Predictive value for the rural Chinese population of the Framingham hypertension risk model: results from Liaoning Province

Development of hypertension models for lung cancer screening cohorts using clinical and thoracic aorta imaging factors

This study aims to develop and validate nomogram models utilizing clinical and thoracic aorta imaging factors to assess the risk of hypertension for lung cancer screening cohorts. We included 804 patients and collected baseline clinical data, biochemical indicators, coexisting conditions, and thoracic aorta factors. Patients were randomly divided into a training set (70%) and a validation set (30%). In the training set, variance, t-test/Mann-Whitney U-test and standard least absolute shrinkage and selection operator were used to select thoracic aorta imaging features for constructing the AIScore. Multivariate logistic backward stepwise regression was utilized to analyze the influencing factors of hypertension. Five prediction models (named AIMeasure model, BasicClinical model, TotalClinical model, AIBasicClinical model, AITotalClinical model) were constructed for practical clinical use, tailored to different data scenarios. Additionally, the performance of the models was evaluated using receiver operating characteristic (ROC) curves, calibration curves and decision curve analyses (DCA). The areas under the ROC curve for the five models were 0.73, 0.77, 0.83, 0.78, 0.84 in the training set, and 0.77, 0.78, 0.81, 0.78, 0.82 in the validation set, respectively. Furthermore, the calibration curves and DCAs of both sets performed well on accuracy and clinical practicality. The nomogram models for hypertension risk prediction demonstrate good predictive capability and clinical utility. These models can serve as effective tools for assessing hypertension risk, enabling timely non-pharmacological interventions to preempt or delay the future onset of hypertension.

Prognostic risk models for incident hypertension: A PRISMA systematic review and meta-analysis

OBJECTIVE

Our goal was to review the available literature on prognostic risk prediction for incident hypertension, synthesize performance, and provide suggestions for future work on the topic.

METHODS

A systematic search on PUBMED and Web of Science databases was conducted for studies on prognostic risk prediction models for incident hypertension in generally healthy individuals. Study-quality was assessed using the Prediction model Risk of Bias Assessment Tool (PROBAST) checklist. Three-level meta-analyses were used to obtain pooled AUC/C-statistic estimates. Heterogeneity was explored using study and cohort characteristics in meta-regressions.

RESULTS

From 5090 hits, we found 53 eligible studies, and included 47 in meta-analyses. Only four studies were assessed to have results with low risk of bias. Few models had been externally validated, with only the Framingham risk model validated more than thrice. The pooled AUC/C-statistics were 0.82 (0.77-0.86) for machine learning models and 0.78 (0.76-0.80) for traditional models, with high heterogeneity in both groups (I2 > 99%). Intra-class correlations within studies were 60% and 90%, respectively. Follow-up time (P = 0.0405) was significant for ML models and age (P = 0.0271) for traditional models in explaining heterogeneity. Validations of the Framingham risk model had high heterogeneity (I2 > 99%).

CONCLUSION

Overall, the quality of included studies was assessed as poor. AUC/C-statistic were mostly acceptable or good, and higher for ML models than traditional models. High heterogeneity implies large variability in the performance of new risk models. Further, large heterogeneity in validations of the Framingham risk model indicate variability in model performance on new populations. To enable researchers to assess hypertension risk models, we encourage adherence to existing guidelines for reporting and developing risk models, specifically reporting appropriate performance measures. Further, we recommend a stronger focus on validation of models by considering reasonable baseline models and performing external validations of existing models. Hence, developed risk models must be made available for external researchers.

Associations of trajectories in body roundness index with incident cardiovascular disease: a prospective cohort study in rural China

Aims

The body roundness index (BRI) has good predictive ability for both body fat and visceral adipose tissue. Longitudinal BRI trajectories can reveal the potential dynamic patterns of change over time. This prospective study assessed potential associations between BRI trajectories and incident cardiovascular disease (CVD) in rural regions of Northeast China.

Methods

In total, 13,209 participants (mean age: 49.0 ± 10.3 years, 6,856 [51.9%] male) were enrolled with three repeated times of BRI measurements at baseline (2004-2006), 2008, and 2010, and followed up until 2017 in this prospective study. Using latent mixture model, the BRI trajectories were determined based on the data from baseline, 2008 and 2010. Composite CVD events (myocardial infarction, stroke, and CVD death combined) was the primary endpoint. Cox proportional-hazards models were used to analyze the longitudinal associations between BRI trajectories and incident CVD.

Results

Three distinct BRI trajectories were identified: high-stable (n = 538), moderate-stable (n = 1,542), and low-stable (n = 11,129). In total, 1,382 CVD events were recorded during follow-up. After adjustment for confounders, the moderate-stable and high-stable BRI groups had a higher CVD risk than did the low-stable BRI group, and the HR (95%CI) were 1.346 (1.154, 1.571) and 1.751 (1.398, 2.194), respectively. Similar associations were observed between the trajectories of BRI and the risk of stroke and CVD death. The high-stable group was also significantly and independently associated with CVD, myocardial infarction, stroke, and CVD death in participants aged <50 years.

Conclusion

BRI trajectory was positively associated with incident CVD, providing a novel possibility for the primary prevention of CVD in rural regions of China.

A diagnostic prediction model for hypertension in Han and Yugur population from the China National Health Survey (CNHS)

BACKGROUND

The prevalence of hypertension is high among Chinese adults, thus, identifying non-hypertensive individuals at high risk for intervention will help to improve the efficiency of primary prevention strategies.

METHODS

The cross-sectional data on 9699 participants aged 20 to 80 years were collected from the China National Health Survey in Gansu and Hebei provinces in 2016 to 2017, and they were nonrandomly split into the training set and validation set based on location. Multivariable logistic regression analysis was performed to develop the diagnostic prediction model, which was presented as a nomogram and a website with risk classification. Predictive performances of the model were evaluated using discrimination and calibration, and were further compared with a previously published model. Decision curve analysis was used to calculate the standardized net benefit for assessing the clinical usefulness of the model.

RESULTS

The Lasso regression analysis identified the significant predictors of hypertension in the training set, and a diagnostic model was developed using logistic regression. A nomogram with risk classification was constructed to visualize the model, and a website ( https://chris-yu.shinyapps.io/hypertension_risk_prediction/ ) was developed to calculate the exact probabilities of hypertension. The model showed good discrimination and calibration, with the C-index of 0.789 (95% confidence interval [CI]: 0.768, 0.810) through internal validation and 0.829 (95% CI: 0.816, 0.842) through external validation. Decision curve analysis demonstrated that the model was clinically useful. The model had a higher area under receiver operating characteristic curves in training and validation sets compared with a previously published diagnostic model based on Northern China population.

CONCLUSION

This study developed and validated a diagnostic model for hypertension prediction in Gansu Province. A nomogram and a website were developed to make the model conveniently used to facilitate the individualized prediction of hypertension in the general population of Han and Yugur.

Development and validation of hypertension prediction models: The Korean Genome and Epidemiology Study_Cardiovascular Disease Association Study (KoGES_CAVAS)

This study aimed to develop and validate the hypertension risk prediction models of the CArdioVascular disease Association Study (CAVAS). Overall, 6,186 participants without hypertension at baseline were randomly divided into derivation and internal validation sets in a 6:4 ratio. We derived two prediction models: the first used the Framingham hypertension risk prediction factors (F-CAVAS-HTN); the second considered additional risk factors identified using stepwise Weibull regression analysis (CAVAS-HTN). These models were externally evaluated among Ansan and Ansung (A&A) participants, and the external validity of the Framingham and A&A prediction models (F-HTN and A&A-HTN) were assessed using the internal validation set of CAVAS. The discrimination, calibration, and net reclassification were determined. During the 4-year follow-up, 777 new cases of hypertension were diagnosed. All four models showed good discrimination (C-statistic ≥ 0.7). Internal calibrations were good for both the coefficient-based and the risk score-based F-CAVAS-HTN models, respectively (Hosmer-Lemeshow chi-square, H-L χ² < 20, P ≥ 0.05). However, the two CAVAS models (H-L χ² ≥ 20, P < 0.05, both) as well as the F-HTN and the A&A-HTN prediction models (H-L χ² = 155.39, P < 0.0001; H-L χ² = 209.72, P < 0.0001, respectively) were not externally calibrated. The F-CAVAS-HTN may be better than models with additional risk factors or derived for another population in the view of the findings of the internal validation in the present study, although future studies to improve the external validity of the F-CAVAS-HTN are needed.

Cumulative exposure to elevated blood pressure better predicts cardiovascular disease risk in rural Chinese adults

Background

Traditional risk estimations for cardiovascular disease (CVD) are based on current blood pressure (BP); however, whether cumulative exposure to elevated BP among rural individuals has additional prognostic value is unclear. We aimed to validate the association of cumulative BP with CVD occurrence and assess the prognostic value of cumulative BP in CVD risk prediction.

Methods

A total of 13,057 participants who underwent three examinations from 2004 to 2010 were included in this rural epidemiological study and followed up until 2017. Cumulative BP was defined as the sum of the product of the average BP values between consecutive examinations and the time interval for each pair of successive tests prior to the follow-up period. CVD incidents that occurred during the follow-up period were noted and verified by qualified researchers. We used multivariate Cox models to assess the association of cumulative BP with CVD risk. The receiver operating characteristic curve was constructed to determine the predictive differentiation of single baseline BP measurements and cumulative BP values for CVD outcomes.

Results

During the follow-up period, 1,312 participants underwent CVD incidents. We found that cumulative systolic BP (hazard ratio = 1.334, 95% confidence interval: 1.245, 1.430) and cumulative diastolic BP (hazard ratio = 1.253, 95% confidence interval: 1.168, 1.343) were associated with CVD incidence above and beyond that of the current BP. These stronger associations persisted for stroke, myocardial infarction, and CVD mortality. The area under the curve for the model increased significantly (p < 0.001) from 0.735 (0.720, 0.750) to 0.742 (0.728, 0.757) when integrating cumulative systolic BP instead of baseline systolic BP.

Conclusion

Cumulative BP in Chinese rural adults showed a stronger association with CVD incidence than that of current BP. Furthermore, cumulative BP slightly improved the predictive performance for CVD. Our findings underline the incremental predictive value of cumulative BP in CVD risk assessment among Chinese rural adults.

Development and validation of prediction models for hypertension risks: A cross-sectional study based on 4,287,407 participants

Objective

To develop an optimal screening model to identify the individuals with a high risk of hypertension in China by comparing tree-based machine learning models, such as classification and regression tree, random forest, adaboost with a decision tree, extreme gradient boosting decision tree, and other machine learning models like an artificial neural network, naive Bayes, and traditional logistic regression models.

Methods

A total of 4,287,407 adults participating in the national physical examination were included in the study. Features were selected using the least absolute shrinkage and selection operator regression. The Borderline synthetic minority over-sampling technique was used for data balance. Non-laboratory and semi-laboratory analyses were carried out in combination with the selected features. The tree-based machine learning models, other machine learning models, and traditional logistic regression models were constructed to identify individuals with hypertension, respectively. Top features selected using the best algorithm and the corresponding variable importance score were visualized.

Results

A total of 24 variables were finally included for analyses after the least absolute shrinkage and selection operator regression model. The sample size of hypertensive patients in the training set was expanded from 689,025 to 2,312,160 using the borderline synthetic minority over-sampling technique algorithm. The extreme gradient boosting decision tree algorithm showed the best results (area under the receiver operating characteristic curve of non-laboratory: 0.893 and area under the receiver operating characteristic curve of semi-laboratory: 0.894). This study found that age, systolic blood pressure, waist circumference, diastolic blood pressure, albumin, drinking frequency, electrocardiogram, ethnicity (uyghur, hui, and other), body mass index, sex (female), exercise frequency, diabetes mellitus, and total bilirubin are important factors reflecting hypertension. Besides, some algorithms included in the semi-laboratory analyses showed less improvement in the predictive performance compared to the non-laboratory analyses.

Conclusion

Using multiple methods, a more significant prediction model can be built, which discovers risk factors and provides new insights into the prediction and prevention of hypertension.

Association of isolated diastolic hypertension based on different guideline definitions with incident cardiovascular risk in a Chinese rural cohort

The 2017 American College of Cardiology/American Heart Association (ACC/AHA) guideline lowered the threshold (systolic blood pressure [SBP] <130 mm Hg and diastolic blood pressure [DBP] ≥80 mm Hg) for isolated diastolic hypertension (IDH), whereas the 2018 Chinese guideline still recommends the old threshold (SBP <140 mm Hg and DBP ≥90 mm Hg). This study aimed to investigate the association between IDH, as defined by both guidelines, and the risk of incident cardiovascular disease (CVD) in rural areas of northeast China. This prospective study included participants whose baseline data were collected between 2004 and 2006. The exclusion criteria were baseline CVD, incomplete data, and systolic hypertension. The primary end point was incident CVD, a composite end point including nonfatal myocardial infarction (MI), nonfatal stroke, and CVD death. Multivariate Cox models were used to evaluate the association of IDH with CVD risk. The authors analyzed 19 688 participants (7140 participants with IDH) according to the ACC/AHA guideline. Compared with normotensive participants, individuals with ACC/AHA‐defined IDH were at a high risk of CVD (HR = 1.177, 95% CI: 1.035–1.339). A similar difference in CVD risk was noted when normotensive participants were compared with those with IDH, determined based on the 2018 Chinese guideline (HR = 1.218, 95% CI: 1.050–1.413). Similar results were found in participants who did not take antihypertensives at baseline. Moreover, IDH defined by either guideline was significantly associated with nonfatal MI. ACC/AHA‐defined IDH was associated with a risk of CVD, implying that blood pressure management should be improved in rural areas of China.

Establishment and verification of a nomogram prediction model of hypertension risk in Xinjiang Kazakhs

Hypertension is the main risk factor for cardiovascular and renal diseases. It is of great importance to develop effective risk prediction models to identify high-risk groups of hypertension. This study is to establish and verify a nomogram model for predicting the risk of hypertension among Kazakh herders in Xinjiang, China.This is a prospective cohort study. Totally, 5327 Kazakh herders from the Nanshan pastoral area of Xinjiang were enrolled. They were randomly divided into the modeling set of 3729 cases (70%) and the validation set of 1598 cases (30%). In the modeling set, univariate analysis, least absolute shrinkage and selection operator regression and multivariate Logistic regression were used to analyze the influencing factors of hypertension, and a nomogram prediction model was constructed. We then validated the model in the validation set, and evaluated the accuracy of the model using receiver operating characteristic and calibration curve.Based on univariate analysis, least absolute shrinkage and selection operator regression and multivariate logistic regression analysis, we identified 14 independent predictors of hypertension in the modeling set, including age, smoking, alcohol consumption, baseline body mass index, baseline diastolic blood pressure, baseline systolic blood pressure, daily salt intake, yak-butter intake, daily oil intake, fruit and vegetable intake, low-density lipoprotein, cholesterol, abdominal circumference, and family history. The area under the receiver operating characteristic curve of the modeling set and the verification set was 0.803 and 0.809, respectively. Moreover, the calibration curve showed a higher agreement between the nomogram prediction and the actual observation of hypertension.The risk prediction nomogram model has good predictive ability and could be used as an effective tool for the risk prediction of hypertension among Kazakh herders in Xinjiang.

Derivation and validation of a clinical prediction model for risks of venous thromboembolism in diabetic and general populations

Most studies on the prediction of venous thromboembolism (VTE) focused on hospitalized, surgery, and cancer patients or women receiving hormonal contraceptives or menopausal hormone therapy. No study considered diabetic and general populations to establish a VTE prediction model, especially in Asia. We developed a predictive model for VTE among type 2 diabetic patients and the general population.This study considered 2 nationwide retrospective cohort studies consisting of 52,427 diabetic participants and 508,664 participants from the general population aged 30 to 85 years during 2001 to 2004 in Taiwan. All participants were followed up until VTE event, death, or December 2011. The outcome event was VTE, including deep venous thrombosis and pulmonary embolism. Candidate predictors consisted of socio-demographic factors, diabetes-related factors and biomarkers, comorbidities, and medicine use. Our study followed the procedures proposed by the Framingham Heart Study to develop prediction models by using a Cox regression model. The predictive accuracy and performance characteristics were assessed using the area under curve of receiver operating characteristics curve and calibration of a risk score were performed by Hosmer-Lemeshow goodness-of-fit test.The common factors for persons with type 2 diabetes and general population included age, hospitalization status 1 year before the baseline, hypertension, chronic kidney disease, chronic obstructive pulmonary disease, and anti-diabetes medications; the specific factors for persons with type 2 diabetes consisted of body mass index, glycosylated hemoglobin A1C, and creatinine; and the factors for general population included gender, peripheral vascular disease, cancer, hypertension medication, cardiovascular medication, and non-steroidal anti-inflammatory drug. The area under curve of 3-, 5-, and 8-year VTE prediction models were 0.74, 0.71, and 0.69 in the diabetic population and 0.77, 0.76, and 0.75 in the general population, respectively.The new clinical prediction models can help identify a high risk of VTE and provide medical intervention in diabetic and general populations.

The Association of Stage 1 Hypertension, Defined by the 2017 ACC/AHA Guidelines, With Cardiovascular Events Among Rural Women in Liaoning Province, China

Background: The recent American College of Cardiology/American Heart Association (ACC/AHA) guidelines redefined blood pressure levels 130-139/80-89 mmHg as stage 1 hypertension. However, the association of stage 1 hypertension with cardiovascular disease (CVD) and its age-specific differences among the rural women in Liaoning province remains unclear. It needs to be quantified in considering guideline adoption in China.

Methods: In total, 19,374 women aged ≥35 years with complete data and no cardiovascular disease at baseline were followed in a rural community-based prospective cohort study of Liaoning province, China. Follow-up for the new cases of CVD was conducted from the end of the baseline survey to the end of the third follow-up survey (January 1, 2008–December 31, 2017). Adjusted Cox proportional hazards models were applied to estimate the Hazard Ratios (HR) and 95% Confidence Intervals (CI) with the normal blood pressure as a reference.

Results: During the median follow-up period of 12.5 years, 1,419 subjects suffered all-cause death, 748 developed CVD, 1,224 participants suffered stroke and 241 had Myocardial Infarction (MI). Compared with normal BP, Stage 1 hypertension had a HR (95% CI) of 1.694 (1.202–2.387) in CVD mortality, 1.575 (1.244–1.994) in the incidence of stroke. The results obtained that the risk of CVD mortality and incidence of stroke was significantly associated with stage 1 hypertension in rural women aged ≥45 years after adjusting for other potential factors. However, in participants aged 35–44 years, stage 1 hypertension was not associated with an increased risk of cardiovascular disease.

Conclusions: The newly defined stage 1 hypertension is associated with an increased risk of CVD mortality and also incidence of stroke in the rural women aged ≥45 years population of Liaoning province. This study can be a good reference for health policy makers and clinicians workers to make evidence-based decisions toward lowering burden of cardiovascular disease more efficient, timely measures on prevention and control of stage 1 hypertension in China.

Development and validation of a nomogram to better predict hypertension based on a 10-year retrospective cohort study in China

Background

Hypertension is a highly prevalent disorder. A nomogram to estimate the risk of hypertension in Chinese individuals is not available.

Methods

6201 subjects were enrolled in the study and randomly divided into training set and validation set at a ratio of 2:1. The LASSO regression technique was used to select the optimal predictive features, and multivariate logistic regression to construct the nomograms. The performance of the nomograms was assessed and validated by AUC, C-index, calibration curves, DCA, clinical impact curves, NRI, and IDI.

Results

The nomogram^140/90 was developed with the parameters of family history of hypertension, age, SBP, DBP, BMI, MCHC, MPV, TBIL, and TG. AUCs of nomogram^140/90 were 0.750 in the training set and 0.772 in the validation set. C-index of nomogram^140/90 were 0.750 in the training set and 0.772 in the validation set. The nomogram^130/80 was developed with the parameters of family history of hypertension, age, SBP, DBP, RDWSD, and TBIL. AUCs of nomogram^130/80 were 0.705 in the training set and 0.697 in the validation set. C-index of nomogram^130/80 were 0.705 in the training set and 0.697 in the validation set. Both nomograms demonstrated favorable clinical consistency. NRI and IDI showed that the nomogram^140/90 exhibited superior performance than the nomogram^130/80. Therefore, the web-based calculator of nomogram^140/90 was built online.

Conclusions

We have constructed a nomogram that can be effectively used in the preliminary and in-depth risk prediction of hypertension in a Chinese population based on a 10-year retrospective cohort study.

Funding

This study was supported by the Hebei Science and Technology Department Program (no. H2018206110).

Putting the glass down may keep the stroke away: Results from a prospective cohort study in rural China

BACKGROUND AND AIMS

Most studies assess the relationship between alcohol and stroke at some point. Little is known about the effect on stroke of drinking status changes over time. This study aimed to examine the association of median 2.4-year drinking status changes with risk of stroke.

METHODS AND RESULTS

We examined 22,691 adults from rural China. Drinking status was assessed at 2004-2006 and in 2008. Participants were divided into four change patterns: consistent non-drinkers, abstainers, starters, and consistent drinkers. A Cox proportional hazards model were performed. We observed 1215 cases of stroke during a median follow-up period of 11.8 years. A faint J-shaped association between alcohol consumption and risk of stroke was found in this population. Based on the amount of alcohol consumption, only current drinkers with ≥721 g/week at baseline in both males and females had a higher risk of stroke [hazard ratio (HR): 1.342; 95% confidence interval (CI): 1.070-1.683 and HR: 2.130; CI: 1.041-4.357, respectively]. Based on change patterns, Compared with consistent non-drinkers, the HR (95% CI) for consistent drinkers, abstainers and starters was 1.298 (1.070-1.576), 1.093 (0.877-1.362) and 1.263 (1.034-1.543), respectively. The same trend was observed in male. The HR (95% CI) for consistent drinkers, abstainers and starters was 1.360 (1.098-1.685), 1.139 (0.883-1.470) and 1.364 (1.092-1.703), respectively. No difference was observed in females.

CONCLUSION

High alcohol consumption was associated with increased risk of stroke in both males and females. However, based on change patterns, consistent drinkers and starters were at higher risk of stroke only in males.

Trajectories of body mass index and risk of incident hypertension among a normal body mass index population: A prospective cohort study

It is unclear whether there are different body mass index (BMI) trajectories among a population with normal BMI levels, and the association between BMI patterns and incident hypertension is not well characterized. This prospective cohort study includes surveys conducted at baseline and three follow‐ups. 3939 participants who are free of hypertension at baseline or first two follow‐ups were enrolled. At baseline, the age of participants ranged from 35 to 82 years and the mean age was 45.9 years. The BMI trajectories were identified using latent mixture modeling with data from the baseline and first two follow‐ups. The effects of different BMI trajectories on the development of hypertension were analyzed using a Cox proportional hazard model. Four distinct BMI trajectories were identified over the study period (2004‐2010): normal‐stable (n = 1456), normal‐increasing (n = 2159), normal‐fluctuated (n = 166), and normal‐sharp‐increasing (n = 158). Relative to the normal‐stable BMI group, the hazard ratios (HRs) and 95% confidence intervals (CIs) after adjustment for confounding factors of the normal‐increasing, normal‐fluctuated, and normal‐sharp‐increasing groups were 1.244 (1.103‐1.402), 1.331 (1.008‐1.756), and 1.641 (1.257‐2.142), respectively. Additionally, subgroup analysis showed that the normal‐fluctuated BMI trajectory was associated with a significantly higher risk of hypertension only in women (HR = 1.362; 95% CI = 1.151‐1.611). The BMI trajectories were significant predictors of hypertension incidence, and increasing BMI trajectories within the currently designated normal range were associated with an increased hypertension risk, especially in women.

Born in winter or spring more susceptible to all-cause and cardiovascular disease death in rural areas of China: results from a 11.9-year follow-up study

There has been no evidence on the effects of birth season and birth month on mortality in China. We aimed to explore the association between birth season, birth month and all-cause and cardiovascular disease (CVD) death. A population-based sample of 21,338 Chinese rural participants aged ≥35 years at baseline was included in our analysis. Age and multivariable adjusted Cox proportional hazards models were used to estimate hazard ratios (HRs) and 95% confidence intervals (95% CIs) for the relationship between astronomical birth season (autumn as the reference), birth month (November as the reference), and all-cause and CVD mortality. During a median follow-up period of 11.9 years, 2,207 people died from all-cause and 1,214 people were attributed to CVD death. In multivariable adjusted analyses, for all-cause death, spring and winter had HRs (95% CIs) of 1.134 (1.005–1.280) and 1.162 (1.038–1.301), respectively; January, March, May, and August had HRs (95% CIs) of 1.249 (1.027–1.518), 1.234 (1.008–1.512), 1.276 (1.037–1.571), and 1.232 (1.003–1.513), respectively. For CVD death, spring and winter with HRs (95% CIs) of mortality were 1.232 (1.048–1.449) and 1.174 (1.007–1.369), respectively; March with HR (95% CI) of mortality were 1.343 (1.030–1.750) (all P < 0.05). Our study indicated that people born in the winter or spring were significantly associated with all-cause and cardiovascular disease mortality in rural areas of China.

Association of general and abdominal obesity and their changes with stroke in Chinese adults: Results from an 11.8-year follow-up study

BACKGROUND AND AIMS

Obesity-related diseases play a significant role in the epidemiology of stroke; however, the exact effects of obesity and transitions in obesity status on stroke risk are still unclear. This study was performed to investigate the association of general and abdominal obesity and their changes with stroke in Chinese adults.

METHODS AND RESULTS

A total of 26,815 subjects (13,684 men and 13,131 women) aged ≥35 years participated in the study. The association of general and abdominal obesity and their changes with stroke was estimated by Cox proportional hazards models. During a median follow-up period of 11.8 years, 1507 people developed an incident stroke event. The multivariable-adjusted hazard ratios (HRs) (95% CIs) for stroke comparing the highest vs. lowest quartiles of these measurements were 1.276 (1.068-1.524) for BMI, 1.245 (1.035-1.499) for WC, 0.940 (0.786-1.125) for WHR, and 1.221 (1.019-1.464) for WHtR in men. For women, the corresponding values were 1.368 (1.089-1.718), 1.424 (1.119-1.813), 0.971 (0.765-1.232), and 1.341 (1.059-1.699), respectively. C- statistics showed no difference in the predictive value for stroke among various measures of adiposity. Compared with participants who maintained a normal BMI, the HRs for reversed general obesity was 1.272 (95% CI: 1.044-1.550) among men and 1.240 (95% CI: 0.948-1.623) among women.

CONCLUSION

Increasing levels of general or abdominal adiposity consistently predict increased risk of stroke, and maintenance of a normal BMI or WC may aid in stroke prevention.

Blood Pressure Changes in a Chinese Population Have a Greater Impact on Short-Term Outcomes Rather Than Long-Term Outcomes of Major Adverse Cardiovascular Events

The purpose of our study was to explore the association of blood pressure (BP) changes on short-and long-term outcomes of major adverse cardiovascular events (MACEs) in rural China. This study was designed to learn the effects of BP changes (2004-2008) on short-term (2008-2010, within 2 years of the initial examination) and long-term (2008-2017) outcomes of MACE, including 24 285 and 27 290 participants, respectively. In this study, 423 (short-term) and 1952 (long-term) MACEs were identified. For prehypertension to hypertension, the risk of long-term stroke was increased (hazard ratio [HR] = 1.18 [1.00-1.39]). For hypertension to prehypertension, the short-term MACE risk (0.65 [0.47-0.90]), short-term stroke risk (0.45 [0.26-0.76]), and long-term stroke risk (0.83 [0.70-0.99]) all decreased. Short-term outcomes conferred a stronger impact than long-term outcomes (Fisher Z test, measured as the difference of β coefficients, all P < .05).

Impact of Prehypertension on the Risk of Major Adverse Cardiovascular Events in a Chinese Rural Cohort

BACKGROUND

The study was performed to investigate the impact of prehypertension defined by the Seventh Report of the Joint National Committee on Prevention, Detection, Evaluation, and Treatment of High Blood Pressure (JNC7) on the risk of major adverse cardiovascular events (MACE) in a Chinese rural cohort.

METHODS

The epidemiological prospective cohort study included 38,765 participants aged ≥35 years followed for a median of 12.5 years-divided into normal BP (n = 7,366), prehypertension (n = 18,095), and hypertension groups (n = 13,304)-were enrolled for the final analysis. Follow-up for MACE including cardiovascular disease (CVD) death, stroke and myocardial infarction (MI) was conducted. Adjusted Cox proportional hazards models were used to estimate hazard ratios (HR) and 95% confidence intervals (CI).

RESULTS

The age and sex-adjusted incidence of MACE and its subtypes rose progressively with elevation of BP levels (P < 0.001). After adjusting multivariable Cox proportional hazards, significant increases were observed from the prehypertensive group for incident MACE (HR = 1.337, 95% CI: 1.186-1.508, P < 0.001), CVD mortality (HR = 1.331, 95% CI: 1.109-1.597, P = 0.002), and stroke (HR = 1.424, 95% CI：1.237-1.639, P < 0.001) but not MI (P > 0.05) compared with normal BP.

CONCLUSION

Prehypertensive individuals had a greater risk of incident MACE, CVD mortality, and stroke, implying that improvements in BP monitoring and early intervention in individuals with prehypertension in rural China are urgently needed.

Effects of long- and short-term body mass index changes on incident hypertension are different

OBJECTIVES

The aim of this study was to evaluate hypertension risk associated with long- and short-term body mass index (BMI) changes.

METHODS

This prospective cohort study included four examinations: 2004 to 2006, 2008, 2010, and 2017. Adjusted Cox proportional hazards models were used to estimate hazard ratios (HRs) and 95% confidence intervals (CIs) of BMI changes on incident hypertension. The difference of β coefficients between long- and short-term BMI changes were examined using Fisher Z-test.

RESULTS

Relative to stable, normal BMI, both long- and short-term elevated BMI conferred an increased risk for hypertension, with HRs of 1.507 (95% CI, 1.286-1.767) and 1.197(95% CI, 1.019-1.405), respectively. In contrast, relative to stable overweight, both long- and short-term decreased BMI conferred a reduced risk for hypertension, with HRs of 0.651(95% CI, 0.536-0.789) and 0.775 (0.625-0.962), respectively. Additionally, for BMI changing from normal to overweight, long-term changes were relatively more strongly associated with increased risk for incident hypertension than short-term based on regression coefficients (β = 0.410 versus β = 0.179, P < 0.001). For BMI changing from overweight to normal, long-term changes were relatively more strongly associated with lower risk than short-term based on regression coefficients (β = -0.430 versus β = -0.254, P = 0.007). Additionally, there was no correlation between absolute changes in BMI and systolic blood pressure for long- (P = 0.744) and short-term (P = 0.097).

CONCLUSION

For participants with normal BMI, risk tended to be higher in adults whose elevated BMI occurred during the long-term. For those who are overweight, long-term decreased BMI can reduce the risk for incident hypertension to a greater extent. No correlation was found between absolute changes in BMI and systolic blood pressure.

Associations between ideal blood pressure based on different BMI categories and stroke incidence

OBJECTIVES

The 2017 American College of Cardiology/American Heart Association (ACC/AHA) Guideline for high blood pressure (BP) in adults redefined hypertension as SBP at least 130 mmHg or DBP at least 80 mmHg. However, the optimal BP for different BMI population to reduce stroke incidence is uncertain.

METHODS

A prospective cohort study was designed by four examinations: baseline (2004-2006), 2008, 2010 and 2017 follow-up. The study group composed of 36 352 individuals, to determine the ideal BP range to reduce stroke incidence of two BMI level, adjusted Cox proportional hazards models were utilized to establish the associations between SBP/DBP and the risk of stroke incident. Then, the restricted cubic spline regression was applied to find the ideal range of SBP/DBP values for two kinds of BMI categories definitions.

RESULTS

During a median follow-up period of 12.5 years, 2548 (7.0%) nonstroke individuals at baseline developed incident stroke. After fully adjusting confounding factors, SBP (per 20 mmHg increase) and DBP (per 10 mmHg increase) are independently associated with the risk of stroke incidence [SBP, hazard ratio = 1.277, 95% confidence interval (95% CI), 1.217-1.340, P < 0.001; DBP, hazard ratio = 1.138, 95% CI, 1.090-1.189, P < 0.001].

CONCLUSION

Our study revealed that the ideal BP for a population with BMI less than 24 kg/m was less than 130/80 mmHg, whereas the ideal BP for BMI at least 24 kg/m was less than 120/80 mmHg. The sensitivity analyses between BMI less than 25 kg/m and BMI at least 25 kg/m showed similar findings. This finding provides more accurate primary prevention strategies based on various BMI populations.

Prediction model and assessment of probability of incident hypertension: the Rural Chinese Cohort Study

We aimed to develop a hypertension risk-prediction model among rural Chinese people. We included data for 9034 participants aged 18-70 years without baseline hypertension, diabetes, myocardial infarction, stroke, or heart failure in a rural Chinese cohort. The sample was randomly divided into a training set (60%) and testing set (40%). We used shrinkage estimates by the least absolute shrinkage and selection operator method in fitting a logistic model to explore the possibility of predicting the risk of hypertension in the training set. On multivariable analysis, age, parental hypertension, systolic and diastolic blood pressure, body mass index (BMI), and age by BMI were significant predictors of hypertension. After bootstrap validation, the corrected C-index, calibration intercept, and calibration slope were 0.7932, -0.0041, and 0.9938, respectively for the training set. Our model also had good discrimination (C-index, 0.7914 [95% CI 0.773-0.809]) and calibration (Hosmer-Lemeshow χ² = 14.366, P = 0.073) for the testing set. Nomograms and score-based models were used to favor the clinical implementation and workability of the risk model. According to the risk score based on these factors, the cumulative risk for hypertension was <20% for 57.62% of participants, 20-40% risk for 27.24%, 40-60% for 12.19%, and >60% for 2.96% during the 6-year follow-up. The score-based area under the receiver operating characteristic curve for the present model and the Framingham risk-score model were similar (P = 0.282). The hypertension risk-prediction system we developed provides convenient approaches to identify individuals at high risk of hypertension.

The Association of Stage 1 Hypertension Defined by the 2017 ACC/AHA Guideline with Stroke and Its Subtypes among Elderly Chinese

Background

The 2017 American College of Cardiology and American Heart Association hypertension guideline updated stage 1 hypertension definition as systolic blood pressure range from 130 to 139 mmHg or diastolic blood pressure from 80 to 89 mmHg. However, the association of stage 1 hypertension with stroke and its subtypes among the older population in rural China remains unclear.

Methods

This population-based cohort study consisted of 7,503 adults aged ≥60 years with complete data and no cardiovascular disease at baseline from rural areas of Fuxin County, Liaoning province, China. Follow-up for the new cases of stroke was conducted from the end of the baseline survey to the end of the third follow-up survey (January 1, 2007-December 31, 2017). Adjusted Cox proportional hazards models were used to estimate hazard ratios and 95% confidence intervals with the normal blood pressure as a reference, and calculated population attributable risk was based on prevalence and hazard ratios.

Results

During a median follow-up of 12.5 years, we observed 1,159 first-ever incident stroke (774 ischemic, 360 hemorrhagic, and 25 uncategorized). With the blood pressure <120/<80 mmHg as a reference, stage 1 hypertension showed the adjusted hazard ratios (95% confidence intervals) of 1.45 (1.11-1.90) for all stroke, 1.65 (1.17-2.33) for ischemic stroke, and 1.17 (0.74-1.85) for hemorrhagic stroke, respectively. In this study, the population attributable risk values of stage 1 hypertension were 10.22% (2.64%-18.56%) for all stroke and 14.34% (4.23%-25.41%) for ischemic stroke.

Conclusion

Among adults aged ≥60 years in rural China, stage 1 hypertension defined by 2017 American College of Cardiology and American Heart Association hypertension guideline was independently associated with the increased risk of all stroke and ischemic stroke, excluding hemorrhagic stroke.

Development and validation of prediction models for hypertension risks in rural Chinese populations

Background

Various hypertension predictive models have been developed worldwide; however, there is no existing predictive model for hypertension among Chinese rural populations.

Methods

This is a 6-year population-based prospective cohort in rural areas of China. Data was collected in 2007-2008 (baseline survey) and 2013-2014 (follow-up survey) from 8319 participants ranging in age from 35 to 74 years old. Specified gender hypertension predictive models were established based on multivariate Cox regression, Artificial Neural Network (ANN), Naive Bayes Classifier (NBC), and Classification and Regression Tree (CART) in the training set. External validation was conducted in the testing set. The estimated models were assessed by discrimination and calibration, respectively.

Results

During the follow-up period, 432 men and 604 women developed hypertension in the training set. Assessment for established models in men suggested men office-based model (M1) was better than others. C-index of M1 model in the testing set was 0.771 (95% confidence Interval (CI) = 0.750, 0.791), and calibration χ² = 6.3057 (P = 0.7090). In women, women office-based model (W1) and ANN were better than the other models assessed. The C-indexes for the W1 model and the ANN model in the testing set were 0.765 (95% CI = 0.746, 0.783) and 0.756 (95% CI = 0.737, 0.775) and the calibrations χ² were 6.7832 (P = 0.1478) and 4.7447 (P = 0.3145), respectively.

Conclusions

Not all machine-learning models performed better than the traditional Cox regression models. The W1 and ANN models for women and M1 model for men have better predictive performance which could potentially be recommended for predicting hypertension risk among rural populations.

Association between body mass index changes and short- and long-term outcomes of hypertension in a Chinese rural cohort study

This study aimed to investigate the effect of body mass index (BMI) changes on hypertension among rural areas of China. A population-based sample of 13,263 and 5944 rural Chinese people aged ≥35 years and without hypertension at baseline was included in our analysis of BMI changes (from (2004-2006) to 2008) and short- and long-term outcomes of hypertension (from 2008 to 2010 and 2010 to 2017). The participants were divided into four groups by a comprehensive cross-sectional combination according to baseline BMI (18.5-24 vs. ≥24 kg/m²) and follow-up changes (decreased vs. increased). Adjusted Cox proportional hazards models were used to estimate hazard ratios (HRs) and 95% confidence intervals (95% CIs). During a median follow-up period of 4.8 (short-term) and 11.7 (long-term) years, 2299 (17.33%) and 2020 (33.98%) participants developed hypertension, respectively. For participants with a baseline BMI ≥ 24 kg/m², when BMI decreased in follow-ups, the multivariable-adjusted HRs (95% CI) of short-term hypertension were 0.898 (0.857-0.942). For baseline 18.5 kg/m² ≤ BMI < 24 kg/m², when BMI increased in follow-ups, the risks of short-term hypertension were 1.103 (1.068-1.139). We detected that BMI changes had a lower impact on the incidence of hypertension in long-term than short-term. Our study indicated that BMI changes were significantly associated with the incidence of hypertension for the short-term, and it had a stronger impact on short-term outcomes than long-term. Managing weight by lifestyle modification was particularly important for the primary prevention of hypertension in rural Chinese population.

Stage 1 hypertension defined by the 2017 ACC/AHA guideline predicts future cardiovascular events in elderly Chinese individuals

The 2017 American College of Cardiology and American Heart Association (ACC/AHA) hypertension guideline updated stage 1 hypertension defined as systolic blood pressure (SBP) of 130‐139 mm Hg or diastolic blood pressure (DBP) of 80‐89 mm Hg. However, the impact of 1 hypertension that affects future cardiovascular risk remains unclear among older adults in rural China. The prospective cohort study included 7503 adults aged ≥60 years with complete data and no cardiovascular disease (CVD) at baseline. Follow‐up for the new adverse events was conducted from the end of the baseline survey to the end of the third follow‐up survey (2007.01‐2017.12). Cox proportional hazards models were used to estimate hazard ratios (HRs) and 95% confidence intervals (95% CIs) for blood pressure (BP) classifications and adverse events with normal BP as reference (< 120/80 mm Hg). During the 57 290 person‐years follow‐up period, 2261 all‐cause mortality, 1271 CVD mortality, 1159 stroke, and 347 myocardial infarctions (MI) occurred. Patients with stage 1 hypertension versus normal BP had HRs (95% CI) of 1.068 (0.904‐1.261) for all‐cause mortality, 1.304 (1.015‐1.675) for CVD mortality, 1.449 (1.107‐1.899) for stroke, and 1.735 (1.051‐2.863) for MI, respectively. In conclusion, among adults aged ≥60 years, stage 1 hypertension revealed an increased hazard of CVD mortality, stroke, and MI, which is complementary evidence for the application of 2017 ACC/AHA hypertension guidelines in an older Chinese population. Therefore, BP control in patients with stage 1 hypertension may be beneficial to reduce the hazard of CVD in elderly Chinese individuals.

Short-Term and Long-Term Blood Pressure Changes and the Risk of All-Cause and Cardiovascular Mortality

Background

Few studies compared the effects of BP changes in short- and long-terms on all-cause mortality and CVD mortality.

Methods

We performed a 12.5-year follow-up study to examine the association between short- (2008 to 2010) and long-term [baseline (2004-2006) to 2010] BP changes and the risk of mortality (2010 to 2017) in the Fuxin prospective cohort study. The Cox proportional hazards model was used for this study, and the average BP was stratified according to the Seven Joint National Committee (JNC7).

Results

We identified 1496 (805 CVD deaths) and 2138 deaths (1222 CVD deaths) in short- and long-term study. Compared with BP maintainer, in short-term BP changes, for participants from normotension or prehypertension to hypertension, the hazards ratios (HRs) and 95% confidence intervals (CIs) of all-cause mortality were 1.948 (1.118-3.392) and 1.439 (1.218-1.700), respectively, while for participants from hypertension to prehypertension, the HRs (95% CIs) were 0.766 (0.638-0.899) for all-cause mortality and 0.729 (0.585-0.908) for CVD mortality, respectively. In long-term BP changes, for participants from normotension or prehypertension to hypertension, the HRs (95% CIs) of all-cause mortality were 1.738 (1.099-2.749) and 1.203 (1.023-1.414), and they were 2.351 (1.049-5.269) and 1.323 (1.047-1.672) for CVD mortality, respectively. In addition, the effects of short-term BP changes on all-cause and CVD mortality, measured as regression coefficients (β), were significantly greater than those in long-term change (all P<0.05).

Conclusions

Our study emphasizes that short-term changes in BP have a greater impact on all-cause and CVD mortality than long-term changes and assess the cut-off value of the changes in blood pressure elevation.

Short-term blood pressure changes have a more strong impact on stroke and its subtypes than long-term blood pressure changes

Background

Elevated blood pressure (BP) is closely related to stroke and its subtypes. However, different time periods changes in BP may result in differential risk of stroke.

Hypothesis

Short‐term blood pressure changes have a more strong impact on stroke and its subtypes than long‐term blood pressure changes.

Methods

We designed the study on the effects of short‐ (2008‐2010) and long‐term (2004‐2010) BP changes on stroke events (2011‐2017), including 22 842 and 28 456 subjects, respectively. The difference in β coefficients between short‐ and long‐term BP changes on the effects of stroke were examined using the Fisher Z test.

Results

During a median 12.5‐year follow‐up period, 1014 and 1505 strokes occurred in short‐ and long‐term groups. In short‐term group, going from prehypertension to hypertension, the risk of stroke events increased (stroke: hazard ratio [HR] = 1.537 [1.248‐1.894], ischemic stroke: 1.456 [1.134‐1.870] and hemorrhagic stroke: 1.630 [1.099‐2.415]); going from hypertension to prehypertension, the risk of stroke events decreased (stroke:0.757 [0.619‐0.927] and hemorrhagic stroke:0.569 [0.388‐0.835]). Similarly, in long‐term group, going from prehypertension to hypertension, individuals had an increased risk of stroke (1.291, 1.062‐1.569) and hemorrhagic stroke (1.818, 1.261‐2.623); going from hypertension to prehypertension, participants had a decreased risk of stroke (0.825, 0.707‐0.963) and hemorrhagic stroke (0.777, 0.575‐0.949). Furthermore, the effects of BP changes during short‐term period on stroke events were greater than that in long‐term period.

Conclusions

Short‐ and long‐terms BP changes were both associated with the risk of stroke events. Furthermore, short‐term BP changes had a stronger impact than did long‐term changes on risk of stroke events.

Future Direction for Using Artificial Intelligence to Predict and Manage Hypertension

PURPOSE OF REVIEW

Evidence that artificial intelligence (AI) is useful for predicting risk factors for hypertension and its management is emerging. However, we are far from harnessing the innovative AI tools to predict these risk factors for hypertension and applying them to personalized management. This review summarizes recent advances in the computer science and medical field, illustrating the innovative AI approach for potential prediction of early stages of hypertension. Additionally, we review ongoing research and future implications of AI in hypertension management and clinical trials, with an eye towards personalized medicine.

RECENT FINDINGS

Although recent studies demonstrate that AI in hypertension research is feasible and possibly useful, AI-informed care has yet to transform blood pressure (BP) control. This is due, in part, to lack of data on AI's consistency, accuracy, and reliability in the BP sphere. However, many factors contribute to poorly controlled BP, including biological, environmental, and lifestyle issues. AI allows insight into extrapolating data analytics to inform prescribers and patients about specific factors that may impact their BP control. To date, AI has been mainly used to investigate risk factors for hypertension, but has not yet been utilized for hypertension management due to the limitations of study design and of physician's engagement in computer science literature. The future of AI with more robust architecture using multi-omics approaches and wearable technology will likely be an important tool allowing to incorporate biological, lifestyle, and environmental factors into decision-making of appropriate drug use for BP control.

Developing and validating a new precise risk-prediction model for new-onset hypertension: The Jichi Genki hypertension prediction model (JG model)

No integrated risk assessment tools that include lifestyle factors and uric acid have been developed. In accordance with the Industrial Safety and Health Law in Japan, a follow-up examination of 63 495 normotensive individuals (mean age 42.8 years) who underwent a health checkup in 2010 was conducted every year for 5 years. The primary endpoint was new-onset hypertension (systolic blood pressure [SBP]/diastolic blood pressure [DBP] ≥ 140/90 mm Hg and/or the initiation of antihypertensive medications with self-reported hypertension). During the mean 3.4 years of follow-up, 7402 participants (11.7%) developed hypertension. The prediction model included age, sex, body mass index (BMI), SBP, DBP, low-density lipoprotein cholesterol, uric acid, proteinuria, current smoking, alcohol intake, eating rate, DBP by age, and BMI by age at baseline and was created by using Cox proportional hazards models to calculate 3-year absolute risks. The derivation analysis confirmed that the model performed well both with respect to discrimination and calibration (n = 63 495; C-statistic = 0.885, 95% confidence interval [CI], 0.865-0.903; χ² statistic = 13.6, degree of freedom [df] = 7). In the external validation analysis, moreover, the model performed well both in its discrimination and calibration characteristics (n = 14 168; C-statistic = 0.846; 95%CI, 0.775-0.905; χ² statistic = 8.7, df = 7). Adding LDL cholesterol, uric acid, proteinuria, alcohol intake, eating rate, and BMI by age to the base model yielded a significantly higher C-statistic, net reclassification improvement (NRI), and integrated discrimination improvement, especially NRI_non-event (NRI = 0.127, 95%CI = 0.100-0.152; NRI_non-event  = 0.108, 95%CI = 0.102-0.117). In conclusion, a highly precise model with good performance was developed for predicting incident hypertension using the new parameters of eating rate, uric acid, proteinuria, and BMI by age.

Recent development of risk-prediction models for incident hypertension: An updated systematic review

BACKGROUND

Hypertension is a leading global health threat and a major cardiovascular disease. Since clinical interventions are effective in delaying the disease progression from prehypertension to hypertension, diagnostic prediction models to identify patient populations at high risk for hypertension are imperative.

METHODS

Both PubMed and Embase databases were searched for eligible reports of either prediction models or risk scores of hypertension. The study data were collected, including risk factors, statistic methods, characteristics of study design and participants, performance measurement, etc.

RESULTS

From the searched literature, 26 studies reporting 48 prediction models were selected. Among them, 20 reports studied the established models using traditional risk factors, such as body mass index (BMI), age, smoking, blood pressure (BP) level, parental history of hypertension, and biochemical factors, whereas 6 reports used genetic risk score (GRS) as the prediction factor. AUC ranged from 0.64 to 0.97, and C-statistic ranged from 60% to 90%.

CONCLUSIONS

The traditional models are still the predominant risk prediction models for hypertension, but recently, more models have begun to incorporate genetic factors as part of their model predictors. However, these genetic predictors need to be well selected. The current reported models have acceptable to good discrimination and calibration ability, but whether the models can be applied in clinical practice still needs more validation and adjustment.

Incident hypertension and its prediction model in a prospective northern urban Han Chinese cohort study

Trends in incidence and prevalence of hypertension are grave in China and identifying high-risk, non-hypertension individuals for intervention may delay hypertension onset. We aimed to investigate the incidence of hypertension in northern urban Han Chinese population and construct multivariable hypertension prediction models through the prospective cohort, which included 7537 men and 4960 women free of hypertension at baseline between 2005 and 2010. During 38 958 person-years of follow-up, 2785 participants (men, 72.57%; women, 27.43%) developed hypertension. The incidence density of hypertension was 71.48 per 1000 person-year. In multivariable backward cox analyses, age, body mass index, systolic blood pressure (SBP), diastolic blood pressure (DBP), fasting blood glucose and current drinking were retained for both men and women, while gamma-glutamyl transferase only for men, total cholesterol, neutrophil granulocyte and current smoking only for women. The area under receiver operating characteristic curve (AUC) was 0.761 (95% confidence interval (CI), 0.752-0.771) for men and 0.753 (95% CI, 0.741-0.765) for women, even after 10-fold cross-validation, the AUC was 0.760 (95% CI, 0.751-0.770) for men and 0.749 (95% CI, 0.737-0.761) for women. Through risk stratification, the absolute risk of incident hypertension in 5 years at moderate, high and very high risk level was 2.13, 3.84 and 6.14 times that of those who were at low risk in men, and 1.30, 2.56 and 6.01 times that of those who were at low risk in women. Our findings identified predictors of incident hypertension and indicated that the sex-specific multivariable prediction models would be simply used to estimate the risk of incident hypertension.

Relationship of Blood Pressure With Mortality and Cardiovascular Events Among Hypertensive Patients aged ≥ 60 years in Rural Areas of China: A Strobe-Compliant Study

The Eighth Joint National Committee (JNC-8) panel recently recommended a systolic blood pressure (BP) threshold of ≥ 150 mmHg for the initiation of drug therapy and a therapeutic target of <150/90 mmHg in patients ≥ 60 years of age. However, results from some post-hoc analysis of randomized controlled trials and observational studies did not support these recommendations. In the prospective cohort study, 5006 eligible hypertensive patients aged ≥ 60 years from rural areas of China were enrolled for the present analysis. The association between the average follow-up BP and outcomes (all-cause and cardiovascular death, incident coronary heart disease [CHD], and stroke), followed by a median of 4.8 years, were evaluated using Cox proportional hazards models adjusting for other potential confounders. The relationship between BP (systolic or diastolic) showed an increased or J-shaped curve association with adverse outcomes. Compared with the reference group of BP <140/90 mmHg, the risk of all-cause death (hazard ratio [HR]: 2.698; 95% confidence interval [CI]: 1.989-3.659), cardiovascular death (HR: 2.702; 95% CI: 1.855-3.935), incident CHD (HR: 3.263; 95% CI: 2.063-5.161), and stroke (HR: 2.334; 95% CI: 1.559-3.945) was still significantly increased in the group with BP of 140-149/<90 mmHg. Older hypertensive patients with BP of 140-149/<90 mmHg were at higher risk of developing adverse outcomes, implying that lenient BP control of 140-149/<90 mmHg, based on the JNC-8 guidelines, may not be appropriate for hypertensive patients aged ≥ 60 years in rural areas of China.