Development of a nomogram for screening the risk of left ventricular hypertrophy in Chinese hypertensive patients

Risk factors and a predictive model for left ventricular hypertrophy in young adults with salt-sensitive hypertension

Salt-sensitive hypertension is common among individuals with essential hypertension, and the prevalence of left ventricular hypertrophy (LVH) has increased. However, data from early identification of the risk of developing LVH in young adults with salt-sensitive hypertension are lacking. Thus, the present study aimed to design a nomogram for predicting the risk of developing LVH in young adults with salt-sensitive hypertension. A retrospective analysis of 580 patients with salt-sensitive hypertension was conducted. The training set consisted of 70% (n = 406) of the patients, while the validation set consisted of the remaining 30% (n = 174). Based on multivariate analysis of the training set, predictors for LVH were extracted to develop a nomogram. Discrimination curves, calibration curves, and clinical utility were employed to assess the predictive performance of the nomogram. The final simplified nomogram model included age, sex, office systolic blood pressure, duration of hypertension, abdominal obesity, triglyceride-glucose index, and estimated glomerular filtration rate (eGFR). In the training set, the model demonstrated moderate discrimination, as indicated by an area under the receiver operating characteristic (ROC) curve of 0.863 (95% confidence interval: 0.831-0.894). The calibration curve exhibited good agreement between the predicted and actual probabilities of LVH in the training set. Additionally, the validation set further confirmed the reliability of the prediction nomogram. In conclusions, the simplified nomogram, which consists of seven routine clinical variables, has shown good performance and clinical utility in identifying young adults with salt-sensitive hypertension who are at high risk of LVH at an early stage.

Effect of early endothelial function improvement on subclinical target organ damage in hypertensives

Endothelial dysfunction is acknowledged as a marker for subclinical target organ damage (STOD) in hypertension, though its therapeutic potential has not yet been clarified. This study assessed whether early endothelial function improvement (EEFI) reduced STOD in patients with essential hypertension (EH). We conducted a retrospective cohort analysis of 456 EH patients initially free from STOD. Endothelial function was assessed using brachial artery flow-mediated dilation (FMD), with values ≤ 7.1% indicating dysfunction. Patients were initially categorized by endothelial status (dysfunction: n = 180, normal: n = 276), and further divided into improved or unimproved groups based on changes within three months post-enrollment. During a median follow-up of 25 months, 177 patients developed STOD. The incidence of STOD was significantly higher in patients with initial dysfunction compared to those with normal function. Kaplan-Meier analysis indicated that the improved group had a lower cumulative incidence of STOD compared to the unimproved group (p < 0.05). Multivariable Cox regression confirmed EEFI as an independent protective factor against STOD in EH patients (p < 0.05), regardless of their baseline endothelial status, especially in those under 65 years old, non-smokers, and with low-density lipoprotein cholesterol levels ≤ 3.4 mmol/L. In conclusion, EEFI significantly reduces STOD incidence in EH patients, particularly in specific subgroups, emphasizing the need for early intervention in endothelial function to prevent STOD.

Association between A/G ratio and arterial stiffness among Chinese type 2 diabetics: A cross-sectional study

BACKGROUND

The android-to-gynoid fat ratio (A/G ratio), an emerging indicator of obesity independent of body mass index (BMI), has yet to be conclusively associated with arterial stiffness in type 2 diabetes mellitus (T2DM). This study aimed to construct a nomogram to estimate arterial stiffness risk in diabetics and explore the interaction effect between A/G ratio and traditional obesity indicators on arterial stiffness.

METHODS

1313 diabetics were divided into 2 groups based on arterial stiffness identified by brachial ankle pulse wave velocity (baPWV), and demographic and clinical features were measured. The LASSO and multivariate logistics regression were used to develop the nomogram. Calibration curve, decision curve analysis (DCA) and receiver operating characteristic (ROC) were applied to assess calibration and clinical usefulness. Interaction effect analysis was performed to quantify the interactive relationship of A/G ratio and obesity indicators on arterial stiffness.

RESULTS

6 independent predictors (age, gender, A/G ratio, SBP, LDL-C and HbA1C) were screened to construct a nomogram prediction model. The calibration curve demonstrated satisfactory agreement between predicted and actual probability, and the nomogram exhibited clinical beneficial at the threshold between 8 % and 95 % indicated by DCA. The area under curve (AUC) was 0.918 and 0.833 for training and external set, respectively. Further investigation revealed A/G ratio and BMI acted positively synergistically towards arterial stiffness, and in BMI-based subgroup analysis, elevated A/G ratio was a significant risk factor for arterial stiffness, especially in normal BMI.

CONCLUSIONS

A/G ratio showed a substantial association with arterial stiffness, and the nomogram, incorporating age, gender, A/G ratio, SBP, LDL-C, and HbA1c, exhibited high predictive value. A/G ratio measurement in BMI-normal individuals assisted in identifying cardiovascular diseases early.

Nomogram-based risk assessment model for left ventricular hypertrophy in patients with essential hypertension: Incorporating clinical characteristics and biomarkers

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.

Development and validation of a nomogram for arterial stiffness

Even though as a gold standard for noninvasive measurement of arterial stiffness, carotid-femoral pulse wave velocity (cfPWV) is not widely used in primary healthcare institutions due to time-consuming and unavailable equipment. The aim of this study was to develop a convenient and low-cost nomogram model for arterial stiffness screening. A cross-sectional study was undertaken in the department of general practice, the First Affiliated Hospital of Fujian Medical University. Arterial stiffness was defined as cfPWV ≥ 10 m/s. A total of 2717 participants were recruited to construct the nomogram using the least absolute shrinkage and selection operator and logistic regressions. Receiver operating characteristic (ROC) curve, calibration curve, decision curve analysis, clinical impact curve were used to evaluate the performance of the model. The model was validated internally and externally (399 participants) by bootstrap method. Arterial stiffness was identified in 913 participants (33.60%). Age, sex, waist to hip ratio, systolic blood pressure, duration of diabetes, heart rate were selected to construct the nomogram model. Good discrimination and accuracy were exhibited with area under curve of 0.820 (95% CI 0.803-0.837) in ROC curve and mean absolute error = 0.005 in calibration curve. A positive net benefit was shown in decision curve analysis and clinical impact curve. A satisfactory agreement was displayed in internal validation and external validation. The low cost and user-friendly nomogram is suitable for arterial stiffness screening in primary healthcare institutions.

A nomogram integrating non-ECG factors with ECG to screen left ventricular hypertrophy among hypertensive patients from northern China

OBJECTIVE

We aimed to establish and validate a user-friendly and clinically practical nomogram for estimating the probability of echocardiographic left ventricular hypertrophy (echo-LVH) indexed to BSA among hypertensive patients from northern China.

METHODS

A total of 4954 hypertensive patients were recruited from a population-based cohort study from January 2012 to August 2013. The dataset was randomly split into two sets: training (n = 3303) and validation (n = 1651). Three nomograms were initially constructed. That is the Cornell product nomogram, the non-ECG nomogram, and the integrated nomogram which integrated non-ECG risk factors and Cornell-voltage duration product. The least absolute shrinkage and selection operator strategies were employed to screen for non-ECG features. The performance of the nomograms was evaluated using discrimination, calibration, and decision curve analysis (DCA). The net reclassification improvement (NRI) and integrated discrimination improvement (IDI) were also calculated.

RESULTS

The AUCs, NRIs, IDIs, and DCA curves of the nomograms demonstrated that the integrated nomogram performed best among all three nomograms. The integrated nomogram incorporated age, sex, educational level, hypertension duration, SBP, DBP, eGFR, sleep duration, tea consumption, and the Cornell-voltage duration product. The AUC was 0.758 and had a good calibration (Hosmer-Lemeshow test, P = 0.73). Internal validation showed an acceptable AUC of 0.735 and good calibration was preserved (Hosmer-Lemeshow test, P = 0.19). The integrated nomogram was clinically beneficial across a range of thresholds of 10-50%.

CONCLUSION

The integrated nomogram is a convenient and reliable tool that enables early identification of hypertensive patients at high odds of LVH and can assist clinicians in their decision-making.