Factors Associating with Non-Dipping Pattern of Nocturnal Blood Pressure in Patients with Essential Hypertension

Cuffless Blood Pressure in clinical practice: challenges, opportunities and current limits

Background: Cuffless blood pressure measurement technologies have attracted significant attention for their potential to transform cardiovascular monitoring.Methods: This updated narrative review thoroughly examines the challenges, opportunities, and limitations associated with the implementation of cuffless blood pressure monitoring systems.Results: Diverse technologies, including photoplethysmography, tonometry, and ECG analysis, enable cuffless blood pressure measurement and are integrated into devices like smartphones and smartwatches. Signal processing emerges as a critical aspect, dictating the accuracy and reliability of readings. Despite its potential, the integration of cuffless technologies into clinical practice faces obstacles, including the need to address concerns related to accuracy, calibration, and standardization across diverse devices and patient populations. The development of robust algorithms to mitigate artifacts and environmental disturbances is essential for extracting clear physiological signals. Based on extensive research, this review emphasizes the necessity for standardized protocols, validation studies, and regulatory frameworks to ensure the reliability and safety of cuffless blood pressure monitoring devices and their implementation in mainstream medical practice. Interdisciplinary collaborations between engineers, clinicians, and regulatory bodies are crucial to address technical, clinical, and regulatory complexities during implementation. In conclusion, while cuffless blood pressure monitoring holds immense potential to transform cardiovascular care. The resolution of existing challenges and the establishment of rigorous standards are imperative for its seamless incorporation into routine clinical practice.Conclusion: The emergence of these new technologies shifts the paradigm of cardiovascular health management, presenting a new possibility for non-invasive continuous and dynamic monitoring. The concept of cuffless blood pressure measurement is viable and more finely tuned devices are expected to enter the market, which could redefine our understanding of blood pressure and hypertension.

Inflammation-based markers, especially the uric acid/albumin ratio, are associated with non-dipper pattern in newly diagnosed treatment-naive hypertensive patients

OBJECTIVE

Physiologically, at night, blood pressure (BP) is expected to decrease by at least 10% in hypertensive individuals. The absence of this decrease, called non-dipper hypertension, is associated with increased end-organ damage and cardiovascular mortality and morbidity in hypertensive individuals. It is known that increased inflammatory process plays an important role in the etiopathogenesis of non-dipper hypertension pattern. In recent years, it has been shown that inflammation-based markers (IBMs) obtained by combining various inflammation-related hematological and biochemical parameters in a single fraction have stronger predictive value than single inflammatory parameters. However, until now, there has not been a study investigating the relationship of these markers with dipper/non-dipper status in newly diagnosed hypertensive patients.

METHODS

Based on ambulatory BP monitoring, 217 dipper and 301 non-dipper naive hypertensive subjects were included in this study. All subjects' IBM values were compared between dipper and non-dipper hypertensive individuals.

RESULTS

IBMs [C-reactive protein/albumin ratio (CAR), monocyte/high-density lipoprotein cholesterol ratio (MHR), neutrophil/lymphocyte ratio (NLR), platelet/lymphocyte ratio, systemic immune-inflammation index (SII), uric acid/albumin ratio (UAR)] were significantly higher in the non-dipper group. CAR, MHR, NLR, SII, and UAR were determined as independent predictors for non-dipper pattern ( P  < 0.05, for all). Also, UAR's diagnostic performance for non-dipper pattern was found to be superior to other IBMs (area under the curve: 0.783, 95% confidence interval: 0.743-0.822; P  < 0.001).

CONCLUSION

These findings suggest an association between elevated IBMs, particularly UAR, and the non-dipper hypertension pattern observed in our study.

Circadian disruptions and their role in the development of hypertension

Circadian fluctuations in physiological setpoints are determined by the suprachiasmatic nucleus (SCN) which exerts control over many target structures within and beyond the hypothalamus via projections. The SCN, or central pacemaker, orchestrates synchrony between the external environment and the internal circadian mechanism. The resulting cycles in hormone levels and autonomic nervous system (ANS) activity provide precise messages to specific organs, adjusting, for example, their sensitivity to approaching hormones or metabolites. The SCN responds to both photic (light) and non-photic input. Circadian patterns are found in both heart rate and blood pressure, which are linked to daily variations in activity and autonomic nervous system activity. Variations in blood pressure are of great interest as several cardiovascular diseases such as stroke, arrhythmias, and hypertension are linked to circadian rhythm dysregulation. The disruption of normal day-night cycles, such as in shift work, social jetlag, or eating outside of normal hours leads to desynchronization of the central and peripheral clocks. This desynchronization leads to disorganization of the cellular processes that are normally driven by the interactions of the SCN and photic input. Here, we review autonomic system function and dysfunction due to regulation and interaction between different cardiorespiratory brain centers and the SCN, as well as social, lifestyle, and external factors that may impact the circadian control of blood pressure.

Prediction of non-dipper blood pressure pattern in Chinese patients with hypertension using a nomogram model

Non-dipper blood pressure has been shown to affect cardiovascular outcomes and cognitive function in patients with hypertension. Although some studies have explored the influencing factors of non-dipper blood pressure, there is still relatively little research on constructing a prediction model. This study aimed to develop and validate a simple and practical nomogram prediction model and explore relevant elements that could affect the dipper blood pressure relationship in patients with hypertension. A convenient sampling method was used to select 356 inpatients with hypertension who visited the Affiliated Hospital of Jining Medical College from January 2022 to September 2022. All patients were randomly assigned to the training cohort (75%, n = 267) and the validation cohort (25%, n = 89). Univariate and multivariate logistic regression were utilized to identify influencing factors. The nomogram was developed and evaluated based on the receiver operating characteristic (ROC) curve, the area under the ROC curve (AUC), and decision curve analyses. The optimal cutoff values for the prevalence of dipper blood pressure were estimated. The nomogram was established using six variables, including age, sex, hemoglobin (Hb), estimated glomerular filtration rate (eGFR), ejection fraction (EF), and heart rate. The AUC was 0.860 in the training cohort. The cutoff values for optimally predicting the prevalence of dipper blood pressure were 41.50 years, 151.00 g/L, 117.53 mL/min/1.73 m2, 64.50%, and 75 beats per minute for age, Hb, eGFR, ejection fraction, and heart rate, respectively. In summary, our nomogram can be used as a simple, plausible, affordable, and widely implementable tool to predict the blood pressure pattern of Chinese patients with hypertension.

The predictive risk factors associated with non-dipper profile in patients with type 2 diabetes and hypertension

Background and aims

The non-dipper status represented by blood pressure reduction by less than 10 percent during sleep is present in about 50 percent of patients with type 2 diabetes (T2D) and hypertension, a pattern associated with more frequent cardiovascular complications and reserved prognosis. This study analyzed the predictive risk factors associated with the different dipper profiles, especially with the nocturnal pattern, following the mean arterial pressure (MAP), the mean heart rate (MHR), and the mean pulse pressure (MPP) in patients with T2D and hypertension, established by ambulatory blood pressure monitoring (ABPM).

Method

166 consecutive patients with type 2 diabetes mellitus and hypertension were included in a cross-sectional study, and they underwent 24-hour ABPM. We excluded patients with secondary hypertension, acute coronary disease and heart failure, with oncologic or endocrine disease. The simple and multiple linear regression models were performed predicting 24-hour, day and night MAP, MHR, and MPP according to various predictors, using software R version 4.3.1.

Results

There were 80 non-dippers (48.20%), 57 dippers (34.34%), 22 reverse-dippers (13.25%) and seven extreme-dippers (4.21%). A statistically significant association was observed between MAP 24-hour and total cholesterol (TC) (higher TC values were associated with higher MAP /24 h values): adjusted coefficient B of the regression slope: 0.09, 95% confidence interval CI (0.04-0.15), p=0.003. In the multivariate analysis: adjusted B: 8.64, 95% CI (-14.67-2.61), p=0.006, beta-blockers reached the threshold of statistical significance in relation to MHR/24 h, their presence decreasing the heart rate. PP/24 hours was associated in the multivariate analysis with age: adjusted B: 0.45, 95% CI (0.05-0.85), p=0.28; abdominal circumference: 0.26, 95% CI (0.03-0.49), p=0.028, and total cholesterol: 0.1, 95% CI (0.02-0.17), p=0.013. Diabetic nephropathy was statistically significantly associated with PP/24 h: adjusted B: 10.19, 95% CI (1.24-19.14), p=0.027.

Conclusions

High cholesterol was associated with higher values of MAP and PP. Beta-blocker treatment lowered non-dipper MHR. Age and AC were correlated with increased PP values. These are predictive risk factors associated with the status of non-dippers established by ABPM, and they represent a veritable link to the non-dipper pattern in patients with T2D and hypertension.

Impact of health literacy, social support, and socioeconomic position on the serum uric acid level in asymptomatic hyperuricaemia patients in China: a structural equation model

BACKGROUND

Hyperuricaemia (HUA) poses a significant public health challenge on a global scale. It is mostly asymptomatic hyperuricemia (AHU) with unsatisfactory recognition and control rates. The role of health literacy in influencing health outcomes is of utmost importance, and enhancing health literacy is helpful for patients in managing risk factors. Additionally, social support and socioeconomic position (SEP) have been identified as potential factors influencing health. However, the exact relationships between these factors and AHU remain unclear. This study aimed to investigate the status of health literacy among patients with AHU and explore the relationships between health literacy, social support, SEP, and serum uric acid (SUA) levels.

METHODS

A cross-sectional study was conducted among 349 participants with AHU in Luzhou, China. The research instruments included a sociodemographic characteristics questionnaire, the Health Literacy Scale for Chronic Patients (HLSCP), and the Social Support Scale (SSRS). The construction of the SEP index was achieved through the application of principal component analysis. Univariate and hierarchical regression analyses were used to evaluate the associations between SEP, social support, health literacy, and SUA levels. Furthermore, structural equation modelling (SEM) was utilized to examine these associations.

RESULTS

(1) Most patients exhibited low health literacy (90.18 ± 15.11), and only 44.4% possessed basic health literacy. (2) SEP was positively correlated with SUA levels (β = 4.086, P < 0.001), and health literacy was negatively related to SUA levels (β = -0.399, P < 0.001). There was no significant relationship between social support and SUA levels (β = 0.051, t = 1.085). (3) Health literacy mediated the association between SEP and SUA levels (β = -0.490, 95% CI: -0.620 to -0.382). SEP had a direct positive effect on SUA levels (β = 0.723) and health literacy (β = 0.696), and the total effect of SEP on SUA levels was 0.233.

CONCLUSIONS

The findings indicate a low level of health literacy among patients with AHU and suggest that health literacy might play a mediating role in the relationship between SEP and SUA levels. Consequently, future initiatives are recommended to prioritize health literacy and devise appropriate intervention strategies to enhance the self-management capabilities of patients with AHU.