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Background Diabetes is considered to be one of the most important metabolic conditions causing left ventricular (LV) dysfunction, one of which is Left ventricular hypertrophy (LVH). Increased left ventricular mass (LVM) and left ventricular mass index (LVMI) are significant predictors of LVH. Aim This study aims to illustrate the significance of using echocardiography to detect left ventricular hypertrophy (as a type of LV dysfunction) in normotensive patients with type 2 diabetes mellitus. Materials and methods The study included 100 participants who were distributed into two groups: group A included normotensive patients with type 2 DM and group B included normotensive non-diabetic patients as a control group. Results LVM values were significantly higher in group A patients compared to group B (187.11 ± 60.83 vs. 119.15 ± 41.87, p <  0.001). Also, LVMI values were significantly higher in group A in comparison to group B (96.64 ± 29.84 vs. 63.17 ± 20.38, p <  0.001). The proportion of abnormal LVMI was higher in group A than group B (56% vs. 6%, p <  0.001). There was a statistically significant positive correlation between LVM and several study parameters including disease duration ( r =  0.369, p  = 0.008), FBS ( r =  0.478, p <  0.001), 2HPP (0.400, p  = 0.004), HA1C (%) ( r =  0.589, p  = 0.003), LVEDD ( r =  0.790, p <  0.001), LVESD ( r =  0.388, p  = 0.005), SWT ( r =  0.897, p <  0.001), PWT ( r =  0.808, p <  0.001), and LA ( r =  0.322, p  = 0.022). Conclusion Left ventricular mass was found to be significantly higher in normotensive type 2 DM patients in comparison to the normotensive non-diabetic control group. LVM is a good marker of LVH among normotensive diabetics and significantly correlates with DM control and duration.

Background Left ventricular mass (LVM) is an independent risk factor for the prediction of cardiac events. Its assessment is a clinically important diagnostic procedure in cardiology and may be performed by Computed Tomography (CT). The aim of this study was to assess the correlation between the cardiac left ventricular shell volume (LVShV) determined by postmortem Computed Tomography (PMCT) and the anatomic LVM obtained at autopsy and to calculate the myocardial tissue density. Methods A total of 109 deceased individuals were examined with a 64-slice CT scanner and LVShV was determined. At autopsy, the left ventricle was dissected and weighted. The correlation between LVShV and the anatomic LVM was analysed. Asymmetric left ventricular (LV) hypertrophy was recorded. Inter-observer variability was evaluated, and a density value for myocardial tissue was calculated. Results The mean age of the deceased was 55 ± 16 years, and 58% was men. We found 30 cases of asymmetric LV hypertrophy. A highly positive correlation existed between LVShV and anatomic LVM (r = 0.857; p  < 0.0001), regardless of hypertrophy, asymmetric hypertrophy and gender. The mean difference in the inter-observer variability for LVShV assessment was - 4.4 ml (95% CI: -26.4; 17.6). A linear regression analysis was performed, resulting in a value of 1.265 g/ml for myocardial tissue density. Applying the hitherto used myocardial tissue density of 1.055 g/ml underestimated the anatomic LVM by 18.1% ( p  < 0.0001). Conclusion PMCT is a helpful tool for the assessment of LVM, and LVShV is highly correlated with LVM as assessed by subsequent autopsy. The correlation between the two was independent of gender, hypertrophy and LV asymmetric hypertrophy. We found a higher myocardial tissue density of 1.265 g/ml compared to previous studies. We show that PMCT combined with autopsy may contribute not only to anatomical but also clinical knowledge.

Left ventricular hypertrophy is an independent predictor of cardiovascular morbidity and mortality in adults. In children, the primary correlate of left ventricular mass (LVM) is lean body mass, but fat mass, gender and systolic blood pressure are also contributors. LVM can be estimated from echocardiographic measurements, and by indexing this allometrically to height to the 2.7 power, the left ventricular mass index (LVMI) can be calculated. LVMI optimizes detection of left ventricular hypertrophy with established normal curves for children from birth to 18 years. In children with sustained hypertension, 8–41 % have LVMI above the 95th percentile and in 10–15.5 % of these, LVMI is elevated above levels associated with increased mortality in adults. The presence of obesity is associated with higher LVMI than is found in children with hypertension alone. In children with chronic kidney disease, left ventricular hypertrophy develops relatively early and becomes more prevalent as kidney function decreases. In summary, left ventricular hypertrophy is a sensitive marker of target organ damage in children with BP elevation, obesity and chronic kidney disease providing important management information.

The objective of the present study was to investigate the association between N-terminal-pro-brain natriuretic peptide (NT-proBNP) quartiles and the risk of left ventricular hypertrophy (LVH), as well as to assess the association between NT-proBNP and hallmarks of LVH in heart failure (HF)-negative patients. Logistic regression analysis was used to analyze four groups of participants, who were stratified according to NT-proBNP quartiles, in order to investigate the association between NT-proBNP and the risk of LVH. Subsequently, analyses involving uni- and multivariate linear regression were performed to evaluate the associations of NT-proBNP with LV mass (LVM), LVM index (LVMI) and relative wall thickness (RWT). The results indicated that the occurrence of LVH was progressively enhanced along with increasing NT-proBNP quartiles in patients without HF. The univariate logistic regression analysis revealed that the groups of quartiles 4 and 3 carried a 5.254 and 1.757 times greater risk of LVH than the group of the lowest NT-proBNP quartile, respectively. Furthermore, the multivariate logistic regression analysis indicated that, compared with the quartile 1 group, participants in quartiles 2-4 had a significantly increased risk of LVH. In addition, significant positive linear associations of Lg(NT-proBNP) with LVM and LVMI were determined, while a inverse association between Lg(NT-proBNP) and RWT was indicated. The results of the present study suggested that the risk of LVH increased progressively with increasing NT-proBNP quartiles. On the basis of these results, NT-proBNP may be an effective independent prognostic marker for the risk of LVH in patients without HF.

Estimated glomerular filtration rate (eGFR) is an important topic in patients with primary aldosteronism (PA). However, the relationship between left ventricular structure and eGFR is unclear. We conducted a prospective, observational, and cross-sectional study to analyze 168 patients with PA and 168 propensity score-matched patients with essential hypertension (EH) as the control group, matched by age, gender, and systolic blood pressure. In the patients with PA, the eGFR was not correlated with left ventricular mass index (LVMI; r=−0.065, p=0.404), while in the patients with EH, the eGFR was negatively correlated with LVMI (r=−0.309, p<0.001). To test whether eGFR had a non-linear relationship with LVMI among the patients with PA, we stratified the patients with PA according to the tertile of eGFR (low, medium, and high tertile). The medium tertile of patients had a significantly lower LVMI than those in the other two tertiles (LVMI: 143.5±41.6, 120.5±40.5, and 133.1±34.3 g/m2, from the lowest to highest tertile of eGFR; analysis of covariance p=0.032). The medium tertile of eGFR is associated with lowest LVMI. Patients with PA with high and low eGFR were associated with higher LVMI. The findings implied that the reasons for an increased LVMI in patients with PA may be different to those in patients with EH.

Background High reproducibility of LV mass and volume measurement from cine cardiovascular magnetic resonance (CMR) has been shown within single centers. However, the extent to which contours may vary from center to center, due to different training protocols, is unknown. We aimed to quantify sources of variation between many centers, and provide a multi-center consensus ground truth dataset for benchmarking automated processing tools and facilitating training for new readers in CMR analysis. Methods Seven independent expert readers, representing seven experienced CMR core laboratories, analyzed fifteen cine CMR data sets in accordance with their standard operating protocols and SCMR guidelines. Consensus contours were generated for each image according to a statistical optimization scheme that maximized contour placement agreement between readers. Results Reader-consensus agreement was better than inter-reader agreement (end-diastolic volume 14.7 ml vs 15.2–28.4 ml; end-systolic volume 13.2 ml vs 14.0–21.5 ml; LV mass 17.5 g vs 20.2–34.5 g; ejection fraction 4.2 % vs 4.6–7.5 %). Compared with consensus contours, readers were very consistent (small variability across cases within each reader), but bias varied between readers due to differences in contouring protocols at each center. Although larger contour differences were found at the apex and base, the main effect on volume was due to small but consistent differences in the position of the contours in all regions of the LV. Conclusions A multi-center consensus dataset was established for the purposes of benchmarking and training. Achieving consensus on contour drawing protocol between centers before analysis, or bias correction after analysis, is required when collating multi-center results.

Objective :The objective of this study is to establish normal reference ranges for the left ventricular mass (LVM) and LVM index (LVMI) in preterm infants according to the body surface area (BSA) and assess their correlation with body weight and gestational age. Subjects and Methods :In a prospective study, 268 preterm babies who fulfilled the criteria for inclusion were examined. Echocardiograms were performed to measure the LVM and LVMI on 0-6 day (s) of life and at weekly intervals until the babies reached 36 weeks. The preterm infants were divided into six groups according to their BSA: 0.07-0.08 m2, 0.09-0.10 m2, 0.11-0.12 m2, 0.13-0.14 m2, 0.15-0.16 m2, and 0.17-0.19 m2. Results : The mean gestational age was 29.8 (±2.38 standard deviation [SD]) weeks, ranging from 24 to 35 weeks. The mean body weight was 1479 (±413 SD) g, ranging from 588 to 3380 g, and the mean BSA was 0.13 m2, ranging from 0.07 to 0.19 m2. The LVM correlated well with the gestational age, body weight, and BSA. The LVMI correlated well with body weight and BSA. Reference ranges with the mean ± SD, range, and interquartile range were calculated for the LVM and LVMI according to the BSA. A significant gradual increase was observed in a LVM with increasing BSA. Overall, a progressive and significant increase in the LVM was observed during the first 9 weeks of life. Conclusion :The LVM and LVMI exhibited a significant correlation with the BSA and body weight. This study provides reference data that can be used as a normal reference tool for the LVM and LVMI for preterm infants based on the BSA.

Prior small studies have shown multiple benefits of frequent nocturnal hemodialysis compared to conventional three times per week treatments. To study this further, we randomized 87 patients to three times per week conventional hemodialysis or to nocturnal hemodialysis six times per week, all with single-use high-flux dialyzers. The 45 patients in the frequent nocturnal arm had a 1.82-fold higher mean weekly stdKt/Vurea, a 1.74-fold higher average number of treatments per week, and a 2.45-fold higher average weekly treatment time than the 42 patients in the conventional arm. We did not find a significant effect of nocturnal hemodialysis for either of the two coprimary outcomes (death or left ventricular mass (measured by MRI) with a hazard ratio of 0.68, or of death or RAND Physical Health Composite with a hazard ratio of 0.91). Possible explanations for the left ventricular mass result include limited sample size and patient characteristics. Secondary outcomes included cognitive performance, self-reported depression, laboratory markers of nutrition, mineral metabolism and anemia, blood pressure and rates of hospitalization, and vascular access interventions. Patients in the nocturnal arm had improved control of hyperphosphatemia and hypertension, but no significant benefit among the other main secondary outcomes. There was a trend for increased vascular access events in the nocturnal arm. Thus, we were unable to demonstrate a definitive benefit of more frequent nocturnal hemodialysis for either coprimary outcome.

We evaluated the relationship between coronary artery disease (CAD) and left ventricular mass (LVM) as measured by cardiac computed tomography (CT) in young adults ≤40 years of age. We retrospectively enrolled 490 consecutive individuals (383 males; mean age, 35.2 ± 4.4 years) who underwent cardiac CT. CAD was defined by the presence of any plaque detected by coronary CT angiography. Left ventricular (LV) function, including LVM, was automatically measured by a dedicated workstation. LVM and LVM index (LVMi) in patients with CT-detected CAD were compared to those of patients without CT-detected CAD. Logistic regression analysis was used to evaluate the relationship between cardiovascular risk factors and CAD. Fifty-five individuals had CT-detected CAD (11.2 %, 53 males). LVM measured by cardiac CT was 126.9 ± 30.0 g for males and 93.6 ± 20.9 g for females. LVM was higher (117.8 ± 30.8 vs. 133.6 ± 33.1 g, P  < 0.001) in patients with CT-detected CAD compared with patients without CT-detected CAD. Obesity, hypertension, smoking, hypercholesterolemia, LVM and LVMi were predictors of CT-detected CAD. Body mass index ( r  = 0.237, P  < 0.001) and systolic blood pressure ( r  = 0.281, P  < 0.001) were positively correlated with LVM. In the multivariate analysis, LVM [odds ratio (OR) = 1.016] and LVMi (OR = 1.026) remained independent predictors of CAD. LVM and LVMi in patients with CT-detected CAD were higher than that of patients without CT-detected CAD. LVM and LVMi measured by cardiac CT were independent predictors of CAD.