups according to the tertile of Gensini score: first tertile (Gensini score 38 points). The median follow-up time was 31.0 (interquartile range, IQR: 30.0) months. Compared the differences in clinical outcomes between the groups. Multivariate Cox regression analyses were performed to assess the predictive value of the Gensini score for outcomes over up to 10 years of follow-up.Results: In the population without diabetes, there were significant differences between the three groups in the incidences of all-cause mortality (ACM, p = 0.048), cardiac mortality (CM, p = 0.024), major adverse cardiovascular (CV) events (MACEs, p = 0.006), and major adverse cardiovascular and cerebrovascular events (MACCEs, p = 0.009). In the population with diabetes, there were significant differences between the three groups in the incidences of ACM, CM, MACEs, and MACCEs (all p < 0.001). After multivariate Cox regression analyses, in the population without diabetes, the respective risks of ACM, CM, MACEs, and MACCEs were increased 89.9% [hazard ratio (HR) = 1.899, 95% CI: 1.285–2.807, p = 0.001], 115.1% (HR = 2.151, 95% CI: 1.378–3.356, p = 0.001), 48.1% (HR = 1.481, 95% CI: 1.152–1.904, p = 0.002), and 49.8% (HR = 1.498, 95% CI: 1.176–1.907, p = 0.001) in the third tertile compared with those in the first tertile. In the population with diabetes, the respective risks of ACM, CM, MACEs, and MACCEs were increased 248.5% (HR = 3.485, 95% CI: 1.973–6.154, p < 0.001), 260.4% (HR = 3.604, 95% CI: 1.866–6.963, p < 0.001), 130.2% (HR = 2.302, 95% CI: 1.649–3.215, p < 0.001), and 119.8% (HR = 2.198, 95% CI: 1.600–3.018, p < 0.001) in the third tertile compared with those in the first tertile.Conclusion: The present study indicated that the Gensini score is an independent predictor of long-term adverse outcomes in patients with CAD who underwent PCI, and it has more predictive value in the population with diabetes.

SARS-CoV-2 is the virus responsible for the ongoing COVID-19 outbreak. The virus uses ACE2 receptor for viral entry. ACE2 is part of the counter-regulatory renin-angiotensin-aldosterone system and is also expressed in the lower respiratory tract along the alveolar epithelium. There is, however, significant controversy regarding the role of ACE2 expression in COVID-19 pathogenesis. Some have argued that decreasing ACE2 expression would result in decreased susceptibility to the virus by decreasing available binding sites for SARS-CoV-2 and restricting viral entry into the cells. Others have argued that, like the pathogenesis of other viral pneumonias, including those stemming from previous severe acute respiratory syndrome (SARS) viruses, once SARS-CoV-2 binds to ACE2, it downregulates ACE2 expression. Lack of the favourable effects of ACE2 might exaggerate lung injury by a variety of mechanisms. In order to help address this controversy, we conducted a literature search and review of relevant preclinical and clinical publications pertaining to SARS-CoV-2, COVID-19, ACE2, viral pneumonia, SARS, acute respiratory distress syndrome and lung injury. Our review suggests, although controversial, that patients at increased susceptibility to COVID-19 complications may have reduced baseline ACE2, and by modulating ACE2 expression one can possibly improve COVID-19 outcomes. Herein, we elucidate why and how this potential mechanism might work.

Background: The hemoglobin level and red cell distribution width (RDW) have been linked to the prognosis of coronary atherosclerotic heart disease (CAHD). However, the relationship between the ratio of hemoglobin to the RDW (HRR) and clinical outcomes after percutaneous coronary intervention (PCI) is not known. Here, we explored the impact of the HRR on clinical outcomes after PCI.Methods: In our study, we selected 6,046 CAHD patients with PCI hospitalized in the First Affiliated Hospital of Xinjiang Medical University from 2008 to 2016. The patients were grouped according to their HRR ratio: group A (HRR < 10.25, n = 2,344) and group B (HRR ≥ 10.25, n = 3,702). The difference in clinical outcomes between the two groups was compared. Patients were followed up for 35.9 ± 22.6 months.Results: Three hundred nine patients died during follow-up. These included 166 patients (7.1%) in the HRR < 10.25 group and 143 patients (3.9%) in the HRR ≥ 10.25 group (P < 0.001). The incidences of cardiogenic death (5.7 vs. 3.2%) and major cardiovascular adverse events (16.5 vs. 12.9%) also differed significantly between the groups (both Ps < 0.001). Analysis using the multivariate Cox proportional hazard model found a significant association between a decreased HRR and post-PCI mortality (all-cause death, adjusted HR: 1.479, 95% CI: 1.156–1.893, p = 0.002; cardiac death, adjusted HR: 1.470, 95% CI: 1.116–1.936, p = 0.006).Conclusion: The HRR is predictive of post-PCI mortality among CAHD patients.