Related Experiment Video
Updated: Jul 1, 2025
Lumped-Parameter and Finite Element Modeling of Heart Failure with Preserved Ejection Fraction
Published on: February 13, 2021
Nomogram-based risk assessment model for left ventricular hypertrophy in patients with essential hypertension:
Chuang-Chang Wang1,2, Li-Keng Liang3, Sheng-Ming Luo2
1Department of Cardiovascular, The Second Affiliated Hospital of Guangzhou University of Chinese Medicine, Guangzhou, China.
Insights
This study developed a better model for assessing left ventricular hypertrophy (LVH) risk by combining clinical factors and biomarkers. The new model accurately identifies patients at higher risk for this hypertensive heart disease.
Area of Science:
- Cardiology
- Hypertension Research
- Biomarker Discovery
Background:
- Left ventricular hypertrophy (LVH) is a significant risk factor for cardiovascular events in patients with hypertension.
- Clinical attributes like gender, age, and renal function, along with biomarkers such as sST2 and NT-proBNP, are implicated in LVH development.
- Effective risk stratification is crucial for managing hypertensive heart disease.
Purpose of the Study:
- To develop and validate a comprehensive risk assessment model for left ventricular hypertrophy (LVH).
- To identify key clinical characteristics and biomarkers associated with LVH in essential hypertension.
- To compare the predictive performance of models based on clinical data, biomarkers, and their combination.
Main Methods:
- A retrospective study involving 417 patients with essential hypertension (EH).
- Development of three multivariate logistic regression models: clinical characteristics, biomarkers (sST2, NT-proBNP), and combined.
- Performance evaluation using Area Under the Curve (AUC) and logistic regression analysis.
Main Results:
- The combined model (Clinical characteristics + Biomarkers) demonstrated superior predictive performance (AUC = 0.83) compared to models using only clinical data (AUC = 0.74) or biomarkers (AUC = 0.75).
- Identified risk factors for LVH include female gender, overweight/obesity, longer hypertension duration, and grade III hypertension.
- Elevated sST2 levels and lower estimated glomerular filtration rate (eGFR) were significant predictors, with sST2 as a risk factor and eGFR as a protective factor.
Conclusions:
- Integrating clinical characteristics with biomarkers significantly enhances the accuracy of LVH risk assessment.
- The developed combined model offers improved stratification for patients with essential hypertension.
- This approach aids in identifying individuals requiring closer monitoring and intervention for hypertensive heart disease.
Abstract:
Left ventricular hypertrophy (LVH) is a hypertensive heart disease that significantly escalates the risk of clinical cardiovascular events. Its etiology potentially incorporates various clinical attributes such as gender, age, and renal function. From mechanistic perspective, the remodeling process of LVH can trigger increment in certain biomarkers, notably sST2 and NT-proBNP. This multicenter, retrospective study aimed to construct an LVH risk assessment model and identify the risk factors. A total of 417 patients with essential hypertension (EH), including 214 males and 203 females aged 31-80 years, were enrolled in this study; of these, 161 (38.6%) were diagnosed with LVH. Based on variables demonstrating significant disparities between the LVH and Non-LVH groups, three multivariate stepwise logistic regression models were constructed for risk assessment: the "Clinical characteristics" model, the "Biomarkers" model (each based on their respective variables), and the "Clinical characteristics + Biomarkers" model, which amalgamated both sets of variables. The results revealed that the "Clinical characteristics + Biomarkers" model surpassed the baseline models in performance (AUC values of the "Clinical characteristics + Biomarkers" model, the "Biomarkers" model, and the "Clinical characteristics" model were .83, .75, and .74, respectively; P < .0001 for both comparisons). The optimized model suggested that being female (OR: 4.26, P <.001), being overweight (OR: 1.88, p = .02) or obese (OR: 2.36, p = .02), duration of hypertension (OR: 1.04, P = .04), grade III hypertension (OR: 2.12, P < .001), and sST2 (log-transformed, OR: 1.14, P < .001) were risk factors, while eGFR acted as a protective factor (OR: .98, P = .01). These findings suggest that the integration of clinical characteristics and biomarkers can enhance the performance of LVH risk assessment.
More Related Videos
07:13A Rat Model of Pressure Overload Induced Moderate Remodeling and Systolic Dysfunction as Opposed to Overt Systolic Heart Failure
Published on: April 30, 2020
07:41Induction and Phenotyping of Acute Right Heart Failure in a Large Animal Model of Chronic Thromboembolic Pulmonary Hypertension
Published on: March 17, 2022
Related Concept Videos
01:17Pathophysiology of Heart Failure
01:19Blood Studies for Cardiovascular System II: CRP, Hcy, and Cardiac Natriuretic Peptide Markers
These markers indicate stress or strain on the heart muscle:
Natriuretic Peptides (BNP)
Cardiac myocytes produce these hormones in response to ventricular stretching...
01:10Pre-Procedural Guidelines for Assessing Blood Pressure
01:23Assessment of blood pressure in brachial artery(two-step method)