Reviews in cardiovascular medicine最新文献

Sleep is a fundamental phenomenon that helps maintain normal physiological processes. Conversely, sleep disorders, usually presented as insomnia, are a common public health problem that can lead to multiple pathophysiological changes in humans, including lipid metabolic abnormality. Interestingly, several previous studies have examined the potential relation of insomnia to metabolic syndrome and hyperlipidemia and found that insomnia was associated with elevated plasma cholesterol and triglyceride concentrations. This review summarizes evidence regarding the linkage between insomnia and lipid abnormalities. Moreover, the underlying physiologic mechanisms linking insomnia to lipid abnormalities are systemically discussed. Finally, issues with lipid-lowering drugs and the risk of insomnia are also presented. This knowledge can improve our understanding of the pathophysiological features of insomnia, which may help to prevent and treat insomnia-induced dyslipidemia clinically.

Inherited cardiac arrhythmias, which may lead to sudden cardiac death, represent a significant health risk, with genetic factors playing a key role in their development. The ankyrin 2 (ANK2) gene, encoding ankyrin-B, is implicated in several heritable arrhythmia syndromes. ANK2 variants have been linked to an inherited condition known as "ankyrin-B syndrome", which manifests as a spectrum of cardiac arrhythmias and cardiomyopathy. Our current review examines the relationship between ANK2 variants and specific heart conditions, summarizing recent findings on the genetic and molecular mechanisms underlying ANK2-related arrhythmias and structural abnormalities. By emphasizing the need for further research, this review aims to enhance understanding of ANK2's role in heart disease and guide the development of effective therapies.

Dilated cardiomyopathy (DCM) is the ultimate manifestation of the myocardial response to various genetic and environmental changes and is characterized mainly by impaired left ventricular systolic and diastolic function. DCM can ultimately lead to heart failure, ventricular arrhythmia (VA), and sudden cardiac death (SCD), making it a primary indication for heart transplantation. With advancements in modern medicine, several novel techniques for evaluating myocardial involvement and disease severity from diverse perspectives have been developed. Myocardial fibrosis is a significant contributor to VA events and SCD. Based on different pathological mechanisms, myocardial fibrosis can be categorized into replacement and interstitial forms. Late gadolinium enhancement (LGE) derived from cardiovascular magnetic resonance is the clinical gold standard for evaluating replacement myocardial fibrosis and exhibits high concordance with histological replacement fibrosis. However, because of the absence of normal tissue as a control, the LGE technique often fails to effectively visualize diffuse interstitial fibrosis. In such cases, T1 mapping and extracellular volume fraction mapping can be complementary or alternative methods to the LGE technique for detecting interstitial fibrosis. This review aimed to provide a comprehensive and precise assessment of myocardial fibrosis and to determine the use of cardiac magnetic resonance imaging for prognostic evaluation and risk stratification of patients with DCM.

With the aging of the general population and the rise in surgical and transcatheter aortic valve replacement, there will be an increase in the prevalence of prosthetic aortic valves. Patients with prosthetic aortic valves can develop a wide range of unique pathologies compared to the general population. Accurate diagnosis is necessary in this population to generate a comprehensive treatment plan. Transthoracic echocardiography is often insufficient alone to diagnose many prosthetic valve pathologies. The integration of many imaging modalities, including transthoracic echocardiography, transesophageal echocardiography, cardiac computed tomography, cardiac magnetic resonance imaging, and nuclear imaging, is necessary to care for patients with prosthetic valves. The purpose of this review is to describe the strengths, limitations, and contemporary use of the different imaging modalities necessary to diagnose prosthetic valve dysfunction.

The evolution of left ventricular assist devices (LVADs) from large, pulsatile systems to compact, continuous-flow pumps has significantly improved implantation outcomes and patient mobility. Minimally invasive surgical techniques have emerged that offer reduced morbidity and enhanced recovery for LVAD recipients. Innovations in wireless power transfer technologies aim to mitigate driveline-related complications, enhancing patient safety and quality of life. Pediatric ventricular assist devices (VADs) remain a critical unmet need; challenges in developing pediatric VADs include device sizing and managing congenital heart disease. Advances in LVAD technology adapted for use in right ventricular assist devices (RVADs) make possible the effective management of right ventricular failure in patients with acute cardiac conditions or congenital heart defects. To address disparities in mechanical circulatory support (MCS) access, cost-effective VAD designs have been developed internationally. The Vitalmex device from Mexico City combines pulsatile-flow technology with a paracorporeal design, utilizing cost-effective materials like silicone-elastic and titanium, and features a reusable pump housing to minimize manufacturing and operational costs. Romanian researchers have used advanced mathematical modeling and three-dimensional (3D) printing to produce a rim-driven, hubless axial-flow pump, achieving efficient blood flow with a compact design that includes a wireless power supply to reduce infection risk. In conclusion, MCS continues to advance with technological innovation and global collaboration. Ongoing efforts are essential to optimize outcomes, expand indications, and improve access to life-saving therapies worldwide.

Background: To study the risk of cardiovascular disease (CVD) and other competing causes of death in older kidney cancer patients.

Methods: Data on older patients (aged 65 and above) diagnosed with kidney cancer between 1975 and 2018 were extracted from the Surveillance, Epidemiology, and End Results (SEER) database. We delved into the distribution of CVD and other competing causes of death across the entire cohort and in various patient subgroups. The competing risk analysis was used to produce cumulative mortality curves based on cumulative mortality for the primary outcomes by follow-up period. Utilizing the standardized mortality ratios (SMRs) and absolute excess risks (AERs), we contrasted the risk of CVD and other competing causes of death in older kidney cancer patients to that observed in the general population.

Results: The analysis included 29,349 older kidney cancer patients, of which included 4563 CVD deaths. As survival time extended, the proportion of non-cancer deaths increased in older kidney cancer patients, with CVD accounting for the largest share of non-cancer deaths. At 10-15 years after diagnosis, cumulative non-cancer mortality exceeded primary kidney cancer as the predominant cause of death, and cumulative CVD mortality is higher among all non-cancer causes. Older kidney cancer patients exhibited a greater risk of CVD and other non-cancer deaths than their counterparts in the general older population did (SMR: 1.38-2.81; AER: 1.1-143.69).

Conclusions: As survival time increases, the risk of non-cancer death in older kidney cancer patients gradually surpassed that of primary cancer, and CVD death accounted for the majority of non-cancer deaths. Among older kidney cancer patients, the risk of CVD mortality was higher than in the general population. Managing non-cancer deaths, especially CVD deaths, should be a focus in the care of older kidney cancer patients.

Background: Exercise-based cardiac rehabilitation programs (CRP) are recommended for patients following acute coronary syndrome to potentially improve high-density lipoprotein cholesterol (HDL-C) levels and prognosis. However, not all patients reach target HDL-C levels. Here we analyze the dynamics and predictors of HDL-C increase during CRP in patients following ST-segment elevation myocardial infarction or occlusion myocardial infarction.

Methods: We conducted a prospective study of myocardial infarction patients who completed exercise-based Phase 2 CRP. Data was collected on clinical variables, cardiovascular risk factors, treatment goals, pharmacological therapy, and health outcomes through questionnaires at the beginning and at the end of Phase 2 CRP. Lipid profile analysis was performed before discharge, 4 to 6 weeks after discharge, and at the end of Phase 2 CRP. Changes in lipid profiles were evaluated, and predictors of failure to increase HDL-C levels were identified by binary logistic regression analysis.

Results: Our cohort comprised 121 patients (mean age 61.67 ± 10.97 years, 86.8% male, and 47.9% smokers before admission). A significant decrease in total cholesterol, triglycerides, and low-density lipoprotein cholesterol (LDL-C) were noted, along with an increase in HDL-C (43.87 ± 9.18 vs. 39.8 ± 10.03 mg/dL, p < 0.001). Patients achieving normal HDL-C levels (>40 mg/dL in men and >50 mg/dL in women) significantly increased from 34.7% at admission to 52.9% the end of Phase 2. Multivariable analysis revealed smoking history (hazard ratio [HR] = 0.35, 95% confidence interval [CI], 0.11-0.96, p = 0.04), increased reduction in total cholesterol (HR = 0.94, 95% CI, 0.89-0.98, p = 0.004), and increased reduction in LDL-C (HR = 0.94, 95% CI, 0.89-0.99, p = 0.01) were inversely associated with failure to increase HDL-C levels. Conversely, higher HDL-C before CRP (HR = 1.15, 95% CI, 1.07-1.23, p < 0.001) and increased lipoprotein (a) (HR = 1.01, 95% CI, 1-1.02, p = 0.04) predicted failure to increase HDL-C levels. No significant correlations were found with Mediterranean diet adherence, weekly physical activity, training modalities, or physical fitness parameters.

Conclusions: Participation in an exercise-based Phase 2 CRP led to mild but significant increases in HDL-C. Smoking history and patients experiencing substantial reductions in total cholesterol and LDL-C were more likely to experience HDL-C increases, unlike those with higher HDL-C and lipoprotein (a) levels before CRP.

Background: This study aimed to develop and validate a predictive model for major depression risk in adult patients with coronary heart disease (CHD), offering evidence for targeted prevention and intervention.

Methods: Using data from the National Health and Nutrition Examination Survey (NHANES) from 2005 to 2018, 1098 adults with CHD were included. A weighted logistic regression model was applied to construct and validate a nomogram-based prediction tool for major depression in this population.

Results: The weighted prevalence of major depression among these patients was 13.95%. Multivariate weighted logistic regression revealed that waist circumference, smoking status, arthritis, sleep disorders, and restricted work capacity were independent risk factors for major depression (odds ratio (OR) >1, p < 0.05). The areas under the receiver operating characteristic (ROC) curve in the nomogram model for both the development and validation cohorts were 0.816 (95% confidence interval (CI): 0.776-0.857) and 0.765 (95% CI: 0.699-0.832), respectively, indicating the model possessed strong discriminative ability. Brier scores in the development and validation cohorts were 0.107 and 0.127, respectively, both well below the 0.25 threshold, demonstrating good calibration. Decision curve analysis (DCA) showed that when the threshold probability for major depression ranged from 0.04 to 0.54 in the development group and from 0.08 to 0.52 in the validation group, the nomogram provided the highest clinical net benefit compared to "Treat All" and "Treat None" strategies, confirming its strong clinical utility.

Conclusions: With a weighted prevalence of 13.95%, this nomogram model shows excellent predictive performance and clinical relevance for predicting major depression risk in patients with CHD. Thus, the model can be applied to aid healthcare professionals in identifying high-risk individuals and implementing targeted preventive strategies, potentially lowering the incidence of major depression in this patient population.

Background: Postpartum cardiomyopathy is defined as an incident of acute heart failure in the postpartum period in the absence of any other cause. Up to 10% of postpartum cardiomyopathy may need to undergo heart transplantation later in life. This study aimed to provide a present-day perspective on all-cause mortality and transplant-related complications after heart transplantation for postpartum cardiomyopathy.

Methods: A retrospective analysis of the United Network for Organ Sharing (UNOS) registry was performed for adult patients undergoing heart transplants (01/2001-01/2023) for postpartum cardiomyopathy.

Results: A total of 677 patients were identified, with a mean age of 35 years. The mean body mass index (BMI) was 27.2 kg/m²; the most common comorbidity was type 2 diabetes (T2D) (n = 589; 87%). Older age was associated with lower overall mortality (hazard ratio (HR): 0.97; 95% CI: 0.95, 0.98; p < 0.01), while diabetes (HR: 1.01; 95% CI: 1.01, 1.01; p < 0.01), dialysis (HR: 1.01; 95% CI: 1.01, 1.01; p < 0.01), days on Status 1 on the UNOS registry (HR: 1.06; 95% CI: 1.03, 10.9; p < 0.01), creatinine (HR: 1.29; 95% CI: 1.02, 1.64; p = 0.034), and length of stay (HR: 1.01; 95% CI: 1.01, 1.02; p = 0.02) were associated with a higher risk of overall mortality. Moreover, 30-day mortality was 2.8%, and 1-year mortality was 11.1%. The era effect was prominent in cases of 1-year mortality (odds ratio (OR): 0.95; 95% CI: 0.91, 0.99, p = 0.006).

Conclusions: Our results suggest that younger age, diabetes, pretransplant dialysis, days on Status 1, and creatinine are associated with higher mortality, while an era effect was observed for 1-year mortality after heart transplantation (HTx) in patients with postpartum cardiomyopathy.

Background: Heart failure (HF) remains a global challenge with disappointing long-term outcomes. Malnutrition is prevalent in patients with HF and disrupts the equilibrium of immune and inflammatory responses, resulting in further deterioration of the HF. Novel indicators emerge as immune nutrition indices, including the prognostic nutritional index (PNI), neutrophil-to-lymphocyte ratio (NLR), Controlling Nutritional Status (CONUT) score, and cholesterol-modified prognostic nutritional index (CPNI). This study examines the correlation between immune nutrition indices and all-cause and cardiovascular mortality in patients with HF.

Methods: The data source for this study was the National Health and Nutrition Examination Survey (NHANES). A total of 1232 participants with HF were included. Weighted Cox proportional hazards models were employed to assess the independent association of different immune nutrition indices with mortality risk, alongside subgroup analyses and Kaplan-Meier survival curves. Restricted cubic spline analysis was utilized to clarify the detailed association between immune nutrition indices and hazard ratio (HR). A time-dependent receiver operating characteristic curve analysis was conducted to assess the predictive ability.

Results: After full adjustments, PNI is independently related to all-cause mortality (HR = 0.94, 95% CI: 0.92-0.97) and cardiovascular mortality (HR = 0.94, 95% CI: 0.90-0.99). CPNI, CONUT, and NLR also showed an independent association with the prognosis of HF. Time-dependent receiver operating characteristic curve analysis indicated that PNI exhibited the highest predictive power for mortality among the CPNI, CONUT, and NLR indexes.

Conclusions: Our study revealed that immune nutrition indicators, including CPNI, could predict all-cause mortality and cardiovascular mortality in the HF population. Compared with other indicators, PNI is the most effective predictor.