Correlation between Left Ventricular Mass Index and Calcium Metabolism in Patients with Essential Hypertension

Serum parathormone, vitamin D and cardiovascular risk factors and markers: A pilot study

BACKGROUND AND AIMS

Vitamin D deficiency is a common cause of secondary hyperparathyroidism, particularly in elderly people. The aim of this study was to evaluate the associations of serum vitamin D and parathormone (PTH) concentrations with blood pressure values and hypertension-mediated target organ damage (HMOD), including left ventricular (LV) hypertrophy and carotid plaque (CP).

METHODS AND RESULTS

We enrolled consecutive patients admitted to the Hypertension Center of Federico II University Hospital in Naples, Italy. All patients underwent carotid doppler ultrasound and echocardiography, measurement of vitamin D and PTH levels and main clinical and laboratory parameters. A total of 126 patients (mean age 54 years, 68% males) were enrolled. Pearson's correlation analysis indicated that PTH levels directly correlated with age, diabetes, dyslipidemia, hypertension, fasting glucose, and LV mass, and inversely with glomerular filtration rate, LDL cholesterol, and vitamin D. Vitamin D levels correlated inversely with PTH, diabetes and CP. Multivariate regression models indicated that an increased LV mass was associated with the presence of obesity (β = 0.342; P = 0.001). Maximal intima-media thickness was significantly associated with older age (β = 0.303; P = 0.033). Combined presence of low vitamin D/high PTH levels were associated with more than 4-fold increased risk of having CP in both univariate (OR = 4.77, p = 0.0001) and multivariate regression analysis (OR = 4.52, p = 0.014).

CONCLUSION

In a population at high cardiovascular risk, vitamin D and PTH levels were not directly associated with blood pressure values and HMOD. Secondary hyperparathyroidism due to vitamin D deficiency is associated with carotid atherosclerosis independently of other common cardiovascular risk factors.

Prevalence of Doppler-Derived Left Ventricular Diastolic Dysfunction Among Newly Diagnosed Hypertensive Patients

BACKGROUND

The initial sign of hypertensive heart disease (HHD) is left ventricular diastolic dysfunction (LVDD), which is caused by remodeling of the left ventricle and left atrium, resulting in impaired relaxation of the left ventricle. LVDD is also partly due to left ventricular hypertrophy (LVH). If left untreated, LVDD can progress to diastolic heart failure and systolic heart failure. In Western countries, the prevalence of LVDD in long-term hypertensive patients ranges from 40.3% to 60%, but it is more common among hypertensive Nigerians. Since systemic hypertension can be asymptomatic in the early stages, it is important to evaluate LVDD early and control blood pressure to slow down its progression.

AIMS AND OBJECTIVES

The study aims to highlight the prevalence of LVDD and to determine the stages of LVDD among newly diagnosed hypertensive patients at the University of Maiduguri Teaching Hospital (UMTH).

METHOD

The study design is a hospital-based, cross-sectional, observational study. The study population consists of 352 consecutive treatment Naïve hypertensive adult patients aged 18 years and above who presented to the Cardiology Clinic of UMTH from June 2019 to June 2021. The study used the diagnostic criteria for LVDD and LVH which were based on the American Society of Echocardiography and the European Association of Cardiovascular Imaging.

RESULTS

A total of 352 newly diagnosed hypertensive patients were recruited, with a mean age of 50.9 ± 11.8 years, and 54.3% were female. The majority of patients (63.6%) were overweight or obese, with a mean body mass index (BMI) of 28.5 ± 4.6 kg/m2. The mean systolic blood pressure (SBP) was 155.7 ± 16.9 mmHg, and the mean diastolic blood pressure (DBP) was 92.8 ± 10.8 mmHg. LVDD was found in 58.5% of the patients, with stage 1 LVDD being the most common (42.6%), followed by stage 2 LVDD (15.9%). The prevalence of LVDD was significantly higher in females compared to males. Patients with LVDD were significantly older and had higher BMI, higher systolic and DBP, higher pulse pressure, higher LAVI, and higher LVMI compared to those without LVDD (P < 0.05).

CONCLUSION

LVDD is highly prevalent among newly diagnosed hypertensive patients, with stage 1 being the most common. Female gender, older age, higher BMI, higher blood pressure, higher LAVI, and higher LVMI were significant predictors of LVDD. Early detection and appropriate management of LVDD may help to prevent adverse cardiovascular outcomes in hypertensive patients.

Leveraging auxiliary measures: a deep multi-task neural network for predictive modeling in clinical research

BACKGROUND

Accurate predictive modeling in clinical research enables effective early intervention that patients are most likely to benefit from. However, due to the complex biological nature of disease progression, capturing the highly non-linear information from low-level input features is quite challenging. This requires predictive models with high-capacity. In practice, clinical datasets are often of limited size, bringing danger of overfitting for high-capacity models. To address these two challenges, we propose a deep multi-task neural network for predictive modeling.

METHODS

The proposed network leverages clinical measures as auxiliary targets that are related to the primary target. The predictions for the primary and auxiliary targets are made simultaneously by the neural network. Network structure is specifically designed to capture the clinical relevance by learning a shared feature representation between the primary and auxiliary targets. We apply the proposed model in a hypertension dataset and a breast cancer dataset, where the primary tasks are to predict the left ventricular mass indexed to body surface area and the time of recurrence of breast cancer. Moreover, we analyze the weights of the proposed neural network to rank input features for model interpretability.

RESULTS

The experimental results indicate that the proposed model outperforms other different models, achieving the best predictive accuracy (mean squared error 199.76 for hypertension data, 860.62 for Wisconsin prognostic breast cancer data) with the ability to rank features according to their contributions to the targets. The ranking is supported by previous related research.

CONCLUSION

We propose a novel effective method for clinical predictive modeling by combing the deep neural network and multi-task learning. By leveraging auxiliary measures clinically related to the primary target, our method improves the predictive accuracy. Based on featue ranking, our model is interpreted and shows consistency with previous studies on cardiovascular diseases and cancers.

Cross-sectional analysis of serum calcium levels for associations with left ventricular hypertrophy in normocalcemia individuals with type 2 diabetes

Background

Left ventricular hypertrophy (LVH) is prevalent in patients with type 2 diabetes mellitus (T2DM). Recent studies show that an increase in albumin-adjusted serum calcium level is associated with an elevated risk of T2DM. We speculate that increased serum calcium levels in T2DM patients are related to LVH prevalence.

Methods

In this echocardiographic study, 833 normocalcemia and normophosphatemia patients with T2DM were enrolled. The associations between serum calcium and metabolic parameters, left ventricular mass index (LVMI), as well as the rate of LVH were examined using bivariate linear correlation, multivariate linear regression and logistic regression, respectively. The predictive performance of serum calcium for LVH was evaluated using the area under the receiver operating characteristic curve (AUC).

Results

Patients with LVH have significantly higher serum calcium than those without LVH. Serum calcium was positively associated with total cholesterol, triglycerides, low-density lipoprotein cholesterol, serum uric acid, HOMA-IR and fasting plasma glucose. Multivariate linear regression analysis demonstrated that serum calcium was independently associated with LVMI (p < 0.001). In comparison with patients in the lowest serum calcium quartile, the odds ratio (OR) for LVH in patients in the highest quartile was 2.909 (95% CI 1.792-4.720; p < 0.001). When serum calcium was analyzed as a continuous variable, per 1 mg/dl increase, the OR (95% CI) for LVH was [2.400 (1.552-3.713); p < 0.001]. Serum calcium can predict LVH (AUC = 0.617; 95% CI (0.577-0.656); p < 0.001).

Conclusions

Albumin-adjusted serum calcium is associated with an increased risk of LVH in patients with T2DM.