Abstract
Background
Left ventricular hypertrophy (LVH) has been associated with oxidative stress, although not with the protein thiolation index (PTI). This study explored the potential use of PTI as a biomarker of oxidative stress in patients with LVH.
Methods
We recruited 70 consecutive patients (n = 35 LVH and n = 35 non-LVH) based on an echocardiography study in our institution (left ventricular mass indexed to body surface area). Plasma levels of both S-thiolated protein and total thiols were measured as biomarkers of oxidative stress by spectrophotometry, and PTI was calculated as the molar ratio between S-thiolated proteins and the total thiol concentration.
Results
Values for plasma S-thiolated proteins were higher in patients with LVH than in the control group (P = 0.01). There were no differences in total thiols between the LVH group and the control group. Finally, PTI was higher in patients with LVH than in the control group (P = 0.001). The area under the ROC curve was 0.75 (95% CI, 0.63–0.86; P<0.001), sensitivity was 70.6%, and specificity was 68.6%, thus suggesting that PTI could be used to screen for LVH. A multivariable logistic regression model showed a positive association (P = 0.02) between PTI and LVH (OR = 1.24 [95% CI, 1.03–1.49]) independently of gender (OR = 3.39 [95% CI, 0.60–18.91]), age (OR = 1.03 [95% CI, 0.96–1.10]), smoking (OR = 5.15 [95% CI, 0.51–51.44]), glucose (OR = 0.99 [95% CI, 0.97–1.01]), systolic arterial pressure (OR = 1.10 [CI 1.03–1.17]), diastolic arterial pressure (OR = 0.94 [CI 0.87–1.02]), dyslipidemia (OR = 1.46 [95% CI, 0.25–8.55]), estimated glomerular filtration rate (OR = 0.98 [95% CI, 0.96–1.01]), body mass index (OR = 1.03 [95% CI, 0.90–1.10]), and valvular and/or coronary disease (OR = 5.27 [95% CI, 1.02–27.21]).
Conclusions
The present study suggests that PTI could be a new biomarker of oxidative stress in patients with LVH.
Introduction
Left ventricular hypertrophy (LVH) is a mechanism by which the heart adapts to different types of stress [1]. LVH progresses over time, thus increasing the incidence of heart failure, malignant arrhythmias, myocardial ischemia, systolic dysfunction, sudden death, and cerebrovascular complications [2–5]. Certain pharmacological treatments produce regression of LVH and decrease the incidence of cardiovascular adverse events and mortality in affected patients [6–11]. Therefore, early diagnosis and initiation of appropriate treatment are essential.
Electrocardiography (ECG) and echocardiography are the most widely used procedures for the diagnosis of LVH, although ECG shows low sensitivity and echocardiography takes longer, is more expensive, and is not always available for technical reasons [12]. 21 studies show that the accuracy of electrocardiographic indexes in the diagnosis of LVH is unsatisfactory [13]. The ECG shows an area under the ROC curve of 0.55 with 14.7% sensitivity and 96.7% specificity [14] and the echocardiography shows an area under the ROC curve of 0.62 with 90% sensitivity and 25% specificity [15]. In clinical practice, echocardiography is the imaging technique of choice [16]. However, the cost-effectiveness of routine echocardiography for diagnosis of LVH has been debated [17].
Biomarkers of oxidative stress play a relevant role in diagnosis, evaluation of disease status, and assessment of the health-enhancing effects of therapies. The protein thiolation index (PTI) is a new biomarker of oxidative stress that is defined as the molar ratio of S-thiolated proteins to free protein thiols in plasma [18]. The PTI can be determined easily and inexpensively and could be used for routine for therapeutic monitoring in clinical practice [18]. LVH has been associated with oxidative stress [19], although not with PTI. The hypertrophic remodeling of the myocardium incorporates increased cardiomyocyte growth, reactive interstitial fibrosis and enhanced nitro-oxidative stress. Oxidative stress occurs when excess reactive oxygen species (ROS) are generated that cannot be adequately countered by intrinsic antioxidant systems. ROS are derived from many sources including mitochondria, xanthine oxidase, uncoupled nitric oxide synthases and NADPH oxidases. Growing evidence implicates redox-sensitive pathways in the development of LVH [20]. LVH shows intensified formation of ROS that include decreased NO (nitric oxide) production due to the oxidation of the endothelial NO synthase, reduced NO bioavailability and oxidation of the sGC enzyme (soluble guanylate cyclase) rendering it a hem-free and NO-insensitive form [21]. The protective role of the guanylate cyclase (GC)–cyclic guanosine; monophosphate (cGMP)- protein kinase G (PKG) pathway in the cardiovascular system has been investigated [22]. The pharmacological activation of the sGC—cGMP pathway may exert reverse-remodeling properties in the myocardium and the intensified formation of ROS interferes with the above mentioned pathway [23].
This study explored the potential use of PTI as a biomarker of oxidative stress in patients with LVH.
Materials and methods
Study participants
We performed a observational study of 70 patients referred consecutively to our institution (to cardiac surgery section) in the period of time December 2015 to March 2016. When a patient is referred to cardiac surgery section, an echocardiography study is usually performed. The first patient, if the echocardiographic study showed LVH, this patient was included in the LVH group and if the echocardiographic study did not show LVH, the patient was included in the control group, and thus with the second patient referred to this section, and then with the third and so on, and then we have done the blood test to study PTI. In the period of time December 2015 to March 2016, 81 patients were referred to the cardiac surgery section, but we included 70 (11 patients show exclusion criteria. The clinical research ethics committee of the Hospital General Universitario Gregorio Marañon approved the study, and all participants gave their written informed consent to undergo the procedures. The inclusion criterion was age ≥18 years. The exclusion criteria were hemodialysis, rheumatoid arthritis, and alkaptonuria. A clinical history was taken, an echocardiography study was performed, and values for S-thiolated protein and total thiols were determined. The echocardiography was performed using the iE33 system (Philips, CA, USA) equipped with a S5-1 probe (1–5 MHz). The echocardiographic diagnosis of LVH (based on left ventricular mass indexed to body surface area, LVMbs) was consistent with the recommendations of the American Society of Echocardiography [24] and was used to form the two study groups (LVH and non-LVH, 35 patients each).
Measurement of PTI in clinical samples
Blood collections and plasma preparation
Blood samples (2.4 mL) were drawn from the antecubital vein and collected in Vacutainer tubes (BD, Plymouth, UK) containing citrate (300 𝜇L) before being centrifuged at 900g for 10 minutes at 4°C to obtain plasma, which was aliquoted and stored at –80°C for further analysis.
Quantification of PTI
Plasma levels of both S-thiolated protein and total thiols were measured individually as biomarkers of oxidative stress by spectrophotometry in the same sample. Total thiols were assessed using the microplate 5,5´-dithiobis (2-nitrobenzoic acid) (DTNB) assay [25], and absorbance was measured at 412 nm in a Synergy HT Multi-Mode Microplate Reader. Plasma S-thiolated proteins were determined by spectrophotometry using a new method with Ninhydrin reagent, as previously described [18]. PTI was calculated as the molar ratio of S-thiolated proteins to the concentration of free, DTNB-titratable SH group proteins (total thiols) [18].
Statistical methods
Categorical variables were expressed as frequency and percentage, and groups were compared using the Pearson chi-square test or Fisher´s test as required. Normality was assessed using the Kolmogorov–Smirnov test. Quantitative variables were described as mean ± standard deviation (for continuous, normally distributed variables), and the between-group comparison was made with two-sample t-test and the Mann-Whitney U-test as appropiate. A receiver operating characteristic curve (ROC) was constructed to determine the diagnostic reliability of PTI. A cut-off point was chosen for the diagnosis of LVH, and their sensitivity, specificity, predictive values, and likelihood ratios were calculated with their respective confidence intervals. A univariate and multivariable logistic regression model was performed to study the strength of the association between PTI and LVH. The independent variables were gender, age, smoking, glucose, systolic and diastolic arterial pressure, estimated glomerular filtration rate (eGFR), body mass index (BMI), coronary disease and valve disease. P values <0.05 were considered statistically significant. The analysis was performed using IBM SPSS Statistics for Windows, Version 21.0 (IBM Corp, Armonk, NY, USA) and Prism Graph Pad 6.0 (Graph Pad Software, California, USA).
Results
In total, 70 patients were included (35 diagnosed with LVH by echocardiography). The patients were considered to have systemic hypertension if they has a history of elevated blood pressure requiring long-term therapy, they were considered to have dyslipidemia if they had the diagnosis of dyslipidemia requiring long-term treatment and they were considered to have diabetes if they had the diagnosis of diabetes requiring long-term treatment. The clinical characteristics of patients are shown in Table 1. No significant differences were observed between the groups for demographic and cardiovascular risk factors (gender, age, weight, body mass index, smoking, diabetes mellitus, hypertension, and dyslipidemia), organ disease (renal failure, coronary disease, valvular disease, coronary and valvular disease, and systolic dysfunction), or antihypertensive treatment (angiotensin receptor blockers, angiotensin-converting enzyme inhibitors, β-blockers, calcium channel blockers, and diuretics). As reported in Table 1, there were significant differences in left ventricular mass index between the groups (LVH and no LVH, 141.8± 45.6 and 88.7±25.1 g/m2 respectively, P<0.001).
Table 1. Clinical charecteristics of the study patients.
| LVH (n = 35) | No LVH (n = 35) | P | OR (95% CI) | |
|---|---|---|---|---|
| Age (years) | 69.7 (10.2) | 63.5 (14.7) | 0.06 | 1.04 (1–1.09) |
| Gender, M (%) | 23 (65.7) | 21 (60) | 0.509 | 0.72 (0.27–1.92) |
| Weight (kg) | 76.1 (13.8) | 75.4 (14.9) | 0.623 | 1.01 (0.98–1.04) |
| Body mass index (m2) | 1.8 (0.1) | 1.8 (0.2) | 0.824 | 0.43 (0.04–5.03) |
| LVMI (g/m2) | 141.8 (45.6) | 88.7 (25.1) | <0.001 | 1.05 (1.02–1.07) |
| Proteins (g/dL) | 6.9 (0.7) | 6.9 (0.6) | 0.841 | 0.92 (0.43–1.99) |
| Glucose (mg/dL) | 115.3 (38) | 109.8 (36.9) | 0.667 | 1.00 (0.99–1.02) |
| Hemoglobin (g/dL) | 12.9 (2.1) | 13.4 (2) | 0.333 | 0.89 (0.70–1.13) |
| Hematocrit (%) | 38.6 (5.8) | 39.8 (5.6) | 0.375 | 0.96 (0.88–1.05) |
| Platelets x103 /μL | 211 (67) | 196 (59) | 0.304 | 1 (1–1.01) |
| ALT (U/L) | 22.2 (19.9) | 19.1 (10.6) | 0.432 | 1.02 (0.99–1.04) |
| GGT (U/L) | 28.5 (20.1) | 29.7 (20.5) | 0.805 | 1.00 (0.99–1.01) |
| Total bilirubin (mg/dL) | 0.69 (0.5) | 0.73 (0.5) | 0.771 | 0.88 (0.36–2.13) |
| CK (U/L) | 67.2 (56.4) | 62.4 (38.4) | 0.849 | 1.00 (0.99–1.01) |
| Smokers (%) | 4 (11.4) | 6 (17.1) | 0.734 | 1.55 (0.4–6.07) |
| Diabetes mellitus (%) | 11 (31.4) | 7 (20) | 0.243 | 0.52 (0.18–1.57) |
| Hypertension (%) | 28 (80) | 23 (65.7) | 0.116 | 0.41 (0.13–1.27) |
| Dyslipidemia (%) | 22 (62.8) | 17 (48.6) | 0.176 | 0.52 (0.20–1.35) |
| Renal failure (%) | 9 (25.7) | 10 (28.5) | 0.611 | 1.11 (0.39–3.2) |
| Coronary disease (%) | 1 (2.8) | 3 (8.5) | 0.310 | 4.20 (0.40–44.4) |
| Vavular disease (%) | 22 (62.8) | 15 (42.8) | 0.155 | 0.17 (0.02–1.65) |
| Coronary and valvular (%) | 12 (34.2) | 17 (48.5) | 0.264 | 1.73 (0.66–4.55) |
| Systolic Disfunction (%) | 13 (37.1) | 14 (40) | 0.881 | 1.08 (0.41–2.83) |
| Antihypertensive (%) | ||||
| ARB | 7 (20) | 3 (8.5) | 0.188 | 0.36 (0.09–1.54) |
| ACEi | 14 (40) | 13 (37.1) | 0.731 | 0.84 (0.32–2.22) |
| β-Blockers | 12 (34.2) | 11 (31.4) | 0.733 | 0.84 (0.31–2.29) |
| Calcium channel blockers | 11 (31.4) | 6 (17.1) | 0.143 | 0.43 (0.14–1.35) |
| Diuretics | 15 (42.8) | 10 (28.5) | 0.179 | 0.51 (0.19–1.38) |
LVH, left ventricular hypertrophy; LVMI, left ventricular mass index. ALT, alanine transaminase. GGT, gamma-glutamyl transpeptidase. CK, creatine kinase. ARB, angiotensin receptor blockers; ACEi, angiotensin-converting enzyme inhibitors.
The oxido-reductive status of the subjects under study is shown in Fig 1. The new method for detecting plasma S-thiolated proteins showed an increase in LVH with respect to the control group (0.102±0.035 vs. 0.07±0.035 μmol/mg protein, P = 0.01). There were no differences in total thiols between the LVH group and the control group (7.414±2.250 and 7.819±2.053 μmol/mg protein, respectively). Finally, PTI was increased in patients with LVH with respect to the control group (0.014±0.005 vs. 0.010±0.004, P = 0.001).
Fig 1. Protein thiolation index in patients with left ventricular hypertrophy.
Association plasma total thiols (A), S-thiolated proteins (B), and Protein thiolation index (PTI) (C) to the presence of left ventricular hypertrophy; data are expressed as the mean ± SD; statistically significant differences between control group (C) and left ventricular hypertrophy group (LVH) are shown (***P < 0.001).
The coefficient of variation was 40.9% and the minimun detection limit was 0.001771.
The area under the ROC curve (0.75, 95% confidence interval [CI] 0.63–0.86; P<0.001) shows the usefulness of the plasma PTI concentration in the diagnosis of LVH (Fig 2). At a cut-off value of 0.012, the 70.6% sensitivity and 68.6% specificity suggested that PTI could be used to screen for LVH. As this is an observational study, we show a positive predictive value of 68.6% and a negative predictive value of 70.6% for this cut-off (Table 2). We used the sensitivity and specificity of the cut-off to calculate the positive likelihood ratio (2.25) and negative likelihood ratio (0.43) (Table 2).
Fig 2. Receiver operating characteristic curve.
Receiver operator curve (ROC) analysis for protein thiolation index (PTI) to diagnose left ventricular hypertrophy.
Table 2. Indexes of diagnostic validity of protein thiolation index for left ventricular hypertrophy.
| PTI Cut-off |
Sensitivity % (95% CI) |
Specificity % (95% CI) |
PPV % (95% CI) |
NPV % (95% CI) |
LR+ (95% CI) |
LR- (95% CI) |
|---|---|---|---|---|---|---|
| 0.012 | 70.6 (52.5–84.9) |
68.6 (50.7–83.1) |
68.6 (50.7–83.1) |
70.6 (52.5–84.9) |
2.25 (1.32–3.84) |
0.43 (0.24–0.76) |
PTI, protein thiolation index; PPV, positive predictive value; NPV, negative predictive value; LR+, positive likelihood ratio; LR-, negative likelihood ratio.
In order to study the association between PTI and LVH, we performed a multivariable logistic regression analysis adjusted for gender, age, smoking, diabetes mellitus, hypertension, dyslipidemia, renal failure, obesity, coronary disease, and valvular disease. As shown in Table 3, a statistically significant positive association (P = 0.02) was observed between PTI and LVH, independently of the variables described in the model.
Table 3. Multivariable logistic regression model: association protein thiolation index and left ventricular hypertrophy.
| OR (95% CI) | P | |
|---|---|---|
| PTI | 1.243 (1.031–1.497) | 0.022 |
| Gender | 3.394 (0.609–18.917) | 0.163 |
| Age | 1.032 (0.962–1.108) | 0.379 |
| Smokers | 5.156 (0.517–51.443) | 0.162 |
| Glucose | 0.994 (0.971–1.017) | 0.614 |
| Systolic arterial pressure | 1.102 (1.030–1.179) | 0.005 |
| Diastolic arterial pressure | 0.944 (0.872–1.022) | 0.157 |
| Dyslipidemia | 1.467 (0.252–8.557) | 0.670 |
| Estimated glomerular filtration rate | 0.988 (0.961–1.016) | 0.410 |
| Body mass index | 1.038 (0.909–1.186) | 0.580 |
| Valvular and/or coronary disease | 5.276 (1.023–27.211) | 0.047 |
PTI (x1000), protein thiolation index
Discussion
PTI and LVH in humans
The main findings of our study were that patients with LVH had a higher PTI value than patients without LVH and that PTI level was independently associated with risk factors (gender, age, smoking, diabetes mellitus, hypertension, dyslipidemia, renal failure, obesity, coronary disease, and valvular disease). Therefore, this is the first study to propose PTI as a new biomarker of oxidative stress in patients with LVH.
Previous studies have revealed that LVH is one of the most important risk factors for cardiovascular disease (LVH is associated with a risk of cardiovascular events 2 to 4 times greater than in the healthy population) [8,26–28]. Therefore, diagnosis of LVH is important if we are to minimize the impact of cardiovascular disease. Methods for diagnosing LVH include ECG, echocardiography, and cardiac magnetic resonance [29]. ECG is an accessible and inexpensive method for the diagnosis of LVH, however the sensitivity of ECG ranges from 7% to 35% for mild LVH to 30% to 60% for moderate to severe LVH [30]. Although not immune from technical limitations, echocardiography is more sensitive than ECG in diagnosing LVH and has been regarded as a diagnostic gold standard [24]. Cardiac magnetic resonance is considered more accurate for estimated left ventricular mass compared to echocardiography, however it is less commonly used because it has higher cost and is less feasible and available [31]. Thus, the low sensitivity, lengthy diagnostic, poor cost-effectiveness ratio, and technical complexity highlight the need for new methods to diagnose LVH. As an alternative, biomarkers could play a relevant role in diagnosis of LVH. Biomarkers are an indicator of pathogenic processes. They indicate the presence/absence of disease and can be used to monitor disease development and progression and response to treatment [32]. Several studies have evaluated natriuretic peptides for the diagnosis of LVH, but the results are contradictory [33–37]. This might be due to the heterogeneity of the populations included, the type of natriuretic peptide analized, and the method used to confirm LVH. Analysis of the usefulness of plasma NT-proBNP (N-terminal pro-brain natriuretic peptide) concentrations in the diagnosis of LVH shows an area under the ROC curve of 0.75 with 76.6% sensitivity and 65.7% specificity [33]. However, only patients who presented hypertension without systolic dysfunction were included. A direct correlation was found between cardiotrophin-1 and left ventricular mass index, with an area under the ROC curve of 0.78, with 70% sensitivity and 75% specificity for predinting LVH [38]. Serum miR-27b which was significantly elevated in hypertensive patients with LVH from hypertensive patients without LVH, could be used to screen for LVH (AUC of 0.81 with 79.1% sensitivity and 70.3% specificity) [29]. Oxidative stress has an important pathophysiological role in patients with LVH [19]. Clinical studies have determinated correlations between biomarkers of oxidative stress and LVH: Galectin-3 has increased in patients with LVH related to hypertension [39] and serum oxidized low-density lipoproptein shows correlation with LVH related to chronic kidney disease [40]. However, these biomarkers are not commonly used in the LVH diagnosis, thus the role of oxidative stress in patients with LVH is underestimated in clinical practice. Consequently, biomarkers with inexpensive reagents that can be implemented easily and quickly and are easily measurable (plasma biomarkers) are needed to facilitate routine measurements of oxidative stress in patients with LVH. Unfortunately, it is difficult to find biomarkers with such characteristics [41–42]. PTI is a new biomarker of oxidative stress [18,43]. However, no association has been established with LVH. In the present study, we used a new spectrophotometry method, which has been validated by other authors, to analyze PTI [18]. The technique is easy to perform and suitable for clinical analyses with a high daily throughput, thus enabling rapid assessment.
Oxidative stress is a complex problem that is the consequence of an imbalance between oxidative damage and antioxidant defense, where many biomarkers play a role [44]. In addition, the complex and multifactorial nature of oxidative stress makes it difficult to assign a prevalent role to a particular biomarker in a disease and does not provide information on overall oxidative status (oxidant and antioxidant) [45]. However, given that PTI is defined as the molar ratio of S-thiolated proteins (oxidant agents) to free protein thiols in plasma (antioxidant molecules) [18], it includes biomarkers of oxidative damage and antioxidant defense.
Strengths and limitations
Our study is subject to a series of limitations. First, we examined the association between determination of plasma PTI and LVH in order to monitor the development of LVH. We intend to use this approach to check the efficiency of treatment in patients with heart disease (coronary and/or valvular). Therefore, it would be interesting to reproduce the results obtained in this study in patients with hypertension only (since this is the most frequent cause of LVH) in order to be able to use PTI for screening of LVH in the general population. Second, we evaluated LVH using echocardiography. The interobserver variability of this technique could lead to bias [46] thus, echocardiography should be performed by single cardiologist, however echocardiography was performed by a small group of experienced cardiologists. Finally, the premise of our investigation is that screening with PTI could be less expensive than standard echocardiography; however, the high quality of echocardiography may reduce the cost gap between both approaches [47].
Conclusion
Our findings suggest that PTI could be a new biomarker of oxidative stress in patients with LVH. It remains necessary to validate the clinical utility of PTI using a large, blinded set of samples and to establish comparability and standards for quality control in order to monitor the development of LVH and to check the efficiency of treatment in the general population.
Data Availability
All relevant data are within the paper.
Funding Statement
This work was supported by a grant from the Spanish Health Ministry (number FIS 16/02069) and Fondos Feder (to BQV).
References
- 1.Lazzeroni D, Rimoldi O, Camici PG. From left ventricular hypertrophy to dysfunction and failure. Circ J 2016; 80:555–564. 10.1253/circj.CJ-16-0062 [DOI] [PubMed] [Google Scholar]
- 2.Levy D, Garrison RJ, Savage DD, Kannel WB, Castelli WP. Prognostic implications of echocardiographycally determined left ventricular mass in the Framingham Heart Study. N Engl J Med 1990; 322:1561–1566. 10.1056/NEJM199005313222203 [DOI] [PubMed] [Google Scholar]
- 3.Koren MJ, Devereux RB, Casale PN, Savage DD, Laragh JH. Relation of left ventricular mass and geometry to morbidity and mortality in uncomplicated essential hypertension. Ann Intern Med 1991; 114:345–352. [DOI] [PubMed] [Google Scholar]
- 4.Verdecchia P, Porcellati C, Reboldi G, Gattobigio R, Borgioni C, Pearson TA, et al. Left ventricular hypertrophy as an independent predictor of acute cerebrovascular events in essential hypertension. Circulation 2001; 104:2039–2044. [DOI] [PubMed] [Google Scholar]
- 5.Bang CN, Soliman EZ, Simpson LM, Davis BR, Devereux RB, Okin PM. Electrocardiographic Left Ventricular Hypertrophy Predicts Cardiovascular Morbidity and Mortality in Hypertensive Patients: The ALLHAT Study. Am J Hypertens 2017; 30:914–922. 10.1093/ajh/hpx067 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 6.Mathew J, Sleight P, Lonn E, Johnstone D, Pogue J, Yi Q, et al. Reduction of cardiovascular risk by regression of electrocardiographic markers of left ventricular hypertrophy by the angiotensin-converting enzyme inhibitor Ramipril. Circulation 2001; 104:1615–1621. [DOI] [PubMed] [Google Scholar]
- 7.Bang CN, Devereux RB, Okin PM. Regression of electrocardiographic left ventricular hypertrophy or strain is associated with lower incidence of cardiovascular morbidity and mortality in hypertensive patients independent of blood pressure reduction–A LIFE review. J Electrocardiol 2014; 47:630–635. 10.1016/j.jelectrocard.2014.07.003 [DOI] [PubMed] [Google Scholar]
- 8.Okin PM, Devereux RB, Jern S, Kjeldsen SE, Julius S, Nieminen MS, et al. Regression of electrocardiographic left ventricular hypertrophy during antihypertensive treatment and the prediction of major cardiovascular events. JAMA 2004; 292:2343–2349. 10.1001/jama.292.19.2343 [DOI] [PubMed] [Google Scholar]
- 9.Devereux RB, Wachtell K, Gerdts E, Boman K, Nieminen MS, Papademetriou V, et al. Prognostic significance of left ventricular mass during treatment of hypertension. JAMA 2004; 292:2350–2356. 10.1001/jama.292.19.2350 [DOI] [PubMed] [Google Scholar]
- 10.Pierdomenico SD, Cuccurullo F. Risk reduction after regression of echocardiographic left ventricular hypertrophy in hypertension: a meta-analysis. Am J Hypertens 2010; 23:876–881. 10.1038/ajh.2010.80 [DOI] [PubMed] [Google Scholar]
- 11.Verdecchia P, Angeli F, Borgioni C, Gattobigio R, de Simeone G, Devereux RB, et al. Changes in cardiovascular risk by reduction of left ventricular mass in hypertension: a meta-analysis. Am J Hypertens 2003; 16(11 Pt 1):895–899. [DOI] [PubMed] [Google Scholar]
- 12.Cabezas M, Comellas A, Gómez JR, López Grillo L, Casal H, Carrillo N, et al. R. Comparación de la sensibilidad y especificidad de los criterios electrocardiográficos para la hipertrofia ventricular izquierda según métodos de Romhilt-Estes, Sokolow-Lyon, Cornell y Rodríguez Padial. Rev Esp Cardiol 1997; 50:31–35. [DOI] [PubMed] [Google Scholar]
- 13.Pewsner D, Jüni P, Egger M, Battaglia M, Sundström J, Bachmann LM. Accuracy of electrocardiography in diagnosis of left ventricular hypertrophy in arterial hypertension: systematic review. BMJ 2007; 335:711 10.1136/bmj.39276.636354.AE [DOI] [PMC free article] [PubMed] [Google Scholar]
- 14.Rider OJ, Ntusi N, Bull SC, Nethononda R, Ferreira V, Holloway CJ, et al. Improvements in ECG accuracy for diagnosis of left ventricular hypertrophy in obesity. Heart 2016; 102:1566–1572. 10.1136/heartjnl-2015-309201 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 15.Supe-Markovina K, Nielsen JC, Musani M, Panesar LE, Woroniecki RP. Assessment of Left Ventricular Mass and Hypertrophy by Cardiovascular Magnetic Resonance Imaging in Pediatric Hypertension. J Clin Hypertens (Greenwich) 2016;18:976–981. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 16.Hlatky MA, Greenland P, Arnett DK, Ballantyne CM, Criqui MH, Elkind MS, et al. Criteria for evaluation of novel markers of cardiovascular risk: a scientific statement from the American Heart Association. Circulation 2009; 119:2408–2416. 10.1161/CIRCULATIONAHA.109.192278 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 17.Cuspidi C, Meani CS, Valerio C, Fusi V, Sala C, Zanchetti A. Left ventricular hypertrophy and cardiovascular risk stratification: impact and cost-effectiveness of echocardiography in recently diagnosed essential hypertension. J Hypertens 2006; 24:1671–1676. 10.1097/01.hjh.0000239305.01496.ca [DOI] [PubMed] [Google Scholar]
- 18.Giustarini D, Dalle-Donne I, Lorenzini S, Selvi E, Colombo G, Milzani A, et al. Protein thiolation index (PTI) as a biomarker of oxidative stress. Free Radic Biol Med 2012; 53:907–915. 10.1016/j.freeradbiomed.2012.06.022 [DOI] [PubMed] [Google Scholar]
- 19.Takimoto E, Kass DA. Role of oxidative stress in cardiac hypertrophy and remodeling. Hypertension 2007; 49:241–248. 10.1161/01.HYP.0000254415.31362.a7 [DOI] [PubMed] [Google Scholar]
- 20.Seddon M, Looi YH, Shah AM. Oxidative stress and redox signalling in cardiac hypertrophy and heart failure. Heart 2007; 93:903–907. 10.1136/hrt.2005.068270 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 21.Stasch JP, Pacher P, Evgenov OV. Soluble guanylate cyclase as an emerging therapeutic target in cardiopulmonary disease. Circulation 2011; 123:2263–2273 10.1161/CIRCULATIONAHA.110.981738 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 22.Kraehling JR, Sessa WC. Contemporary approaches to modulating the nitric oxide-cGMP pathway in cardiovascular disease. Circ Res 2017; 120:1174–1182. 10.1161/CIRCRESAHA.117.303776 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 23.Ruppert M, Korkmaz-Icöz S, Li S, Brlecic P, Németh BT, Oláh A, et al. Comparison of the reverse-remodeling effect of pharmacological soluble guanylate cyclase activation with pressure unloading in pathological myocardial left ventricular hypertrophy. Front Physiol 2019; 9:1869 10.3389/fphys.2018.01869 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 24.Lang RM, Badano LP, Mor-Avi V, Afilalo J, Armstrong A, Ernande L, et al. Recommendations for cardiac chamber quantification by echocardiography in adults: an update from the American Society of Echocardiography and the European Association of Cardiovascular Imaging. J Am Soc Echocardiogr 2015; 28:1–39. 10.1016/j.echo.2014.10.003 [DOI] [PubMed] [Google Scholar]
- 25.Hawkins CL, Morgan PE, Davies MJ. Quantification of protein modification by oxidants. Free Radic Biol Med 2009; 46:965–988. 10.1016/j.freeradbiomed.2009.01.007 [DOI] [PubMed] [Google Scholar]
- 26.Wachtell K, Okin PM, Olsen MH, Dahlöf B, Devereux RB, Ibsen H, et al. Regression of electrocardiographic left ventricular hypertrophy during antihypertensive therapy and reduction in sudden cardiac death: the LIFE Study. Circulation 2007; 116:700–705. 10.1161/CIRCULATIONAHA.106.666594 [DOI] [PubMed] [Google Scholar]
- 27.Kannel WB. Prevalence and natural history of electrocardiographic left ventricular hypertrophy. Am J Med 1983; 75: 4–11. [DOI] [PubMed] [Google Scholar]
- 28.Vakili BA, Okin PM, Devereux RB. Prognostic implications of left ventricular hypertrophy. Am Heart J 2001; 141:334–341. 10.1067/mhj.2001.113218 [DOI] [PubMed] [Google Scholar]
- 29.Wang Y, Chen S, Gao Y, Zhang S. Serum MicroRNA-27b as a Screening Biomarker for Left Ventricular Hypertrophy. Tex Heart Inst J 2017; 44:385–389. 10.14503/THIJ-16-5955 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 30.Nadour W, Biederman RW. Is left ventricular hypertrophy regression important? Does the tool used to detect it matter? The Journal of Clinical Hypertension. 2009; 11:441–447. 10.1111/j.1751-7176.2009.00137.x [DOI] [PMC free article] [PubMed] [Google Scholar]
- 31.Hendel RC, Patel MR, Kramer CM, Poon M, Hendel RC, Carr JC, et al. ACCF/ACR/SCCT/SCMR/ASNC/NASCI/SCAI/SIR 2006 appropriateness criteria for cardiac computed tomography and cardiac magnetic resonance imaging: a report of the American College of Cardiology Foundation Quality Strategic Directions Committee Appropriateness Criteria Working Group, American College of Radiology, Society of Cardiovascular Computed Tomography, Society for Cardiovascular Magnetic Resonance, American Society of Nuclear Cardiology, North American Society for Cardiac Imaging, Society for Cardiovascular Angiography and Interventions, and Society of Interventional Radiology. J Am Coll Cardiol. 2006; 48:1475–97. 10.1016/j.jacc.2006.07.003 [DOI] [PubMed] [Google Scholar]
- 32.Boenzi S, Diodato D. Biomarkers for mitochondrial energy metabolism diseases. Essays Biochem 2018; 62:443–454. 10.1042/EBC20170111 [DOI] [PubMed] [Google Scholar]
- 33.Andrade H, Morillas P, Castillo J, Roldán J, Mateo I, Agudo P, et al. Validez diagnóstica del NT-proBNP frente al electrocardiograma en la detección de hipertrofia ventricular izquierda de origen hipertensivo. Rev Esp Cardiol 2011;64: 939–941. 10.1016/j.recesp.2011.02.019 [DOI] [PubMed] [Google Scholar]
- 34.de Lemos JA, McGuire DK, Khera A, Das SR, Murphy SA, Omland T, et al. Screening the population for left ventricular hypertrophy and left ventricular systolic dysfunction using natriuretic peptides: results from the Dallas Heart Study. Am Heart J 2009; 157:746–753. 10.1016/j.ahj.2008.12.017 [DOI] [PubMed] [Google Scholar]
- 35.Nakamura M, Tanaka F, Yonezawa S, Satou K, Nagano M, Hiramori K. The limited value of plasma B-type natriuretic peptide for screening for left ventricular hypertrophy among hypertensive patients. Am J Hypertens 2003; 16:1025–1029. [DOI] [PubMed] [Google Scholar]
- 36.Mueller T, Gegenhuber A, Dieplinger B, Poelz W, Haltmayer M. Capability of B-type natriuretic peptide (BNP) and amino-terminal proBNP as indicators of cardiac structural disease in asymptomatic patients with systemic arterial hypertension. Clin Chem 2005; 51:2245–2251. 10.1373/clinchem.2005.056648 [DOI] [PubMed] [Google Scholar]
- 37.Goetze JP, Mogelvang R, Maage L, Scharling H, Schnohr P, Sogaard P, et al. Plasma pro-B-type natriuretic peptide in the general population: screening for left ventricular hypertrophy and systolic dysfunction. Eur Heart J 2006; 27:3004–3010. 10.1093/eurheartj/ehl406 [DOI] [PubMed] [Google Scholar]
- 38.López B, González A, Lasarte JJ, Sarobe P, Borrás F, Díaz A, et al. Is plasma cardiotrophin-1 a marker of hypertensive heart disease? J Hypertens 2005; 23:625–632. [DOI] [PubMed] [Google Scholar]
- 39.Nar G, Aksan G, Gorgulu O, Inci S, Soylu K, Ozdemir M, et al. Galectin-3 as a novel biomarker for the diagnosis of essential hypertension with left ventricular hypertrophy. J Exp Clin Med 2016; 33:123–128. [Google Scholar]
- 40.Drożdż D, Kwinta P, Sztefko K, Kordon Z, Drożdż T, Łątka M, et al. Oxidative Stress Biomarkers and Left Ventricular Hypertrophy in Children with Chronic Kidney Disease. Oxid Med Cell Longev 2016; 2016:7520231 10.1155/2016/7520231 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 41.Xanthakis V, Larson MG, Wollert KC, Aragam J, Cheng S, Ho J, et al. Association of novel biomarkers of cardiovascular stress with left ventricular hypertrophy and dysfunction: implications for screening. J Am Heart Assoc 2013; 2:e000399 10.1161/JAHA.113.000399 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 42.Coutinho T, Al-Omari M, Mosley TH Jr, I.J. Kullo IJ. Biomarkers of left ventricular hypertrophy and remodeling in blacks. Hypertension 2011; 58:920–925. 10.1161/HYPERTENSIONAHA.111.178095 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 43.Colombo G, Reggiani F, Podestà MA, Garavaglia ML, Portinaro NM, Milzani A, et al. Plasma protein thiolation index (PTI) as a biomarker of thiol-specific oxidative stress in haemodialyzed patients. Free Radic Biol Med 2015; 89:443–451. 10.1016/j.freeradbiomed.2015.08.022 [DOI] [PubMed] [Google Scholar]
- 44.González J, Valls N, Brito R, Rodrigo R. Essential hypertension and oxidative stress: New insights. World J Cardiol 2014; 6:353–366. 10.4330/wjc.v6.i6.353 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 45.Veglia F, Cavalca V, Tremoli E. OXY-SCORE: a global index to improve evaluation of oxidative stress by combining pro- and antioxidant markers. Methods Mol Biol 2010; 594:197–213. 10.1007/978-1-60761-411-1_14 [DOI] [PubMed] [Google Scholar]
- 46.Morbach C, Gelbrich G, Breunig M, Tiffe T, Wagner M, Heuschmann PU, et al. Impact of acquisition and interpretation on total inter-observer variability in echocardiography: results from the quality assurance program of the STAAB cohort study. Int J Cardiovasc Imaging 2018; 24:1057–1065. [DOI] [PubMed] [Google Scholar]
- 47.Galasko GI, Barnes SC, Collinson P, Lahiri A, Senior R. What is the most cost-effective strategy to screen for left ventricular systolic dysfunction: natriuretic peptides, the electrocardiogram, hand-held echocardiography, traditional echocardiography, or their combination? Eur Heart J 2006; 27:193–200. 10.1093/eurheartj/ehi559 [DOI] [PubMed] [Google Scholar]
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