Background and Purpose—: Elevated blood homocysteine concentration increases the risk of stroke, especially among hypertensive individuals. Homocysteine is largely affected by the methylenetetrahydrofolate reductase C677T polymorphism and folate status. Among hypertensive patients, we aimed to test the hypothesis that the association between homocysteine and stroke can be modified by the methylenetetrahydrofolate reductase C677T polymorphism and folic acid intervention. Methods—: We analyzed the data of 20 424 hypertensive adults enrolled in the China Stroke Primary Prevention Trial. The participants, first stratified by methylenetetrahydrofolate reductase genotype, were randomly assigned to receive double-blind treatments of 10-mg enalapril and 0.8-mg folic acid or 10-mg enalapril only. The participants were followed up for a median of 4.5 years. Results—: In the control group, baseline log-transformed homocysteine was associated with an increased risk of first stroke among participants with the CC/CT genotype (hazard ratio, 3.1; 1.1–9.2), but not among participants with the TT genotype (hazard ratio, 0.7; 0.2–2.1), indicating a significant gene–homocysteine interaction ( P =0.008). In the folic acid intervention group, homocysteine showed no significant effect on stroke regardless of genotype. Consistently, folic acid intervention significantly reduced stroke risk in participants with CC/CT genotypes and high homocysteine levels (tertile 3; hazard ratio, 0.73; 0.55–0.97). Conclusions—: In Chinese hypertensive patients, the effect of homocysteine on the first stroke was significantly modified by the methylenetetrahydrofolate reductase C677T genotype and folic acid supplementation. Such information may help to more precisely predict stroke risk and develop folic acid interventions tailored to individual genetic background and nutritional status. Clinical Trial Registration—: URL: http://www.clinicaltrials.gov . Unique identifier: NCT00794885.

The spot urine method as an alternative approach in estimating daily urine sodium excretion has been proposed for many years. Kawasaki has created an equation to predict daily urinary sodium excretion using second morning urine (SMU) samples which was obtained before breakfast after initial voiding upon arising. Tanaka has developed another equation by examining spot urine samples submitted at random times during the day. A newly published study proposed that the “PM sample,” collected in the late afternoon or early evening before dinner, showed a stronger relationship with actual sodium excretion. We aimed to verify the effectiveness of these methods in evaluating 24-hour urinary sodium in Chinese hypertensive patients. A total of 334 hypertensive participants were eligible to participate in this study. A total of 222 patients provided qualified SMU samples, Post Meridiem (PM) samples, and complete 24-hour urine collections. Biases using the Kawasaki formula were 2.1 mmol/day for the SMU specimens; for the Tanaka equation, biases of SMU and PM samples were 21.1 and 30.1 mmol/day, respectively. The highest intraclass correlation coefficient (ICC) was 0.64 when the Kawasaki formula was used in PM specimens, with the lowest ICC 0.17 when it is used in SMUs. Spot urine method is acceptable for estimating 24-hour urinary sodium excretion in hypertensive individuals. Kawasaki’s formula is useful for estimating population mean levels of sodium excretion from SMU, although it is not suitable for estimating individual sodium excretion.

Introduction: Identifying people at risk of cardiovascular diseases (CVD) is a cornerstone of preventive cardiology. We developed machine learning (ML) algorithms and investigated their performance in predicting patients’ current CVD risk (coronary heart disease and stroke in this study).Materials and methods: We compared traditional logistic regression (LR) with five ML algorithms LR with Elastic-Net, Random Forest (RF), XGBoost (XGB), Support Vector Machine, Deep Learning, and an Ensemble model averaging predictions from RF, XGB, and Deep Learning for CVD risk prediction using pre-existing patient-level data from a multi-center, cross-sectional study (the Microalbuminuria Screening in Hypertensive Patients Project initiated by the China International Exchange and Promotive Association for Medical and Healthcare) that enrolled 143,043 patients with hypertension from 600 tertiary, secondary, or community hospitals. Each of the five ML algorithms incorporated 18 variables, such as demographics, examinations, comorbidities, and treatment regimens, and were trained and evaluated using 5-fold cross-validation. Predictive accuracy was assessed by the area under the receiver operating curve (AUROC).Results: Patients’ mean age was 62 ± 12 years and 57% were men. Advanced ML algorithms outperformed the traditional LR model. Particularly, the Ensemble model had superior discrimination with an AUROC of 0.760 than LR (AUC = 0.737) and other tested models.Conclusion: We establishes an Ensemble model that shows better performance in predicting patients’ current CVD risk using routine information compared to the traditional LR model. ML can help physicians design follow-up plans with more accurate results, offering new possibilities for short-term risk prediction and early detection. Further, ML models can be trained with longitudinal data and used to predict long-term CVD risks, thereby informing CVD prevention.

In China, automated blood pressure monitors have been readily available for home use. Home blood pressure monitoring has been indispensable in the management of hypertension. There is therefore a need to establish guidelines for home blood pressure monitoring on the basis of the 2012 consensus document. In this guidelines document, the committee put forward recommendations on the selection and calibration of blood pressure measuring devices, the frequency (times) and duration (days) of blood pressure measurement, and the diagnostic threshold of home blood pressure.

Nocturnal hypertension is highly prevalent among Chinese and Asian populations, which is mainly attributed to high salt intake and high salt sensitivity. Nocturnal hypertension increases the risk of cardiovascular and all‐cause mortality, independent of daytime blood pressure (BP). However, it can usually be detected by 24‐h ambulatory BP monitoring, rather than routine office or home BP measurement, thus is often underdiagnosed in clinical practice. Currently, no specific guidance is available for the management of nocturnal hypertension in China or worldwide. Experts from the Chinese Hypertension League summarized the epidemiologic and pathophysiologic characteristics and clinical phenotype of nocturnal hypertension and provided consensus recommendations on optimal management of nocturnal hypertension, with the goal of maximally reducing the cardiovascular disease risks. In this consensus document, 24‐h ABPM is recommended for screening and diagnosis of nocturnal hypertension, especially in the elderly, patients with diabetes, chronic kidney diseases, obstructive sleep apnea and other conditions prone to high nocturnal BP. Lifestyle modifications including salt intake restriction, exercise, weight loss, sleep improvement, and mental stress relief are recommended. Long‐acting antihypertensive medications are preferred for nocturnal and 24‐h BP control. Some newly developed agents, renal denervation, and other device‐based therapy on nocturnal BP reduction are evaluated.