Differences in the 2020 ESC Versus 2015 ESC and 2014 ACC/AHA Guidelines on the Management of Acute Coronary Syndromes in Patients Presenting Without Persistent ST-Segment Elevation

Effect of stress-induced hyperglycemia on long-term mortality in non-diabetic patients with acute type A aortic dissection: a retrospective analysis

BACKGROUND

Acute Type A Aortic Dissection (AAAD) is one of the most life-threatening diseases, often associated with transient hyperglycemia induced by acute physiological stress. The impact of stress-induced hyperglycemia on the prognosis of ST-segment elevation myocardial infarction has been reported. However, the relationship between stress-induced hyperglycemia and the prognosis of AAAD patients remains uncertain.

METHODS

The clinical data of 456 patients with acute type A aortic dissection were retrospectively reviewed. Patients were divided into two groups based on their admission blood glucose. Cox model regression analysis was performed to assess the relationship between stress-induced hyperglycemia and the 30-day and 1-year mortality rates of these patients.

RESULTS

Among the 456 patients, 149 cases (32.7%) had AAAD combined with stress-induced hyperglycemia (SIH). The results of the multifactor regression analysis of the Cox model indicated that hyperglycemia (RR = 1.505, 95% CI: 1.046-2.165, p = 0.028), aortic coarctation involving renal arteries (RR = 3.330, 95% CI: 2.237-4.957, p < 0.001), aortic coarctation involving superior mesenteric arteries (RR = 1.611, 95% CI: 1.056-2.455, p = 0.027), and aortic coarctation involving iliac arteries (RR = 2.034, 95% CI: 1.364-3.035, p = 0.001) were independent influences on 1-year postoperative mortality in AAAD patients.

CONCLUSION

The current findings indicate that stress-induced hyperglycemia measured on admission is strongly associated with 1-year mortality in patients with AAAD. Furthermore, stress-induced hyperglycemia may be related to the severity of the condition in patients with AAAD.

Development and validation of a machine learning-based readmission risk prediction model for non-ST elevation myocardial infarction patients after percutaneous coronary intervention

To investigate the factors that influence readmissions in patients with acute non-ST elevation myocardial infarction (NSTEMI) after percutaneous coronary intervention (PCI) by using multiple machine learning (ML) methods to establish a predictive model. In this study, 1576 NSTEMI patients who were hospitalized at the Affiliated Hospital of North Sichuan Medical College were selected as the research subjects. They were divided into two groups: the readmitted group and the non-readmitted group. The division was based on whether the patients experienced complications or another incident of myocardial infarction within one year after undergoing PCI. Common variables selected by univariate and multivariate logistic regression, LASSO regression, and random forest were used as independent influencing factors for NSTEMI patients' readmissions after PCI. Six different ML models were constructed using these common variables. The area under the ROC curve, accuracy, sensitivity, and specificity were used to evaluate the performance of the six ML models. Finally, the optimal model was selected, and a nomogram was created to visually represent its clinical effectiveness. Three different methods were used to select seven representative common variables. These variables were then utilized to construct six different ML models, which were subsequently compared. The findings indicated that the LR model exhibited the most optimal performance in terms of AUC, accuracy, sensitivity, and specificity. The outcome, admission mode (walking and non-walking), communication ability, CRP, TC, HDL, and LDL were identified as independent predicators of readmissions in NSTEMI patients after PCI. The prediction model constructed by the LR algorithm was the best. The established column graph model established proved to be effective in identifying high-risk groups with high accuracy and differentiation. It holds a specific predictive value for the occurrence of readmissions after direct PCI in NSTEMI patients.

Gender Disparities in Patients' Decisions about the Management of Myocardial Infarction in East Chinese Province

Background

Previous studies showed that there are gender disparities in various respects of acute myocardial infarction (AMI), including risk factors, symptoms, and outcomes. However, few of them noticed the gender disparities in patients' decision about the management of AMI, which might also be associated with the outcome.

Aims

To identify gender disparities in patients' decisions about the management of myocardial infarction.

Methods

In this cohort study, the critical time points including the time of symptom onset, visiting hospital, diagnosis of AMI, consent to coronary angiography (CAG), beginning of CAG, and balloon dilation were recorded. Medication and major adverse cardiac event (MACE) within 6 months were also recorded.

Results

Female patients took more time from symptom onset to visiting hospital (P = 0.001), from diagnosis of AMI to consent to CAG (P < 0.05), and from door to needle/balloon than male (P < 0.05). Less female patients accepted CAG (P < 0.05) and coronary intervention/bypass grafting (P < 0.05). Less female patients kept good inherence to antiplatelet therapy (P < 0.05) and statins (P < 0.05) than male, more female preferred traditional Chinese medicine (TCM) than male patient (P < 0.05), and most of them had MACE within 6 months (P < 0.05). Patients' good adherence to antiplatelet therapy and statins and accepting coronary intervention/bypass grafting were associated with a reduced risk of MACE.

Conclusion

Female patients were more reluctant to make decisions about emergency management of AMI and tended to choose conservative treatment. More female patients preferred TCM than evidence-based medicine. Their reluctance about the critical management of AMI and poor adherence to evidence-based medicine were associated with an elevated risk of MACE.

Nanoparticle Based Cardiac Specific Drug Delivery

Heart failure secondary to myocardial injuries is a leading cause of death worldwide. Recently, a growing number of novel therapies have emerged for injured myocardium repairment. However, delivering therapeutic agents specifically to the injured heart remains a significant challenge. Nanoparticles are the most commonly used vehicles for targeted drug delivery. Various nanoparticles have been synthesized to deliver drugs and other therapeutic molecules to the injured heart via passive or active targeting approaches, and their targeting specificity and therapeutic efficacies have been investigated. Here, we summarized nanoparticle-based, cardiac-specific drug delivery systems, their potency for treating heart diseases, and the mechanisms underlying these cardiac-targeting strategies. We also discussed the clinical studies that have employed nanoparticle-based cardiac-specific drug delivery.

The prognostic utility of GRACE risk score in predictive adverse cardiovascular outcomes in patients with NSTEMI and multivessel disease

BACKGROUND

GRACE risk score models are capable of predicting all-cause mortality of non-ST elevation myocardial infarction (NSTEMI) patients. However, its utility for evaluating major adverse cardiovascular events (MACE) in NSTEMI patients with multivessel disease (MVD) remains unclear.

METHODS AND RESULTS

This study was designed as a retrospective cohort study that recruited patients with NSTEMI and multivessel disease between September 2013 and December 2018 in Daping Hospital, Chongqing, China. The primary outcome was a composite outcome that included all-cause mortality, recurrent angina, non-fatal myocardial infarction, coronary re-vascularization, and non-fatal strokes. Of the 827 patients with NSTEMI, 32 did not complete follow-up and 430 were excluded because of single-vessel disease. The remaining 365 NSTEMI patients with MVD had a median follow-up of 3.0 (IQR 2.6-3.3) years, 78 patients experienced outcomes. The GRACE risk score predicted the MACE (hazard ratio 1.014, 95% CI 1.006-1.021, P < 0.001). The GRACE risk score performed well in predicting all-cause mortality (c-statistic 0.72, 95% CI 0.59-0.85, P = 0.001) in MVD but was less powerful in predicting MACE (c-statistic 0.69, 95% CI 0.62-0.75, P < 0.001). When combining the GRACE risk score with the SYNTAX score, and blood urea nitrogen for predicting all-cause mortality and MACE events, the c-statistic value increased to 0.82 and 0.81 (P < 0.001).

CONCLUSION

In NSTEMI patients with MVD, the GRACE score showed an acceptable predictive value for all-cause mortality, but it was less powerful in predicting MACE. Blood urea nitrogen may be valuable in assessing long-term cardiovascular events in patients with MVD.

Body Mass Index Is Independently Associated with the Presence of Ischemia in Myocardial Perfusion Imaging

Background and Objectives: Obesity has been linked to various cardiovascular risk factors, increased incidence of coronary artery disease, and myocardial perfusion defects. The aim of this study was to investigate if body mass index (BMI) and waist circumference (WC) were associated with myocardial perfusion defects. Materials and Methods: A total of 308 consecutive patients who had myocardial perfusion imaging (MPI) with single photon emission computed tomography (SPECT) and a complete medical record on file were studied retrospectively. Results: The median age was 69 (61−76) years, the BMI was 27.6 (24.4−30.7) kg/m2, and the WC was 110 (102−118) cm. Of the 308 patients, 239 patients (77.6%) had myocardial ischemia. A positive test for ischemia was more frequent in men compared to women (72 vs. 28%, p < 0.001). Within the male group, BMI and WC were not significantly different between the ischemia and non-ischemia groups. In contrast, within the female group, both BMI (30.2 vs. 27.1 kg/m2, p = 0.002) and WC (112 vs. 105.5 cm, p = 0.020) were significantly higher in the ischemia group. Multivariable logistic regression showed that male sex and BMI were the only two independent predictors of ischemia in our patient population. Conclusions: This study showed that BMI was an independent predictor of ischemia in our patient population.

Impact of multicomponent integrated care on mortality and hospitalization after acute coronary syndrome: a systematic review and meta-analysis

AIMS

Multicomponent integrated care is associated with sustained control of multiple cardiometabolic risk factors among patients with type 2 diabetes. There is a lack of data in patients with acute coronary syndrome (ACS). We aimed to examine its efficacy on mortality and hospitalization outcomes among patients with ACS in outpatient settings.

METHODS AND RESULTS

A literature search was conducted on PubMed, EMBASE, Ovid and Cochrane library databases for randomized controlled trials, published in English language between January 1980 and November 2020. Multicomponent integrated care defined as two or more quality improvement strategies targeting different domains (the healthcare system, healthcare providers and patients) for one month or more. The study outcomes were all-cause and cardiovascular-related mortality, hospitalization and emergency department visits. We pooled the risk ratio (RR) with 95% confidence interval (CI) for the association between multicomponent integrated care and study outcomes using the Mantel-Haenszel test. 74 trials (n = 93,278 patients with ACS) were eligible. The most common quality improvement strategies were team change (83.8%), patient education (62.2%) and facilitated patient-provider relay (54.1%). Compared with usual care, multicomponent integrated care was associated with reduced risks for all-cause mortality (RR 0.83, 95% CI 0.77-0.90; p<0.001; I2 = 0%), cardiovascular mortality (RR 0.81, 95% CI 0.73-0.89; p<0.001; I2 = 24%) and all-cause hospitalization (RR 0.88, 95% CI, 0.78-0.99; p = 0.040; I2 = 58%). The associations of multicomponent integrated care with cardiovascular-related hospitalization, emergency department visits and unplanned outpatient visits were not statistically significant.

CONCLUSIONS

In outpatient settings, multicomponent integrated care can reduce risks for mortality and hospitalization in patients with ACS.