Current Hypertension Reviews最新文献

Introduction: Type 2 diabetes is a metabolic disorder that is becoming more prevalent over time. Research has shown that the Mediterranean diet (MD) and intermittent fasting (IF) can improve the metabolic parameters of patients with type 2 diabetes. However, there has yet to be a study comparing the effectiveness of these two diets in diabetic patients. This review aims to compare the impact of the Mediterranean diet and intermittent fasting on glycemic, lipid, and anthropometric indices in patients with type 2 diabetes.

Methods: We selected clinical trial studies published between 2013 and 2023 that examined the impact of the MD and the IF diet on glycemic, lipid, and anthropometric indices in patients with type 2 diabetes, in the PubMed and Scopus databases on November 23, 2023, and were included in our study following the PRISMA guidelines.

Results: A total of 22 clinical trials meeting the inclusion criteria were chosen. Out of these, 13 clinical trials focused on the impact of the Mediterranean diet, while the remaining trials examined the effects of the IF diet on type 2 diabetes. The age range of participants in all studies was above 18 years, with the number of individuals investigated ranging from 9 to 557. The duration of the interventions varied from 1 week to 8 years. The MD and IF have both have been shown to effectively improve glycemic control, lipid profiles, and anthropometric measurements in patients with type 2 diabetes. However, the MD tends to offer more consistent and sustainable long-term benefits. This can be attributed to its rich composition of antioxidants, healthy fats, and dietary fiber. IF has demonstrated potential benefits for improving blood sugar levels and lipid profiles over short periods. However, its effectiveness may be compromised by the risk of hypoglycemia and the inconsistent commitment of patients.

Conclusion: These findings suggest that the MD is preferable for long-term, while IF may serve as a complementary short-term strategy. Further research in this area is necessary to provide a definitive opinion.

Hypertension is a chronic medical state and a major determining factor for cardiovascular and renal diseases. Both genetic and non-genetic factors contribute to hypertensive conditions among individuals. The Renin-Angiotensin-Aldosterone System (RAAS) is a major genetic target for the anti-hypertension approach. The majority of classical antihypertensive drugs were mainly focused on the RAAS signaling pathways. Though these antihypertensive drugs control Blood Pressure (BP), they have mild to severe life-threatening effects. Unrevealing effective hypertensive targets for BP management is essential. The effective targets could emerge either from RAAS-dependent or RAAS-independent pathways and/or through the cross-talks among them. Analyzing the physiopathological mechanisms of hypertension has the benefit of understanding the interactions between these systems which helps in better understanding of drug targets and the importance of emergence of novel therapeutics. This review is about the signaling pathways involved in hypertension pathogenesis and their cross-talks and it contributes to a better understanding of the etiology of hypertension.

Hypertension, commonly known as high blood pressure, is a chronic condition characterized by elevated arterial pressure. It occupies a unique position in population health. It is the leading cause of cardiovascular disease and the most common non-communicable condition affecting millions worldwide and is a major public health challenge. The etiology of hypertension involves a complex interplay of environmental and pathophysiological factors alongside genetics, diet, lifestyle, and other coexisting medical conditions. Treatment typically involves medication and lifestyle adjustments such as dietary changes, regular exercise, weight management, and stress reduction to pharmacological interventions involving drugs like diuretics, beta-blockers & ACE inhibitors to lower blood pressure. The pathogenesis of hypertension is linked to endothelial dysfunction, vascular remodelling, sympathetic nervous system activation, and the renin-angiotensin-aldosterone system. Diagnosis is made by measuring blood pressure using a sphygmomanometer, with stages including prehypertension, stage 1 hypertension, and stage 2 hypertension. Effective management of hypertension requires lifestyle modifications such as dietary changes, regular exercise, weight control, and reduced alcohol consumption, alongside pharmacological interventions. As hypertension continues to be a leading cause of death and disability globally, understanding and addressing these factors are crucial for mitigating the widespread impact of hypertension on public health.

Substantial evidence indicates that breastfeeding reduces mortality and morbidity in infants. However, social changes in the 20th century resulted in a considerable decline in breastfeeding rates in many countries. Breast milk is crucial because of its nutritional, immunological, and emotional benefits and economic value. Approximately 10% of pregnancies are complicated by hypertensive syndromes, which are the most commonly diagnosed conditions during pregnancy. This perspective aims to explore how hypertension may interfere with the quality of human breast milk. While numerous studies have investigated the composition of breast milk and its numerous benefits for both infants and mothers, limited research examines the relationship between colostrum, breast milk, and hypertension. Given the diverse nutritional and immunological components of breast milk, many questions remain about this complex interaction.

Introduction: Hypertension, characterized by chronically elevated blood pressure, poses a significant global health burden. Its prevalence, a critical public health concern, necessitates accurate prediction models for timely intervention and management.

Aim: The proposed approach leverages the capability of an artificial neural network to capture complex patterns and non-linear relationships within the time series data, allowing for the development of a robust forecasting model to predict Hypertension. The study population consisted of known hypertensives. In this study, historical time series data related to Hypertension, including patient demographics, lifestyle factors, and medical records, were collected from a Rural primary health center associated with the medical college in coastal Karnataka, India, which is employed to train and validate the model.

Methods: The performance of the Artificial Neural Network (ANN) is evaluated using metrics such as MAE (Mean Absolute Error) and RMSE (Root Mean Squared Error) on a separate test dataset. This research explores the potential of ANN in time series forecasting of Hypertension.

Results: ANN performs well for this data and has been chosen as the best algorithm for this data set, as it has the lowest MAP (0.20) and MAE (0.45) and the highest R-Square (0.89), making it the most accurate and reliable model for the given data. If these algorithms prove beneficial, they can be used in the primary prevention of Hypertension. Individuals, institutions, and even government bodies can use it to save treatment costs and lives.

Conclusion: The ANN model demonstrated reasonably accurate predictions despite the lower overall fit. It has shown the potential to be used as a primary healthcare tool by helping physicians predict and warn about the dangers of elevated blood pressure to patients. These algorithms, deployed using a web application, will enable people to evaluate themselves in the comfort of their homes. This would make us inch closer to the WHO's broader goal of making health a universal right, irrespective of a person's place of residence.

Introduction: Dihydropyridine-calcium channel blockers (DHP-CCBs) are effective first-line blood pressure-lowering agents for primary hypertension. However, data comparing the variations in efficacy and safety between different types of DHP-CCBs are scarce.

Aims and objectives: This study aimed to summarize the latest evidence on the benefits and harms of seven DHP-CCBs (amlodipine, levamlodipine, felodipine, lacidipine, nitrendipine, nifedipine, and benidipine).

Methods: A meta-analysis of DHP-CCBs was carried out to explore differences in efficacy and safety. We searched PubMed, Embase, the Cochrane Library, CNKI, Wanfang Data, and VIP databases from inception to September, 2023, for randomized controlled trials (RCTs) comparing DHP-CCBs. The main outcomes were blood pressure lowering and adverse events (AEs) during treatment.

Results: We included 181 RCTs (21,383 patients) in this analysis. In terms of efficacy, levamlodipine ranked highest in reducing office blood pressure (surface under the cumulative ranking systolic blood pressure = 80.81%, diastolic blood pressure (DBP) = 82.42%) and 24-h ambulatory DBP (98.07%). Felodipine had the highest probability of reducing 24-h ambulatory blood pressure (80.65%). Regarding safety, levamlodipine had the least impact on heart rate (85.71%). In terms of AEs, benidipine had the highest rate for cardiovascular (86.58%) and digestive system (93.57%) AEs. Nifedipine and amlodipine had the highest rates of central (80.65%) and peripheral nervous system (83.28%) AEs, respectively. Levamlodipine exhibited significantly lower rates of total AEs (1.24%), central nervous system AEs (1.28%), and cardiovascular system AEs (3.62%) than the other interventions.

Conclusion: In the office setting, levamlodipine may be the best treatment for primary hypertension, and lacidipine shows good safety.

Background: Chronic Kidney Disease (CKD) is a known risk factor for End-Stage Renal Disease (ESRD) and Cardiovascular Diseases (CVD). Renal Doppler Ultrasound (RDU) can detect early renal involvement in CKD using the Renal Resistive Index (RRI).

Aims: This study aimed to investigate the effects of risk factors and clinical complications associated with CKD on RRI among patients with different stages of CKD.

Methods: In this analytical cross-sectional study, 186 patients referred to Poursina Hospital for RDU were categorized into six groups (normal and five stages of CKD). We analyzed the impact of demographic factors and clinical complications on RRI across all groups.

Results: Our findings indicated that CKD prevalence was particularly high among older patients and those with CVD, type 2 diabetes mellitus (DM), and hypertension (HTN). Elevated RRI in CKD patients was significantly associated with age, CKD stage, CVD, and HTN (p < 0.05). Furthermore, RRI was higher in CKD patients with elevated serum phosphorus (P) levels, higher low-density lipoproteins (LDL), and lower calcium (Ca) and hemoglobin (Hb) levels. Based on a multivariate regression model, CVD, lower Ca, high LDL, and proteinuria were identified as independent predictors of elevated RRI (p < 0.05).

Conclusion: This study concludes that elevated RRI is associated with the severity of CKD and its clinical complications, suggesting that RRI can serve as a reliable indicator for assessing CKD patients, managing treatment, and preventing early death complications.

Large artery stiffness (LAS) is widely recognized as a highly clinically relevant determinant of cardiovascular health and an independent prognostic marker. However, routine assessment of LAS has not yet been integrated into clinical practice. Arterial wall stiffness is dependent on distending pressure (i.e., mean arterial pressure), which may confound the interpretation of individual measurements. The cardio-ankle vascular index (CAVI) is an index of arterial stiffness designed to mitigate the dependence of pulse wave velocity on blood pressure. However, because CAVI incorporates pulse wave velocity measured between the heart and the ankle, it is influenced by both the stiffness of the aorta and medium-sized muscular arteries. Several observational, longitudinal studies have demonstrated that higher CAVI is associated with cardiovascular events and mortality, although most available data are derived from Asian populations. Future studies of CAVI are needed to establish its prognostic value in addition to traditionally used cardiovascular risk factors in the setting of primary prevention. This review aims to provide a brief overview of the definition, theoretical principles, practical considerations, key strengths and limitations, and the clinical utility of CAVI.

Introduction: Left Ventricular Dysfunction (LVD) is a frequent complication in Diabetes mellitus (DM) patients, often worsened by cardiovascular disease. This study explores the role of dipyridamole (DP)-induced heart rate variability and G-SPECT imaging in evaluating LVD in DM patients. This study aimed to evaluate the relationship between heart rate ratio (HRR) during DP stress and LVD parameters derived from gated SPECT (G-SPECT) in DM patients, aiming to identify if HRR can serve as a marker for early LVD assessment.

Methods: A cross-sectional study of 125 patients referred for cardiac scanning. Patients were grouped by diabetic status and HRR (≤ 1.2 vs. > 1.2) post-DP. G-SPECT-derived left ventricular parameters were compared between groups.

Results: G-SPECT showed that peak filling rate (PFR) was higher in non-DM patients. In the HRR ≤ 1.2 group, DM patients had significantly higher end-diastolic volume (EDV) and end-systolic volume (ESV) than non-DM patients (EDV: 66.41±31 vs. 51.34±18, p-value:0.009; ESV: 27.88±11.21 vs. 18.63±15.5, p- p-value: 0.015).

Discussion: This study evaluated the role of heart rate response during dipyridamole stress testing combined with G-SPECT imaging in assessing left ventricular dysfunction (LVD) in diabetic patients. The findings indicate that changes in ventricular volume parameters, along with heart rate response, may serve as early markers of cardiac impairment, potentially facilitating earlier detection and improved management of cardiac complications in this population.

Conclusion: Reduced HRR during DP stress, combined with G-SPECT, may aid in the assessment of LVD in DM patients, potentially facilitating earlier diagnostic insights.