Current Hypertension Reviews - Volume 21, Issue 2, 2025

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.

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.

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.

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.

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.

Blood pressure variability (BPV) is a potential predictor of vascular events and triggers target organ damage. This study aimed to determine the BPV in stroke and coronary heart disease (CHD) in the Bogor Cohort Study in Indonesia.

Over six years of monitoring, a prospective cohort study was conducted on 1649 respondents aged ≥ 31 years from the Bogor Non-communicable Diseases Risk Factors Cohort Study. The dependent variable was vascular events (stroke or CHD), which were new cases (incidents) that appeared during the 6-year monitoring period (2011 – 2017 and 2012-2018).

During the six years of monitoring, the incidence of vascular events was 12.4 percent. The dose-response of systolic and diastolic BPV in vascular events, stroke, and coronary heart disease showed an increased risk (quintiles Q2, Q3, and Q4) compared to quintile 1 (Q1). Systolic BPV of ≥12,10 mmHg and diastolic BPV of ≥ 7,31 mmHg had a risk of 2.3 and 1.7 (95% Confidence Intervals (CI)), respectively, for vascular events during the period of 6-year observation, after controlling for age, hypertension status, and lipid profile.

BPV is an independent predictor of vascular events, stroke, and coronary heart disease. The public and clinicians must pay attention to controlling BPV as a risk factor for vascular events, stroke, and CHD.

According to current clinical practice guidelines, Ambulatory Blood Pressure Measurement (ABPM) is recommended to confirm diagnoses of hypertension. It remains unclear as to which method is superior in predicting mortality outcomes.

Prospective observational studies, comparing ABPM with Clinical Blood Pressure Measurements (CBPM), were included with outcomes of the study being all-cause and cardiovascular mortality.

Nine studies with a total of 23,140 participants were included. Each 10-mmHg increase in 24-hour mean systolic blood pressure (SBP) was linked to a higher risk of all-cause mortality (HR: 1.13, 95% CI: 1.09–1.18), while Clinic Blood Pressure Measurement (CBPM) was not a significant predictor (HR: 1.02, 95% CI: 0.90–1.13). Nighttime SBP increases of 10 mmHg were associated with a higher all-cause mortality risk than daytime SBP (HR: 1.16, 95% CI: 1.11–1.21 versus HR: 1.08, 95% CI: 1.05–1.12). For cardiovascular mortality, a 10 mmHg increase in SBP yielded an HR of 1.21 (95% CI: 1.16–1.27) for 24-hour ABPM compared to 1.08 (95% CI: 1.04–1.11) for CBPM. Similarly, for a 5 mmHg increase in Diastolic Blood Pressure (DBP), the HR was 1.14 (95% CI: 1.07–1.20) for 24 hour ABPM versus 1.04 (95% CI: 1.01–1.07) for clinical DBP, highlighting 24-hour monitoring as a stronger predictor for cardiovascular mortality.

The findings of this study support the superiority of ABPM measurements in predicting both all-cause and cardiovascular mortality.

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.

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).

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.

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.

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