Abstract
Background
Cardiac biomarkers have been shown to be related to cardiac abnormalities; nonetheless, few studies have confirmed the association between cardiac and rheumatoid biomarkers in rheumatoid arthritis (RA) patients. This study assessed the correlation of rheumatoid and cardiac biomarker levels with cardiac anatomy and function and explored the interaction between cardiac and rheumatoid biomarkers in RA patients without clinically overt cardiovascular diseases.
Methods
A cross-sectional study was conducted among RA patients aged 18–65 years without other connective tissue diseases, overlap syndrome, heart disease, or renal failure were included. Main cardiac and rheumatoid biomarkers, including high-sensitivity troponin T (hsTropT), N-terminal pro-B-type natriuretic peptide (NT-proBNP), rheumatoid factor, and anti-cyclic citrullinated peptide antibody (ACPA), were collected. Echocardiography was performed to examine cardiac anatomy and function.
Results
The mean left ventricular mass index (LVMI) was 80.8 g/sqm, and the relative wall thickness was 0.4. The mean left ventricular ejection fraction was 70.3%. The hsTropT levels showed a weak positive correlation with LVMI and E/e' ratio and a very weak correlation with E/A ratio. Interaction effect between hsTropT and ACPA on LVMI was found in univariate analysis, not in multivariate analysis. Higher systolic blood pressure (SBP) and the use of non-steroidal anti-inflammatory drug (NSAID) increased the LVMI. Only age was related to the E/e' increase.
Conclusion
The effect of hsTropT on LVMI was probably modified by ACPA in RA patients without clinically overt cardiovascular diseases. Age, SBP, and NSAID use among RA patients should be taken into account due to their relations to cardiac abnormalities.
Keywords: Rheumatoid biomarker, Cardiac biomarker, Cardiac anatomy, Cardiac function
1. Introduction
Rheumatoid arthritis (RA) is the most common type of chronic inflammatory arthritis. Chronic inflammation in RA leads to permanent joint damage, disability, and premature death [1], and the mortality rate has been reported to be higher in RA patients than in the general population [2], [3]. Cardiovascular disease (CVD) is a major cause of death in RA patients [2], [4], and cardiovascular mortality is increased by 20–50% in RA patients, compared with that in patients without RA [5], [6]. Moreover, the incidence of myocardial infarction, arrhythmia, pericardial disease, and left ventricular (LV) dysfunction is higher in RA patients than in the general population [4], [7], [8]. Additionally, RA patients have significantly worse LV systolic and diastolic function, especially patients with active disease [9], [10]. Some biomarkers such as high-sensitivity troponin T (hsTropT) and B-type natriuretic peptide (BNP) are evidently related to abnormal heart structure and function, which are mediated by chronic myocardial injury [11], [12].
Both hsTropT and BNP are found in patients with hypertrophic cardiomyopathy [13], which can be explained by chronic cardiac injury that causes an elevation in cardiac biomarker levels in malignant LV hypertrophy and subclinical cardiac injury in the general population [14]. In hypertensive patients, hsTropT and BNP levels are related to an abnormal LV structure [15], [16]. Furthermore, cardiac troponin and BNP levels have been reported to increase in patients with myotonic dystrophy or chronic kidney disease and in the subclinical general population with abnormal LV systolic and diastolic function [17], [18], [19]. Similarly, cardiac troponin has been shown to be related to indolent myocardial injury in RA patients [20].
In RA patients, rheumatoid factor (RF) and anti-cyclic citrullinated protein/peptide antibody (ACPA) are common rheumatoid-related biomarkers that function as antigenic stimuli [21]. ACPA and RF are autoantibodies that arise as a result of the loss of tolerance to citrulline-containing proteins, which incurs a risk of sustained inflammatory cascade by RF-producing B cells, leading to tissue damage, including extra-articular manifestations [22]. The erythrocyte sedimentation rate (ESR) and C-reactive protein (CRP) level are also associated with inflammation and active diseases [23]. RF is an independent risk factor for LV dysfunction in heart failure among RA patients with cardiovascular disease after adjustment for other risk factors [24], [25], as well as in RA patients with asymptomatic ventricular dysfunction [26].
Previous studies reported abnormalities in LV and right ventricular structure and function in RA patients without clinically overt cardiovascular diseases, which may be related to positive RF [27], [28]. Nonetheless, the explanation for these findings remains unclear. We hypothesized that rheumatoid and cardiac biomarkers are associated with abnormal cardiac anatomy and function. Therefore, this study aimed to assess the correlation of rheumatoid and cardiac biomarker levels with cardiac anatomy and function in RA patients without clinically overt cardiovascular diseases and explore the interaction effect between rheumatoid and cardiac biomarkers and other associated factors on cardiac anatomy and function.
2. Methods
A cross-sectional study was conducted from May to November 2018 at a rheumatology clinic in Songklanagarind Hospital, a tertiary-care university hospital located in southern Thailand. The study proposal was submitted to and approved by the Human Ethical Research Committee of the Prince of Songkla University Faculty of Medicine (REC. 60-257-14-1), and informed consent was obtained from all participants included in the study.
A total of 299 eligible participants were RA patients aged at least 18 years who were diagnosed using the 1987 American College of Rheumatology (ACR) criteria [29] or the 2010 ACR/European League Against Rheumatism criteria [30]. The exclusion criteria were as follows: age > 65 years (owing to the increased incidence of cardiovascular events in those aged > 65 years) [31] and diagnosis of other connective tissue diseases, overlap syndrome, heart disease (previous or current clinical signs of heart disease diagnosed by a cardiologist, including CVD, cardiomyopathy, valvular heart disease, arrhythmia, and congestive heart failure), or renal failure (glomerular filtration rate < 30 mL/min or renal replacement therapy). Thirty patients were excluded as they were unwilling to participate in the study.
The sample size was calculated using the correlation formula, considering the correlation coefficient between cardiac biomarkers and cardiac anatomy. We used BNP as a cardiac biomarker and LV mass index (LVMI) as a determinant of cardiac anatomy, which showed a correlation coefficient of 0.3 [32]. Considering a 95% confidence interval and 90% power, at least 73 RA patients were required. In order to obtain sufficient samples, BNP was chosen for the sample size calculation because it showed a lower correlation with LVMI than hsTropT.
The main outcome measures were cardiac anatomy and function, which were measured using transthoracic echocardiography performed by two experienced cardiology board-certified physicians using GE Vivid E9 (GE Healthcare, Wauwatosa, WI, USA) with an M5S probe in accordance with a predefined protocol.
Main parameters of cardiac anatomy were relative wall thickness (RWT) and LVMI. RWT was calculated based on posterior wall thickness (PWT). LVMI was calculated by dividing the LV mass by the body surface area. The LV mass was calculated from end-diastolic estimates of PWT, septal wall thickness (SWT), LV internal diameter at end-diastole (LVIDD), and at end-systole (LVIDS) using Devereux’s formula. PWT, SWT, LVIDD, and LVIDS were measured in millimeters.
Main parameters of cardiac function were considered as systolic left ventricular function measured by left ventricular ejection fraction (LVEF) measured using Teicho’s method and modified Simpson’s biplane method [33] and diastolic left ventricular function measured by deceleration time (DT), ratio of early filling and atrial filling velocities on transmitral Doppler (E/A), and ratio of early filling velocity on transmitral Doppler and early relaxation velocity on tissue Doppler (E/e'). E/e' and E/A were calculated by dividing E by e' and A, respectively. DT was defined as the time interval from the peak of the early filling velocity wave to its projected baseline [34], [35]
The main exposures were cardiac (hsTropT and NT-proBNP) and rheumatoid (RF and ACPA) biomarkers. Serum hsTropT and proBNP (cobas e411; Roche Diagnostics, Indianapolis, IN, USA) levels were reported in ng/L and pg/mL, respectively. RF was measured using the turbidimetric method, with a cut-off point of > 12.5 IU/mL being defined as positive. ACPA was measured using the chemiluminescent microparticle immunoassay method, with a cut-off point of > 5 IU/mL being defined as positive.
Other independent variables were age, blood pressure, underlying disease, basic laboratory results, duration of RA, extra-articular manifestations, rheumatoid activity, treatment, and disease-modifying anti-rheumatic drugs (DMARDs). Rheumatoid activity was evaluated using the standard Disease Activity Score-28 (DAS28), which was calculated using ESR. Patients were categorized into the following 4 groups: DAS28 > 5.1, high disease activity; DAS28 > 3.2 ≤ 5.1, moderate disease activity; DAS28 ≥ 2.6 and ≤ 3.2, low disease activity; and DAS28 < 2.6, remission [36]. Additionally, routine clinical chemistry data were collected.
All RA patients who visited the rheumatology clinic in the study setting were checked against the eligibility criteria and invited to participate in the study. After the patients provided written consent, they were interviewed to gather demographic, clinical, and laboratory data on the same day as enrollment. Echocardiography was scheduled within 1 week after enrollment. All data were confidentially recorded and analyzed in accordance with the ethics committee-approved protocol.
All analyses were performed using R software version 4.1.2 (R Foundation for Statistical Computing, Vienna, Austria) [37]. Baseline characteristics were presented as frequency and percentage, mean with standard deviation (SD), or median with interquartile range, as appropriate. The correlation of cardiac markers (hsTropT and NT-proBNP) with cardiac anatomy and function was analyzed using Spearman’s rank correlation (rho coefficients). Cardiac anatomy (LVMI and RWT) and function (LVEF, E/A, DT, E/e') in four groups of either positive or negative biomarkers (RF negative / ACPA negative, RF negative / ACPA positive, RF positive / ACPA negative, RF positive / ACPA positive) were analyzed using Analysis of Variance (ANOVA) or the Kruskal Wallis test for continuous variables, depending on the distribution of data. Because BNP showed a negligible correlation [38] with cardiac anatomy and function, only hsTropT was tested for the interaction with rheumatoid markers to determine LVMI and E/e' using univariate and multivariate linear regression models. The main exposures and other variables measured in this study was included in the first model and backward stepwise method were used to identify the significant variables. Significant variables adjusted for main cardiac and rheumatoid biomarkers as well as the interaction of hsTropT and rheumatoid markers were kept in the final model. Significance level was set at a p-value < 0.05.
3. Results
Of 299 patients with eligible criteria, 190 patients were excluded due to age > 65 years (n = 48), diagnosis of other connective tissue diseases, cardiovascular disease (n = 80), renal failure (n = 32), and unwilling to participate in the study (n = 30). The clinical characteristics of 109 RA patients are summarized in Table 1. The age of the patients ranged from 31 to 65 years, and 96.3% of the RA patients were women. Obesity, hypertension, hyperlipidemia, and diabetes were identified in 16%, 18.3%, 41.3%, and 6.4% of patients, respectively. The proportion of patients with moderate to severe disease activity was higher than that of patients with low disease activity and remission, as classified by DAS28 (64.2% vs. 35.8%). The mean duration of RA was 106.8 months. Rheumatoid nodules were present in 16.5% of patients. Overall, 33% of patients received non-steroidal anti-inflammatory drugs for symptom control, whereas 54% used steroids. Methotrexate was the mainstay DMARD (93.6%). None of the patients were treated with gold or biological agents.
Table 1.
Characteristics and clinical data of the included RA patients without clinically overt cardiovascular diseases.
| Patients (N = 109) | |
|---|---|
| Age (years), median (IQR) | 53 (47, 58) |
| Female (n, %) | 105 (96.3) |
| BMI, median (IQR) | 23.8 (21.7, 27.5) |
| SBP, mean (SD) | 129.3 (15.4) |
| DBP, mean (SD) | 74.9 (9.6) |
| Past medical history | |
| Smoker | |
| Former | 7 (6.4) |
| Current | 2 (1.8) |
| Never | 100 (91.7) |
| Hypertension | 20 (18.3) |
| Diabetes mellitus | 7 (6.4) |
| Dyslipidemia | 45 (41.3) |
| Family history of | |
| Myocardial infarction (n, %) | 10 (9.2) |
| Old cerebrovascular accident (n, %) | 14 (12.8) |
| RA and treatment | |
| Duration of RA (months), mean (SD) | 106.8 (77.1) |
| Presence of rheumatoid nodules | 18 (16.5) |
| Disease Activity Score-28 | |
| Remission | 23 (21.1) |
| Low disease activity | 16 (14.7) |
| Moderate disease activity | 56 (51.4) |
| Severe disease activity | 14 (12.8) |
| ESR (mm/h), mean (SD) | 46.5 (30) |
| CRP (mg/L), mean (SD) | 4.3 (5.4) |
| NSAID use (n, %) | 36 (33.0) |
| Prednisolone use (n, %) | 59 (54.1) |
| DMARDs | |
| DMARD use, mean (SD) | 1.8 (0.9) |
| Methotrexate use (n, %) | 102 (93.6) |
| Sulfasalazine use (n, %) | 36 (33) |
| Hydroxychloroquine use (n, %) | 29 (26.6) |
| Azathioprine use (n, %) | 1 (0.9) |
| Chloroquine use (n, %) | 2 (1.8) |
| Leflunomide use (n, %) | 30 (27.5) |
RA, rheumatoid arthritis; BMI, body mass index; SBP, systolic blood pressure; DBP, diastolic blood pressure; ESR, erythrocyte sedimentation rate; CRP, C-reactive protein; NSAID, non-steroidal anti-inflammatory drug; DMARD, disease-modifying anti-rheumatic drug.
Table 2 presents the rheumatoid and cardiac biomarkers in RA patients without clinically overt cardiovascular diseases. Of these patients, 57.8% and 63.3% had positive RF and ACPA, respectively. The ESR and CRP levels were 46.5 mm/hour and 4.3 mg/L, respectively. The mean hsTropT and NT-proBNP levels were 5.6 ng/L and 74 pg/mL, respectively. Most patients had a lower cut-off point for both hsTropT and NT-proBNP levels (96% and 87.7%, respectively).
Table 2.
Identification of rheumatoid and cardiac biomarkers in RA patients without clinically overt cardiovascular diseases.
| Patients (N = 109) | |
|---|---|
| RF positive (n, %) | 63 (57.8) |
| ACPA positive (n, %) | 69 (63.3) |
| hsTropT (ng/L), mean (SD) | 5.6 (2.9) |
| <14 | 102 (96.2) |
| ≥14 | 4 (3.8) |
| NT-proBNP (pg/mL), mean (SD) | 74 (69.3) |
| <125 | 93 (87.7) |
| ≥125 | 13 (12.3) |
RA, rheumatoid arthritis; RF, rheumatoid factor; ACPA, anti-cyclic citrullinated peptide antibody; hsTropT, high-sensitivity troponin T; NT-proBNP, N-terminal pro-B-type natriuretic peptide
Table 3 shows the cardiac anatomy and function in RA patients without clinically overt cardiovascular diseases. LVMI ranged from 39.45 to 160.18 gm/sqm (mean ± SD: 80.8 ± 20.1), whereas LVEF ranged from 57% to 85% (mean ± SD: 70.3 ± 6.1). Table 4 shows the correlations of cardiac biomarkers with cardiac anatomy and function. hsTropT showed a weak positive correlation with LVMI and E/e’ and a very weak negative correlation with the E/A ratio. In contrast, NT-proBNP showed very weak correlations with cardiac anatomy and function measured.
Table 3.
Details regarding cardiac anatomy and function in RA patients without clinically overt cardiovascular diseases.
| Patients (N = 109) Mean (SD) | |
|---|---|
| Anatomy | |
| SWT (mm) | 8.9 (1.7) |
| PWT (mm) | 9.2 (3.5) |
| LVIDD (mm) | 43.7 (5.3) |
| RWT (mm) | 0.4 (0.1) |
| LVMI (gm/sqm) | 80.8 (20.1) |
| Function | |
| LVEF | 70.3 (6.1) |
| DT (ms) | 210.1 (48.8) |
| E/A | 1.2 (0.4) |
| E/e' | 9.3 (2.8) |
RA, rheumatoid arthritis; SWT, septal wall thickness; PWT, posterior wall thickness; LVIDD, left ventricular diastolic diameter at end-diastole; RWT, relative wall thickness; LVMI, left ventricular mass index; LVEF, left ventricular ejection fraction; DT, deceleration time; E/A, early filling and atrial filling velocities on transmitral doppler; E/e', early filling velocity on transmitral Doppler and early relaxation velocity on tissue Doppler
Table 4.
Correlations of cardiac biomarker and cardiac anatomy and function in RA patients without clinically overt cardiovascular diseases.
| Correlation coefficient (rho) |
||
|---|---|---|
| hsTropT | NT-proBNP | |
| Anatomy | ||
| RWT (mm) | 0.11 | 0.10 |
| LVMI (gm/sqm) | 0.25 | 0.11 |
| Function | ||
| LVEF(%) | 0.04 | 0.15 |
| DT (ms) | −0.08 | −0.17 |
| E/A | −0.19 | 0.10 |
| E/e' | 0.26 | −0.05 |
RA, rheumatoid arthritis; hsTropT, high-sensitivity troponin T; NT-proBNP, N-terminal pro-B-type natriuretic peptide; RWT, relative wall thickness; LVMI, left ventricular mass index; LVEF, left ventricular ejection fraction; DT, deceleration time; E/A, early filling and atrial filling velocities on transmitral Doppler; E/e', early filling velocity on transmitral doppler and early relaxation velocity on tissue Doppler.
There were no statically significant differences of cardiac anatomy and function among four groups of either positive or negative RF and ACPA biomarkers in patients without clinical overt cardiovascular disease (Table 5) Patients with positive both RF and ACPA were more likely to have higher LVMI than those in other groups. Slightly higher LVEF, but slightly lower E/e', in patients with negative both RF and ACPA was found comparing to those with positive at least one biomarker.
Table 5.
Association of rheumatoid biomarkers with cardiac anatomy and function in rheumatoid arthritis patients without clinically overt cardiovascular diseases.
| Cardiac anatomy and function | RF - / ACPA - | RF - / ACPA + | RF + / ACPA - | RF + / ACPA + | p-value |
|---|---|---|---|---|---|
| n = 11 | n = 35 | n = 29 | n = 34 | ||
| RWT, mean (SD) | 0.4 (0.1) | 0.4 (0.1) | 0.4 (0.1) | 0.4 (0.1) | 0.112 |
| LVMI, mean (SD) | 81.7 (32.3) | 80.6 (18.8) | 81 (20.7) | 83.4 (20.9) | 0.956 |
| LVEF, mean (SD) | 72.2 (4.1) | 70 (7.1) | 69.7 (5.8) | 70.3 (5.9) | 0.718 |
| DT, median (IQR) | 220 (189.5,272.5) | 214 (194.5,250.5) | 188 (169.0,222.0) | 201.5 (183.2,230.0) | 0.076 |
| E/A, median (IQR) | 1.3 (0.8,1.3) | 1.2 (0.8,1.5) | 1.2 (0.9,1.4) | 1.2 (0.8,1.4) | 0.944 |
| E/e', mean (SD) | 8.2 (1.8) | 9.8 (2.3) | 9.4 (2.9) | 9.1 (3.3) | 0.377 |
-, negative; + positive, RA, rheumatoid arthritis; RF, rheumatoid factor; ACPA, anti-cyclic citrullinated peptide antibody; RWT, relative wall thickness; LVMI, left ventricular mass index; LVEF, left ventricular ejection fraction; DT, deceleration time; E/A, early filling and atrial filling velocities on transmitral doppler; E/e', early filling velocity on transmitral Doppler and early relaxation velocity on tissue Doppler.
The interaction effect between hsTropT and rheumatoid biomarkers (RF and ACPA) on cardiac anatomy (LVMI) and function (E/e') is shown in Fig. 1, Fig. 2, respectively. Univariate (Fig. 2B) and multivariate analyses (Fig. 2D) revealed that the effect of hsTropT on LVMI was enhanced by the presence of ACPA. As illustrated by the graphs in Fig. 1, Fig. 2, the slope for the ACPA-positive group was steeper than that for the ACPA-negative group, and there was no interaction effect between hsTropT and rheumatoid biomarkers on E/e'.
Fig. 1.
Interaction between hsTropT and LVMI stratified by rheumatoid biomarkers in rheumatoid arthritis patients without clinically overt cardiovascular diseases (A, B). Adjusted multivariate analysis (C, D). hsTropT, high-sensitivity troponin T; RF, rheumatoid factor; LVMI, left ventricular mass index; ACPA, anti-cyclic citrullinated peptide antibody.
Fig. 2.
Associations between hsTropT and E/e' stratified by rheumatoid biomarkers (A, B) in rheumatoid arthritis patients without clinical overt cardiovascular diseases. Adjusted multivariate analysis (C, D). hsTropT, high-sensitivity troponin T; RF, rheumatoid factor; ACPA, anti-cyclic citrullinated peptide antibody; E/e', early filling velocity on transmitral Doppler and early relaxation velocity on tissue Doppler.
The final models show the relationships of LVMI and E/e' with significant variables adjusted with cardiac and rheumatoid biomarkers including the interaction between hsTropT and rheumatoid biomarkers, are presented in Table 6. LVMI was significantly increased when the SBP was higher (adjusted β coefficient = 0.292, p = 0.036) and the NSAID was used (adjusted β coefficient = 8.681, p = 0.045). Only age was shown to be significant; in particular, as age increased, E/e' increased (adjusted β coefficient = 0.101, p = 0.009). The effects of cardiac and rheumatoid biomarkers and the interaction on LVMI and E/e' were not found.
Table 6.
Multivariate analysis of LVMI and E/e' ratio.
| Factors | LVMI |
E/e' |
||||
|---|---|---|---|---|---|---|
| Adjusted β coefficient | 95% CI of β coefficient | p value | Adjusted β coefficient | 95% CI of β coefficient | p value | |
| Intercept | 45.497 | 5.149, 85.845 | 0.028 | 3.557 | −1.014, 8.128 | 0.126 |
| hsTropT | −0.931 | −4.318, 2.456 | 0.587 | 0.070 | −0.403, 0.543 | 0.769 |
| NT-proBNP | −0.013 | −0.073, 0.047 | 0.669 | −0.003 | −0.011, 0.005 | 0.491 |
| RF | −0.308 | −18.977, 18.362 | 0.974 | −0.040 | −2.606, 0.526 | 0.976 |
| ACPA | −15.556 | −34.533, 3.420 | 0.107 | 0.580 | −2.019, 3.180 | 0.659 |
| SBP | 0.292 | 0.019, 0.565 | 0.036 | - | - | - |
| NSAID | 8.681 | 0.184, 17.178 | 0.045 | - | - | - |
| Age | - | - | - | 0.101 | 0.026, 0.176 | 0.009 |
| Interaction | ||||||
| hsTropT *RF + | 0.437 | −2.776, 3.651 | 0.788 | 0.016 | −0.427, 0.458 | 0.944 |
| hsTropT *ACPA + | 2.839 | −0.338, 6.017 | 0.079 | −0.037 | −0.470, 0.397 | 0.867 |
+, positive; LVMI, left ventricular mass index; E/e', early filling velocity on transmitral Doppler and early relaxation velocity on tissue Doppler; hsTropT, high-sensitivity troponin T; NT-proBNP, N-terminal pro-B-type natriuretic peptide; RF, rheumatoid factor; ACPA, anti-cyclic citrullinated peptide antibody; SBP, systolic blood pressure; NSAID, non-steroidal anti-inflammatory drug.
4. Discussion
The hsTropT and NT-proBNP showed a weak correlation with cardiac anatomy and function in RA patients without clinically overt cardiovascular diseases. However, the RA patients, who had higher systolic blood pressure, used NSAID, or had positive ACPA with higher hsTropT levels, had probably higher risk of LVMI which will guide the clinicians to pay attention on clinical observation and cardiac biomarkers in RA patients before clinically overt cardiac diseases are presented. Moreover, the cardiac function was also needed to be monitored in older RA patients due to the fact that higher E/e' ratio was increased by patients' age.
It was not surprising to find that hsTropT and NT-proBNP were weakly correlated with cardiac anatomy and function in our study because the RA patients had no clinically overt cardiovascular diseases. However, the hsTropT and NT-proBNP levels detected in the study population were slightly higher than those found in the general population [39], [40]. This supports some probable mechanisms of cardiac marker alterations in RA patients. According to previous reviews in the literature, hsTropT and NT-proBNP are nonspecific markers of cardiac abnormalities [41], [42], and their excretion may be affected by biological variation [43], [44].
hsTropT was correlated with cardiac structure and function to a greater extent than NT-proBNP. This may be explained by the findings of a previous study in which hsTropT was related to an abnormal myocardium, irrespective of causative factors, whereas NT-proBNP was mostly related to the compensatory cardiac ventricular response to pressure and volume overload [45]. In addition, a previous study showed that patients with high LVMI had low capillary density and high LV mass, which were related to microvascular dysfunction, resulting in an ischemic myocardium and the release of hsTropT [15]. To date, only 1 study has confirmed the relationship between hsTropT and LVMI in RA patients [46]; nonetheless, it did not account for the effect of biomarkers in RA patients.
The results of our study indicated a higher LVMI in RA patients in the presence of ACPA and RF; however, the difference was not significant, which may be attributable to the small sample size. The high LVMI in RA patients, which was similar to the findings of an increasing LVMI in pre-dialytic chronic kidney disease patients in previous studies [47], [48] may be explained by a shared mechanism of the relationship of chronic systemic inflammation in RA patients and in chronic kidney disease patients. Moreover, the indolent ischemia in RA may contribute to cardiac remodeling, resulting in an increased LVMI [20], [49].
In the present study, the effect of hsTropT on LVMI was probably modified by the presence of ACPA in RA patients without clinically overt cardiovascular diseases since it was significant in univariate, not multivariate analysis. Of note, no previous studies have taken this effect modifier into account. This interaction effect of ACPA on the relationship between hsTropT and LVMI can be mediated by the immune complex between ACPA and citrullinated proteins, including vimentin, enolase, and fibronectin, which can cause inflammation in the rheumatoid synovium and myocardial tissue [50]. An in vitro study observed strong citrullination staining in the myocardial interstitium of RA patients [51]. Higher ACPA was also associated with the presence of citrullinated protein within atherosclerotic plaques, which may play a role in the large atherosclerotic burden, leading to the impaired resolution of inflammation within the atherosclerotic plaque [52]. Increased SBP and NSAID use were related to increased LVMI could be explained by the SBP was modified left ventricular mass [53] with confirm by the high prevalence of left ventricular hypertrophy [54] and NSAIDs enhanced the effect of angiotension II [55] with causing abnormal finding on echocardiography [56].
In our study, cardiac and rheumatoid biomarkers showed no significant association with E/e'. This may be because E/e' reflects cardiac function in specific clinical symptoms of heart failure [57]. Only age was identified to be significant; in particular, as age increased, E/e' increased, which was consistent with the findings of a previous study that included healthy volunteers [58]. The effect of age can be explained by the enhanced intrinsic inflammation and inadequate resolution of inflammation [59], [60]. The identification of the modifying effect of cardiac and rheumatoid biomarkers, particularly hsTropT and ACPA, on LVMI suggested a link between the basic pathophysiology of ACPA-related inflammation and indolent myocardial ischemia with LVMI-related RA.
This study had some limitations. First, our cross-sectional design could not represent the causal relationship between biomarkers and cardiac anatomy and function; however, we included RA patients without clinically overt cardiovascular diseases who were less likely to have pathological cardiovascular diseases. Second, both RF and ACPA were recorded as positive or negative; therefore, the correlation tests for their levels were limited. Third, only 7 parameters of cardiac anatomy and 7 parameters of cardiac function were selected for use in this study, and only 1 parameter for each of anatomy and function was chosen. Fourth, the majority of patients analyzed were female, thus these biomarker findings may be limited to female patients. However, this disease was common in female so this limitation might be minimal. Fifth, the explicit information on history of alcohol consumption was not recorded even all patients said they did not drink alcohol. The bias of this information ascertainment may be minimal since the majority of RA patients were female who were less likely to have alcohol consumption. Finally, the findings of this study cannot be generalized to RA patients with clinical cardiovascular diseases.
Declaration of Competing Interest
The authors declare the following financial interests/personal relationships which may be considered as potential competing interests: Duangkamol Aiewruengsurata reports financial support was provided by Prince of Songkla University. Thanapon Nilmoje reports a relationship with Prince of Songkla University that includes: funding grants.
Acknowledgement
We would like to thank the Faculty of Medicine, Prince of Songkla University for their support.
References
- 1.Silman A.J., Pearson J.E. Epidemiology and genetics of rheumatoid arthritis. Arthritis. Res. 2002;4(Suppl 3):S265–S272. doi: 10.1186/ar578. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 2.van den Hoek J., Boshuizen H.C., Roorda L.D., Tijhuis G.J., Nurmohamed M.T., van den Bos G.A., Dekker J. Mortality in patients with rheumatoid arthritis: a 15-year prospective cohort study. Rheumatol. Int. 2017;37:487–493. doi: 10.1007/s00296-016-3638-5. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 3.Dadoun S., Zeboulon-Ktorza N., Combescure C., Elhai M., Rozenberg S., Gossec L., Fautrel B. Mortality in rheumatoid arthritis over the last fifty years: systematic review and meta-analysis. Joint. Bone. Spine. 2013;80:29–33. doi: 10.1016/j.jbspin.2012.02.005. [DOI] [PubMed] [Google Scholar]
- 4.Avina-Zubieta J.A., Thomas J., Sadatsafavi M., Lehman A.J., Lacaille D. Risk of incident cardiovascular events in patients with rheumatoid arthritis: a meta-analysis of observational studies. Ann. Rheum. Dis. 2012;71:1524–1529. doi: 10.1136/annrheumdis-2011-200726. [DOI] [PubMed] [Google Scholar]
- 5.Ma N.H., Teh C.L., Rapaee A., Lau K.B., Fong A.Y., Hi S., Chang B.C., Yew K.L., Liew H.B., Ang C.K., Ong T.K., Chua S.K., Chin R.W., Sim K.H. Subclinical coronary artery disease in Asian rheumatoid arthritis patients who were in remission: a pilot study. Int. J. Rheum. Dis. 2010;13:223–229. doi: 10.1111/j.1756-185X.2010.01533.x. [DOI] [PubMed] [Google Scholar]
- 6.Aviña-Zubieta J.A., Choi H.K., Sadatsafavi M., Etminan M., Esdaile J.M., Lacaille D. Risk of cardiovascular mortality in patients with rheumatoid arthritis: a meta-analysis of observational studies. Arthritis. Rheum. 2008;59:1690–1697. doi: 10.1002/art.24092. [DOI] [PubMed] [Google Scholar]
- 7.Hromádka M., Seidlerová J., Baxa J., Suchý D., Rajdl D., Šedivý J., Rokyta R. Relationship between hsTnI and coronary stenosis in asymptomatic women with rheumatoid arthritis. BMC. Cardiovasc. Disord. 2016;16:184. doi: 10.1186/s12872-016-0359-3. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 8.Y. Khalid, N. Dasu, A. Shah, K. Brown, A. Kaell, A. Levine, K. Dasu, A. Raminfard, Incidence of congestive heart failure in rheumatoid arthritis: a review of literature and meta-regression analysis. ESC Heart Fail, https://doi.org/10.1002/ehf2.12947. [DOI] [PMC free article] [PubMed]
- 9.Midtbø H., Gerdts E., Kvien T.K., Olsen I.C., Hirth A., Davidsen E.S., Semb A.G. Disease activity and left ventricular structure in patients with rheumatoid arthritis. Rheumatology. (Oxford) 2015;54:511–519. doi: 10.1093/rheumatology/keu368. [DOI] [PubMed] [Google Scholar]
- 10.Liang K.P., Myasoedova E., Crowson C.S., Davis J.M., Roger V.L., Karon B.L., Borgeson D.D., Therneau T.M., Rodeheffer R.J., Gabriel S.E. Increased prevalence of diastolic dysfunction in rheumatoid arthritis. Ann. Rheum. Dis. 2010;69:1665–1670. doi: 10.1136/ard.2009.124362. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 11.deFilippi C.R., de Lemos J.A., Christenson R.H., Gottdiener J.S., Kop W.J., Zhan M., Seliger S.L. Association of serial measures of cardiac troponin T using a sensitive assay with incident heart failure and cardiovascular mortality in older adults. JAMA. 2010;304:2494–2502. doi: 10.1001/jama.2010.1708. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 12.de Lemos J.A., Drazner M.H., Omland T., Ayers C.R., Khera A., Rohatgi A., Hashim I., Berry J.D., Das S.R., Morrow D.A., McGuire D.K. Association of troponin T detected with a highly sensitive assay and cardiac structure and mortality risk in the general population. JAMA. 2010;304:2503–2512. doi: 10.1001/jama.2010.1768. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 13.Kawasaki T., Sakai C., Harimoto K., Yamano M., Miki S., Kamitani T. Usefulness of high-sensitivity cardiac troponin T and brain natriuretic peptide as biomarkers of myocardial fibrosis in patients with hypertrophic cardiomyopathy. Am. J. Cardiol. 2013;112:867–872. doi: 10.1016/j.amjcard.2013.04.060. [DOI] [PubMed] [Google Scholar]
- 14.Neeland I.J., Drazner M.H., Berry J.D., Ayers C.R., deFilippi C., Seliger S.L., Nambi V., McGuire D.K., Omland T., de Lemos J.A. Biomarkers of chronic cardiac injury and hemodynamic stress identify a malignant phenotype of left ventricular hypertrophy in the general population. J. Am. Coll. Cardiol. 2013;61:187–195. doi: 10.1016/j.jacc.2012.10.012. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 15.Cramer G., Bakker J., Gommans F., Brouwer M., Kurvers M., Fouraux M., Verheugt F., Kofflard M. Relation of highly sensitive cardiac troponin T in hypertrophic cardiomyopathy to left ventricular mass and cardiovascular risk. Am. J. Cardiol. 2014;113:1240–1245. doi: 10.1016/j.amjcard.2013.12.033. [DOI] [PubMed] [Google Scholar]
- 16.Nishikimi T., Yoshihara F., Morimoto A., Ishikawa K., Ishimitsu T., Saito Y., Kangawa K., Matsuo H., Omae T., Matsuoka H. Relationship between left ventricular geometry and natriuretic peptide levels in essential hypertension. Hypertension. 1996;28:22–30. doi: 10.1161/01.hyp.28.1.22. [DOI] [PubMed] [Google Scholar]
- 17.Hamilton M.J., Robb Y., Cumming S., Gregory H., Duncan A., Rahman M., McKeown A., McWilliam C., Dean J., Wilcox A., Farrugia M.E., Cooper A., McGhie J., Adam B., Petty R., Longman C., Findlay I., Japp A., Monckton D.G., Denvir M.A. Elevated plasma levels of cardiac troponin-I predict left ventricular systolic dysfunction in patients with myotonic dystrophy type 1: A multicentre cohort follow-up study. PLoS. One. 2017;12:e0174166. doi: 10.1371/journal.pone.0174166. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 18.Satyan S., Light R.P., Agarwal R. Relationships of N-terminal pro-B-natriuretic peptide and cardiac troponin T to left ventricular mass and function and mortality in asymptomatic hemodialysis patients. Am. J. Kidney. Dis. 2007;50:1009–1019. doi: 10.1053/j.ajkd.2007.08.017. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 19.Ravassa S., Kuznetsova T., Varo N., Thijs L., Delles C., Dominiczak A., Díez J., Staessen J.A. Biomarkers of cardiomyocyte injury and stress identify left atrial and left ventricular remodelling and dysfunction: A population-based study. Int. J. Cardiol. 2015;185:177–185. doi: 10.1016/j.ijcard.2015.03.046. [DOI] [PubMed] [Google Scholar]
- 20.Bradham W.S., Bian A., Oeser A., Gebretsadik T., Shintani A., Solus J., Estis J., Lu Q.A., Todd J., Raggi P., Stein C.M. High-sensitivity cardiac troponin-I is elevated in patients with rheumatoid arthritis, independent of cardiovascular risk factors and inflammation. PLoS. One. 2012;7:e38930. doi: 10.1371/journal.pone.0038930. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 21.Slaughter L., Carson D.A., Jensen F.C., Holbrook T.L., Vaughan J.H. In vitro effects of Epstein-Barr virus on peripheral blood mononuclear cells from patients with rheumatoid arthritis and normal subjects. J. Exp. Med. 1978;148:1429–1434. doi: 10.1084/jem.148.5.1429. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 22.De Rycke L., Peene I., Hoffman I.E., Kruithof E., Union A., Meheus L., Lebeer K., Wyns B., Vincent C., Mielants H., Boullart L., Serre G., Veys E.M., De Keyser F. Rheumatoid factor and anticitrullinated protein antibodies in rheumatoid arthritis: diagnostic value, associations with radiological progression rate, and extra-articular manifestations. Ann. Rheum. Dis. 2004;63:1587–1593. doi: 10.1136/ard.2003.017574. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 23.Pope J.E., Choy E.H. C-reactive protein and implications in rheumatoid arthritis and associated comorbidities. Semin. Arthritis. Rheum. 2021;51:219–229. doi: 10.1016/j.semarthrit.2020.11.005. [DOI] [PubMed] [Google Scholar]
- 24.Nicola P.J., Maradit-Kremers H., Roger V.L., Jacobsen S.J., Crowson C.S., Ballman K.V., Gabriel S.E. The risk of congestive heart failure in rheumatoid arthritis: a population-based study over 46 years. Arthritis. Rheum. 2005;52:412–420. doi: 10.1002/art.20855. [DOI] [PubMed] [Google Scholar]
- 25.Bhatia G., Sosin M., Patel J., Grindulis K., Khattak F., Hughes E., Lip G.Y.H., Davis R.C. Left ventricular systolic dysfunction in rheumatoid disease: An unrecognised burden? Eur. J. Heart. Fail. 2005;4:67–68. doi: 10.1016/j.jacc.2005.10.059. [DOI] [PubMed] [Google Scholar]
- 26.Garza-García C., Rocío S.S., Orea-Tejeda A., Castillo-Martínez L., Eduardo C., López-Campos J.L., Keirns-Davis C. Risk factors for asymptomatic ventricular dysfunction in rheumatoid arthritis patients. ISRN. Cardiol. 2013;2013 doi: 10.1155/2013/635439. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 27.Bakhoum S.W., Ashour Z.A., Mohammed M.S., WadieFawzy M. Left ventricular function and left atrial volumes in rheumatoid arthritis patients: Subclinical cardiac involvement and relation to seropositivity. Egypt. Rheumatol. 2021;43:41–45. [Google Scholar]
- 28.Magda S.L., Mincu R.I., Florescu M., Ciobanu A.O., Udrea G.F., Cinteza M., Vinereanu D. The assessment of subclinical cardiovascular dysfunction in treated rheumatoid arthritis. Maedica. (Bucur) 2016;11:267–276. [PMC free article] [PubMed] [Google Scholar]
- 29.Arnett F.C., Edworthy S.M., Bloch D.A., McShane D.J., Fries J.F., Cooper N.S., Healey L.A., Kaplan S.R., Liang M.H., Luthra H.S. The American Rheumatism Association 1987 revised criteria for the classification of rheumatoid arthritis. Arthritis. Rheum. 1988;31:315–324. doi: 10.1002/art.1780310302. [DOI] [PubMed] [Google Scholar]
- 30.Villeneuve E., Nam J., Emery P. 2010 ACR-EULAR classification criteria for rheumatoid arthritis. Rev. Bras. Reumatol. 2010;50:481–483. [PubMed] [Google Scholar]
- 31.Rodgers J.L., Jones J., Bolleddu S.I., Vanthenapalli S., Rodgers L.E., Shah K., Karia K., Panguluri S.K. Cardiovascular risks associated with gender and aging. J. Cardiovasc. Dev. Dis. 2019;6:E19. doi: 10.3390/jcdd6020019. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 32.Xu Y., Hu H., Sun M., Tian T., Li J. The level of cardiac troponin T and its possible influence factors in maintenance hemodialysis patients. Food. Sci. Technol. 2021:42. [Google Scholar]
- 33.Kosaraju A., Goyal A., Grigorova Y., Makaryus A.N. StatPearls [Internet]. Treasure Island. StatPearls Publishing; (FL): 2022. Left ventricular ejection fraction. [PubMed] [Google Scholar]
- 34.Shaikh K.A., Quinones M.A. The diastolic stress test: a new approach to an old problem. Heart. Fail. Rev. 2011;16:339–349. doi: 10.1007/s10741-010-9217-z. [DOI] [PubMed] [Google Scholar]
- 35.Nagueh S.F., Smiseth O.A., Appleton C.P., Byrd B.F., Dokainish H., Edvardsen T., Flachskampf F.A., Gillebert T.C., Klein A.L., Lancellotti P., Marino P. Recommendations for the evaluation of left ventricular diastolic function by echocardiography: an update from the American Society of Echocardiography and the European Association of Cardiovascular Imaging. Eur. J. Echocardiogr. 2016 Jul 15;17(12):1321–1360. doi: 10.1093/ehjci/jew082. [DOI] [PubMed] [Google Scholar]
- 36.Saag K.G., Teng G.G., Patkar N.M., Anuntiyo J., Finney C., Curtis J.R., Paulus H.E., Mudano A., Pisu M., Elkins-Melton M., Outman R., Allison J.J., Suarez Almazor M., Bridges S.L., Chatham W.W., Hochberg M., MacLean C., Mikuls T., Moreland L.W., O'Dell J., Turkiewicz A.M., Furst D.E., Saag K.G., Curtis J.R., Paulus H.E., Allison J.J., Almazor M.S., Bridges S.L., Chatham W.W., Hochberg M., MacLean C., Mikuls T., Moreland L.W., O'Dell J., Turkiewicz A.M., Furst D.E., Bombardier C., Dore R.K., Golodner L.F., Hennessy S., Kavanaugh A.F., Khanna D., Kremer J.M., Leong A.L., Matteson E.L., Schousboe J.T., Tosteson A.N., Tugwell P., Yazici Y., Beukelman T., Danila M.I., Faggard J., Gaffo A., McDonough A., Nair R., Shakoory B., Verchot M., Maranian P., Scott S., Winthrop K.L., Gores G.J., Saag M., Shekelle P. American College of Rheumatology 2008 recommendations for the use of nonbiologic and biologic disease-modifying antirheumatic drugs in rheumatoid arthritis. Arthritis. Rheum. 2008;59:762–784. doi: 10.1002/art.23721. [DOI] [PubMed] [Google Scholar]
- 37.Chan B.K.C. Data Analysis using R programming. Adv. Exp. Med. Biol. 2018;1082:47–122. doi: 10.1007/978-3-319-93791-5_2. [DOI] [PubMed] [Google Scholar]
- 38.Schober P., Boer C., Schwarte L.A. Correlation coefficients: Appropriate use and interpretation. Anesth. Analg. 2018;126:1763–1768. doi: 10.1213/ANE.0000000000002864. [DOI] [PubMed] [Google Scholar]
- 39.Saenger A.K., Beyrau R., Braun S., Cooray R., Dolci A., Freidank H., Giannitsis E., Gustafson S., Handy B., Katus H., Melanson S.E., Panteghini M., Venge P., Zorn M., Jarolim P., Bruton D., Jarausch J., Jaffe A.S. Multicenter analytical evaluation of a high-sensitivity troponin T assay. Clin. Chim. Acta. 2011;412:748–754. doi: 10.1016/j.cca.2010.12.034. [DOI] [PubMed] [Google Scholar]
- 40.Pongsuthana S., Kuptapong N. Circadian variation of N-terminal pro-B-type natriuretic peptide in a normal population. J. Med. Assoc. Thai. 2019;102:6. [Google Scholar]
- 41.Daniels L.B., Maisel A.S. Natriuretic peptides. J. Am. Coll. Cardiol. 2007;50:2357–2368. doi: 10.1016/j.jacc.2007.09.021. [DOI] [PubMed] [Google Scholar]
- 42.Xu R.Y., Zhu X.F., Yang Y., Ye P. High-sensitive cardiac troponin T. J. Geriatr. Cardiol. 2013;10:102. doi: 10.3969/j.issn.1671-5411.2013.01.015. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 43.Nordenskjöld A.M., Ahlström H., Eggers K.M., Fröbert O., Jaffe A.S., Venge P., Lindahl B. Short- and long-term individual variation in cardiac troponin in patients with stable coronary artery disease. Clin. Chem. 2013;59:401–409. doi: 10.1373/clinchem.2012.191700. [DOI] [PubMed] [Google Scholar]
- 44.Nordenskjöld A.M., Ahlström H., Eggers K.M., Fröbert O., Venge P., Lindahl B. Short- and long-term individual variation in NT-proBNP levels in patients with stable coronary artery disease. Clin. Chim. Acta. 2013;422:15–20. doi: 10.1016/j.cca.2013.03.025. [DOI] [PubMed] [Google Scholar]
- 45.Yu S.R., Zhang C.Y., Xiong W.J., Chen J.T., Song J.X., Chen H. A hypothesis: Disproportion between cardiac troponin and B-type natriuretic peptide levels-A high risk and poor prognostic biomarker in patients with fulminant myocarditis. Heart. Lung. Circ. 2021;30:837–842. doi: 10.1016/j.hlc.2020.12.012. [DOI] [PubMed] [Google Scholar]
- 46.Kobayashi M., Ferreira M.B., Costa R.Q., Fonseca T., Oliveira J.C., Marinho A., Carvalho H.C., Girerd N., Rossignol P., Zannad F., Rodrigues P., Ferreira J.P. Circulating biomarkers and cardiac structure and function in rheumatoid arthritis. Front. Cardiovasc. Med. 2021;8 doi: 10.3389/fcvm.2021.754784. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 47.Rudominer R.L., Roman M.J., Devereux R.B., Paget S.A., Schwartz J.E., Lockshin M.D., Crow M.K., Sammaritano L., Levine D.M., Salmon J.E. Independent association of rheumatoid arthritis with increased left ventricular mass but not with reduced ejection fraction. Arthritis. Rheum. 2009;60:22–29. doi: 10.1002/art.24148. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 48.Abramowitz M.K., Hostetter T.H., Melamed M.L. The serum anion gap is altered in early kidney disease and associates with mortality. Kidney. Int. 2012;82:701–709. doi: 10.1038/ki.2012.196. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 49.Frieler R.A., Mortensen R.M. Immune cell and other noncardiomyocyte regulation of cardiac hypertrophy and remodeling. Circulation. 2015;131:1019–1030. doi: 10.1161/CIRCULATIONAHA.114.008788. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 50.Bongartz T., Cantaert T., Atkins S.R., Harle P., Myers J.L., Turesson C., Ryu J.H., Baeten D., Matteson E.L. Citrullination in extra-articular manifestations of rheumatoid arthritis. Rheumatology. (Oxford) 2007;46:70–75. doi: 10.1093/rheumatology/kel202. [DOI] [PubMed] [Google Scholar]
- 51.Giles J.T., Fert-Bober J., Park J.K., Bingham C.O., Andrade F., Fox-Talbot K., Pappas D., Rosen A., van Eyk J., Bathon J.M., Halushka M.K. Myocardial citrullination in rheumatoid arthritis: a correlative histopathologic study. Arthritis. Res. Ther. 2012;14:R39. doi: 10.1186/ar3752. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 52.Sokolove J., Brennan M.J., Sharpe O., Lahey L.J., Kao A.H., Krishnan E., Edmundowicz D., Lepus C.M., Wasko M.C., Robinson W.H. Brief report: citrullination within the atherosclerotic plaque: a potential target for the anti-citrullinated protein antibody response in rheumatoid arthritis. Arthritis. Rheum. 2013;65:1719–1724. doi: 10.1002/art.37961. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 53.Kunišek J., Kunišek L. Impact of blood pressure components on left ventricular hypertrophy remodeling. Acta. Clinica. Croatica. 2018 Dec;57(4):638. doi: 10.20471/acc.2018.57.04.05. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 54.Yongtai L., Jinzhi L., Lixin Z., Feifei Z., Dingding Z., Zhuang T., Yanlin Z., Wei C., Hua B., Hui W., Yicheng Z. Effect of different ranges of systolic blood pressure on left ventricular structure and diastolic function in a Chinese population: a cross-sectional population-based Shunyi study. BMJ. open. 2019 Aug 1;9(8):e028398. doi: 10.1136/bmjopen-2018-028398. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 55.Wu R., Laplante M.A., de Champlain J. Cyclooxygenase-2 inhibitors attenuate angiotensin II–induced oxidative stress, hypertension, and cardiac hypertrophy in rats. Hypertension. 2005 Jun 1;45(6):1139–1144. doi: 10.1161/01.HYP.0000164572.92049.29. [DOI] [PubMed] [Google Scholar]
- 56.van den Hondel K.E., Eijgelsheim M., Ruiter R., Witteman J.C., Hofman A., Stricker B.H. Effect of short-term NSAID use on echocardiographic parameters in elderly people: a population-based cohort study. Heart. 2011 Apr 1;97(7):540–543. doi: 10.1136/hrt.2010.200717. [DOI] [PubMed] [Google Scholar]
- 57.Santos M., Rivero J., McCullough S.D., West E., Opotowsky A.R., Waxman A.B., Systrom D.M., Shah A.M. E/e' Ratio in Patients with unexplained dyspnea: Lack of accuracy in estimating left ventricular filling pressure. Circ. Heart. Fail. 2015;8:749–756. doi: 10.1161/CIRCHEARTFAILURE.115.002161. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 58.Caballero L., Kou S., Dulgheru R., Gonjilashvili N., Athanassopoulos G.D., Barone D., Baroni M., Cardim N., Gomez de Diego J.J., Oliva M.J., Hagendorff A., Hristova K., Lopez T., Magne J., Martinez C., de la Morena G., Popescu B.A., Penicka M., Ozyigit T., Rodrigo Carbonero J.D., Salustri A., Van De Veire N., Von Bardeleben R.S., Vinereanu D., Voigt J.U., Zamorano J.L., Bernard A., Donal E., Lang R.M., Badano L.P., Lancellotti P. Echocardiographic reference ranges for normal cardiac Doppler data: results from the NORRE Study. Eur Heart J Cardiovasc. Imaging. 2015;16:1031–1041. doi: 10.1093/ehjci/jev083. [DOI] [PubMed] [Google Scholar]
- 59.Kobayashi Y., Giles J.T., Hirano M., Yokoe I., Nakajima Y., Bathon J.M., Lima J.A., Kobayashi H. Assessment of myocardial abnormalities in rheumatoid arthritis using a comprehensive cardiac magnetic resonance approach: a pilot study. Arthritis. Res. Ther. 2010;12:R171. doi: 10.1186/ar3131. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 60.Sendama W. The effect of ageing on the resolution of inflammation. Ageing. Res. Rev. 2020;57 doi: 10.1016/j.arr.2019.101000. [DOI] [PMC free article] [PubMed] [Google Scholar]