B-Type Natriuretic Peptide and Ventricular Dysfunction in the Prediction of Cardiovascular Events and Death in Hypertension

Risk factors and prediction models for cardiovascular complications of hypertension in older adults with machine learning: A cross-sectional study

Background

Hypertension has emerged as a chronic disease prevalent worldwide that may cause severe cardiovascular complications, particularly in older patients. However, there is a paucity of studies that use risk factors and prediction models for cardiovascular complications associated with hypertension in older adults.

Objectives

To identify the risk factors and develop prediction models for cardiovascular complications among older patients with hypertension.

Methods

A convenience sample of 476 older patients with hypertension was recruited from a university-affiliated hospital in China. Demographic data, clinical physiological indicators, regulatory emotional self-efficacy, medication adherence, and lifestyle information were collected from participants. Binary logistic regression analysis was performed to screen for preliminary risk factors associated with cardiovascular complications. Two machine learning methods, Back-Propagation neural network, and random forest were applied to develop prediction models for cardiovascular complications among the study cohort. The sensitivity, specificity, accuracy, receiver operating characteristic curve, and area under the curve (AUC) values were used to assess the performance of the prediction models.

Results

Binary logistic regression identified nine risk factors for cardiovascular complications among older patients with hypertension. The machine learning models displayed excellent performance in predicting cardiovascular complications, with the random forest model (AUC 0.954) outperforming the Back-Propagation neural network model (AUC 0.811), as confirmed by model comparison analysis. The sensitivity, specificity and accuracy of the Back-Propagation neural network model compared to the random forest model were 74.2% vs. 86.5%, 75.2% vs. 94.3%, and 74.7% vs. 90.4%, respectively.

Conclusion

The machine learning methods employed in this study demonstrated feasibility in predicting cardiovascular complications among older patients with hypertension, with the random forest model based on nine risk factors exhibiting excellent prediction performance. These models could be used to identify high-risk populations and suggest early interventions aimed at preventing cardiovascular complications in such cohorts.

Use of Clinical and Echocardiographic Evaluation to Assess the Risk of Heart Failure

BACKGROUND

Clinical and echocardiographic features predict incident heart failure (HF), but the optimal strategy for combining them is unclear.

OBJECTIVES

This study sought to define an effective means of using echocardiography in HF risk evaluation.

METHODS

The same clinical and echocardiographic evaluation was obtained in 2 groups with HF risk factors: a training group (n = 926, followed to 7 years) and a validation group (n = 355, followed to 10 years). Clinical risk was categorized as low, intermediate, and high using 4-year ARIC (Atherosclerosis Risk In Communities) HF risk score cutpoints of 9% and 33%. A risk stratification algorithm based on clinical risk and echocardiographic markers of stage B HF (SBHF) (abnormal global longitudinal strain [GLS], diastolic dysfunction, or left ventricular hypertrophy) was developed using a classification and regression tree analysis and was validated.

RESULTS

HF developed in 12% of the training group, including 9%, 18%, and 73% of low-, intermediate-, and high-risk patients. HF occurred in 8.6% of stage A HF and 19.4% of SBHF (P < 0.001), but stage A HF with clinical risk of ≥9% had similar outcome to SBHF. Abnormal GLS (HR: 2.92 [95% CI: 1.95-4.37]; P < 0.001) was the strongest independent predictor of HF. Normal GLS and diastolic function reclassified 61% of the intermediate-risk group into the low-risk group (HF incidence: 12%). In the validation group, 11% developed HF over 4.5 years; 4%, 17%, and 39% of low-, intermediate-, and high-risk groups. Similar results were obtained after exclusion of patients with known coronary artery disease. The echocardiographic parameters also provided significant incremental value to the ARIC score in predicting new HF admission (C-statistic: 0.78 [95% CI: 0.71-0.84] vs 0.83 [95% CI: 0.77-0.88]; P = 0.027).

CONCLUSIONS

Clinical risk assessment is adequate to classify low and high HF risk. Echocardiographic evaluation reclassifies 61% of intermediate-risk patients.

The underlying mechanism of transcription factor IRF1, PRDM1, and ZNF263 involved in the regulation of NPPB rs3753581 on pulse pressure hypertension

To investigate the correlation between NPPB gene variants and pulse pressure hypertension and the underlying regulatory mechanisms and try to confirm that NPPB may be a potential molecular target of gene therapy for pulse pressure hypertension. A total of 898 participants were recruited from the First Affiliated Hospital of Fujian Medical University and the plasmids with differential expression of NPPB were constructed. Genotype distribution of NPPB(rs3753581, rs198388, and rs198389)was analyzed and the expression of N-terminal pro-B-type natriuretic peptide(NT-proBNP) and renin-angiotensin -aldosterone system(RAAS) related indicators were identified in the groups studied. According to a genotype analysis, there was a significant difference in the genotype distribution of NPPB rs3753581 among the groups (P=0.034). In logistic regression analysis, NPPB rs3753581 TT was associated with a 1.8-fold greater risk of pulse pressure hypertension than NPPB rs3753581 GG (odds ratio = 1.801; 95% confidence interval: 1.070-3.032; P=0.027). The expression of NT-proBNP and RAAS related indicators in clinical and laboratory samples showed striking differences. The activity of firefly and Renilla luciferase in pGL-3-NPPB-luc (-1299G) was higher than pGL-3-NPPBmut-luc(-1299T)(P<0.05). The binding of NPPB gene promoter rs3753581 (-1299G) with transcription factors IRF1, PRDM1, and ZNF263 was predicted and validated by the bioinformatics software TESS and chromatin immunoprecipitation(P<0.05). NPPB rs3753581 was correlated with genetic susceptibility to pulse pressure hypertension and the transcription factors IRF1, PRDM1, and ZNF263 may be involved in the regulation of NPPB rs3753581 promoter (-1299G) on the expression of NT-proBNP/RAAS.

Growth stimulation expressed gene 2 (ST2): Clinical research and application in the cardiovascular related diseases

As an interleukin (IL)-1 receptor family member, scientists found that when circulating soluble growth stimulation expressed gene 2 (sST2) is low, its ligand, IL-33, will bind to ST2L to exert protective effects on various types of cells. On the other hand, competitive binding of IL-33 occurs when sST2 concentrations are increased, followed by a reduction in the amount available for cell protection. Based on this mechanism, the usage of sST2 is to identify the population of high-risk patients with cardiovascular disease. In recent years, the role of serum sST2 in the occurrence, diagnosis, prognosis, and treatment of cardiovascular diseases has been gradually accepted by doctors. This manuscript systemically reviews the biological functions and applications of sST2 in disease diagnosis and treatment, especially for cardiovascular diseases. In clinical testing, since IL-33 can negatively impact sST2 measurement accuracy, the properties of current assay kits have been summarized and discussed to provide a clear view of the clinical chemistry results. Although sST2 is a promising biomarker, there are few quantitative approaches available for clinical testing. In this context, a mass spectrometry (MS)-based approach might be an option, as this is a powerful analytical tool to distinguish structurally related molecules in the matrix and decrease false-positive results in clinical testing. Moreover, approaches developed based on MS would be an ideal way to further study sST2 standardization.

Plasma Ceramides and Cardiovascular Events in Hypertensive Patients at High Cardiovascular Risk

BACKGROUND

Plasma ceramides (Cer) have been used to evaluate risk of cardiovascular (CV) events in patients with coronary heart disease. We investigated the performance of ceramides and ceramide score (CERT) in hypertensive patients at high CV risk.

METHODS

Seven ceramides were analyzed using ultra-performance liquid chromatography-tandem mass spectrometry in 920 essential hypertension patients at high CV risk, who visited Beijing Anzhen Hospital from September 2016 to September 2018 (median age: 49 years, 562 males). All patients were followed up for major adverse cardiovascular events (MACE), which included incident acute coronary syndrome, heart failure, stroke, and CV death.

RESULTS

During mean 2.3-year follow-up, 71 patients experienced MACE. Cer(d18:1/16:0), Cer(d18:1/22:0), and Cer(d18:1/24:0) were highly significant in predicting MACE [multiadjusted hazard ratios (95% confidence interval, CI) per SD were 1.76 (1.34-2.30), 0.55 (0.41-0.73), and 0.66 (0.47-0.92), respectively]. Compared with traditional variables (comprising presence of CV risk factors, hypertension-mediated organ damage, and comorbidities), a novel CERT for hypertensive patients (CERT-HBP), composed of Cer(d18:1/16:0), Cer(d18:1/24:1), and their ratios to Cer(d18:1/24:0) and Cer(d18:1/22:0), respectively, increased the C-statistic from 0.751 (95% CI, 0.697-0.806) to 0.791 (95% CI, 0.737-0.845), P = 0.010. Net reclassification improvement and integrated discrimination improvement were 0.648 (95% CI, 0.421-0.885, P < 0.001) and 0.046 (95% CI, 0.025-0.068, P < 0.001), respectively.

CONCLUSIONS

A ceramide-based CERT-HBP was established to evaluate risk of MACE in hypertensive patients at high CV risk. This may improve identification of high-risk patients requiring increased attention and aggressive therapy.

CLINICAL TRIALS REGISTRATION

Trial Number NCT03708601.

FKBPL is associated with metabolic parameters and is a novel determinant of cardiovascular disease

Type 2 diabetes (T2D) is associated with increased risk of cardiovascular disease (CVD). As disturbed angiogenesis and endothelial dysfunction are strongly implicated in T2D and CVD, we aimed to investigate the association between a novel anti-angiogenic protein, FK506-binding protein like (FKBPL), and these diseases. Plasma FKBPL was quantified by ELISA cross-sectionally in 353 adults, consisting of 234 T2D and 119 non-diabetic subjects with/without CVD, matched for age, BMI and gender. FKBPL levels were higher in T2D (adjusted mean: 2.03 ng/ml ± 0.90 SD) vs. non-diabetic subjects (adjusted mean: 1.79 ng/ml ± 0.89 SD, p = 0.02), but only after adjustment for CVD status. In T2D, FKBPL was negatively correlated with fasting blood glucose, HbA1c and diastolic blood pressure (DBP), and positively correlated with age, known diabetes duration, waist/hip ratio, urinary albumin/creatinine ratio (ACR) and fasting C-peptide. FKBPL plasma concentrations were increased in the presence of CVD, but only in the non-diabetic group (CVD: 2.02 ng/ml ± 0.75 SD vs. no CVD: 1.68 ng/ml ± 0.79 SD, p = 0.02). In non-diabetic subjects, FKBPL was positively correlated with an established biomarker for CVD, B-type Natriuretic Peptide (BNP), and echocardiographic parameters of diastolic dysfunction. FKBPL was a determinant of CVD in the non-diabetic group in addition to age, gender, total-cholesterol and systolic blood pressure (SBP). FKBPL may be a useful anti-angiogenic biomarker in CVD in the absence of diabetes and could represent a novel CVD mechanism.

Heart Failure in Sub-Saharan Africa

Heart failure is a growing problem in sub-Saharan Africa. This arises as the prevalence of risk factors for cardiovascular disease rises, life expectancy increases and causes of heart failure more common in Africa, such as rheumatic heart disease and endomyocardial fibrosis, continue to be a significant issue. Lack of access to diagnostics is an issue with the expense and technical expertise required for echocardiography limiting access. Biomarker strategies may play a role here. Access to essential medicines is also limited and requires a renewed focus by the international community to ensure that appropriate medications are readily available, similar to that which has been implemented for HIV and malaria.