Abstract
We applied 24-h Holter monitoring to analyze the characteristics of arrhythmias and heart rate variability in Chinese patients with primary aldosteronism (PA) and compared them with age-, sex-, and blood pressure-matched primary hypertension (PH) patients. A total of 216 PA patients and 261 PH patients were enrolled. The nonstudy data were balanced using propensity score matching (PSM), and the risk variables for developing arrhythmias were then analyzed using logistic regression analysis. Before PSM, the proportion of PA patients with combined atrial premature beats and prolonged QT interval was higher than the corresponding proportion in the PH group. After PSM, the PA group had a larger percentage of transient atrial tachycardia and frequent atrial premature beats, and it had higher heart rate variability metrics. The proportion of unilateral PA combined with multiple ventricular premature beats was higher than that of bilateral PA. Older age, grade 3 hypertension, and hypokalemia were independent risk factors for the emergence of arrhythmias in PA patients. PA patients suffer from a greater prevalence of arrhythmias than well-matched PH patients.
Introduction
Primary aldosteronism (PA) is one of the most common causes of secondary hypertension (1). It is characterized by the overproduction of aldosterone and renin suppression with or without hypokalemia. Patients with PA have a higher prevalence of cardiovascular diseases than those with primary hypertension (PH), including cerebrovascular events, coronary artery disease, and arrhythmias, which are due not only to high blood pressure but also to damage that hyperaldosteronism does to the heart and blood vessels (2). For the first time, in 2020, the European Society of Hypertension (ESH) proposed including patients with atrial fibrillation (AF) of unclear cause in PA screening (3). The incidence of AF and other arrhythmias in the Chinese PA population is unknown. Most earlier studies used traditional regression methods to examine the relationship between PA and cardiovascular diseases, and the original data were prone to confounding bias. The purpose of propensity score matching (PSM) is to simplify the matching process by collapsing all confounders into a single value (4), thus making the baseline characteristics more similar and avoiding the potential for selection bias. Hence, in this study, demographic characteristics and biochemical measurements were balanced between the PA and PH groups so that the PSM-adjusted results could reflect the difference in cardiac features in the two groups more precisely and rationally. In this study of Chinese PA and PH patients, we aimed to compare their arrhythmia and heart rate variability (HRV) after correcting for confounding factors with PSM, clarify the impact of PA on the cardiac conduction system, and provide a factual basis for the early identification and prevention of PA-related cardiovascular complications.
Subjects and methods
Subjects
A total of 216 patients with PA and 261 patients with PH diagnosed by the Adrenal Center, Department of Endocrinology and Metabolism, West China Hospital of Sichuan University, from December 2018 to December 2021 were retrospectively included. PA inclusion criteria followed the 2020 consensus of the ESH (3) and the 2016 American Endocrine Society Clinical Practice Guideline (5): (i) the plasma aldosterone-to-renin ratio (ARR) screening and confirmatory test (saline loading test and/or captopril test) results were positive and (ii) the patients could proceed directly to inclusion if they had spontaneous hypokalemia, plasma aldosterone concentration (PAC) greater than 20 ng/dL, and renin below assay detection limits. PH inclusion criteria followed the 2023 arterial hypertension guideline of ESH (6) along with a negative confirmatory test, excluding secondary hypertension from other causes. In this study, 330 patients underwent the salt loading test and 457 patients underwent the captopril test.
Exclusion criteria were (i) serious organic heart disease or severe hepatic impairment; (ii) pregnancy or nursing; (iii) recent use of estrogen or a contraceptive; and (iv) aldosterone-secreting adrenocortical carcinoma, multiple endocrine neoplasms, etc.
The study protocol was approved by the Ethics Committee of West China Hospital, Sichuan University. All study subjects signed an informed consent form, agreeing to allow the use of their clinical data for medical research.
Hormone testing
Before November 2020, radioimmunoassays were used to measure PAC (Jiuding Medical Bioengineering Co) and plasma renin activity (Beijing North Institute of Biotechnology Co). After November 2020, PAC and direct renin concentration were measured by chemical immunoluminescence using a chemiluminescence immune detection system from Diasorin. All antihypertensive agents with notable impacts on ARR, such as mineralocorticoid receptor antagonists, diuretics, angiotensin-converting enzyme inhibitors, angiotensin receptor antagonists, calcium antagonists, and beta-blockers, were withdrawn before the test. α1-adrenergic receptor antagonists or nondihydropyridine calcium channel blockers could be used as substitutive medications in patients with severe hypertension. Blood was collected in mid-morning with patients in the seated position.
Adrenal venous sampling
PA patients underwent adrenal venous sampling (AVS) after completing a scan of adrenal contrast-enhanced computed tomography. All simultaneous AVS processes were performed without adrenocorticotropic hormone stimulus by an experienced urologist in our hospital. Successful cannulation of adrenal veins was confirmed through the selectivity index (the gradient of adrenal to peripheral cortisol) cutoff value that was no less than 2:1. Unilateral PA was defined as a lateralization index (the ratio of aldosterone to cortisol between the dominant and nondominant adrenal glands) higher than 2.0; bilateral PA was described as a lateralization index less than 2.0 (7). A total of 190 PA patients underwent successful AVS. The results suggested that 131 patients had unilateral forms, and 59 patients were considered to have bilateral forms.
Holter monitor examination
The SEER 12 Holter monitor (GETEMED Medizin- und Informationstechnik AG) was used to monitor ECG for 24 h. All Holter monitoring data were subsequently analyzed in line with the ACC/AHA clinical competence statement (8). Participants underwent the examination within 1 week of admission. During the monitoring period, subjects had been on stable antihypertensive treatment with α1-adrenergic receptor antagonists or nondihydropyridine calcium channel blockers. The measurements included (i) mean heart rate, atrial premature beats, atrial tachycardia, AF, ventricular premature beats, ventricular tachycardia, conduction block, ST-T alterations, and QT interval prolongation and (ii) HRV metrics. The metrics included the following: (i) time‐domain metrics: the mean of all normal R–R intervals (MeanNN), the standard deviation of all normal R–R intervals (SDNN), the standard deviations of the average R–R intervals for each 5-min segment (SDANN), mean of the standard deviations of all the R–R intervals for each 5-min segment (ASDNN), the square root of the mean squared differences of successive NN intervals (rMSSD), and the percentage of NN intervals that were more than 50 ms different from the previous interval (PNN50) and (ii) frequency-domain metrics: very-low-frequency component (VLF), low-frequency component (LF), high-frequency component (HF), and LF/HF ratio.
Statistical analysis
Analyses were performed with R4.0.3 for Windows. The Shapiro‒Wilk normality test was used to test the normality of continuous variables, with normally distributed continuous variables expressed as mean (±s.d.), nonnormally distributed continuous variables as median and interquartile range, and categorical variables as n (%). PSM was performed to equalize covariates using the 1:1 nearest-neighbor matching method for the PA and PH groups with the caliper value set at 0.01. A t-test (normally distributed) or Wilcoxon rank sum test (nonnormally distributed) was used to compare continuous variables, and the χ 2 test or Fisher’s exact probability test was used to compare categorical variables. Univariate logistic regression was performed to analyze the correlation between arrhythmic events and clinical or laboratory variables. Significant parameters in the univariate analysis (P ≤ 0.05) were included in stepwise multivariate logistic analysis, and ORs and 95% CIs were calculated. P ≤ 0.05 was statistically significant.
Results
Comparison of characteristics and metabolic parameters of patients before and after PSM
A total of 216 PA patients and 261 PH patients successfully underwent Holter monitoring. Before PSM, the baseline data suggested significant differences in age, duration of hypertension, uric acid (UA), triglycerides (TG), HDL-C, and the proportion of combined dyslipidemia between the PA and PH groups and no differences in other parameters except hormonal parameters. PA patients had higher PAC and ARR and lower concentrations of renin and serum potassium than PH patients. Therefore, age, duration of hypertension, UA, TG, and HDL-C were matched as covariates for PSM. There were 129 patients in each group after matching.
After PSM, patients in the PA group had lower concentrations of serum potassium and renin and higher PAC and ARR than patients in the PH group, whereas no significant differences were found in other variables between the two groups (Table 1), indicating that matching was effective.
Demographic characteristics and metabolic parameters in PA and PH groups after PSM
| PA (n = 129) | PH (n = 129) | P | |
|---|---|---|---|
| Demographic characteristics | |||
| Age (years) | 48.00 (15.89) | 51.00 (26.00) | 0.493 |
| Male, n (%) | 63 (48.83) | 60 (46.51) | 0.803 |
| BMI (kg/m2) | 24.96 ± 3.47 | 25.11 ± 3.81 | 0.754 |
| Duration of hypertension (months) | 60 (108) | 36 (110) | 0.309 |
| SBP (mmHg) | 149.00 (24.00) | 147.00 (19.00) | 0.635 |
| DBP (mmHg) | 99.00 (19.00) | 94 (17.00) | 0.051 |
| Antihypertensive drugs (type) | 2 (1) | 2(1) | 0.986 |
| Grade 3 hypertension, n (%) | 83 (64.34) | 90 (69.77) | 0.427 |
| Hypokalemia, n (%) | 74 (57.36) | 25 (19.38) | <0.001 |
| Diabetes, n (%) | 25 (19.37) | 26 (20.15) | 1.000 |
| Dyslipidemia, n (%) | 51 (39.53) | 61 (47.29) | 0.258 |
| Hyperuricemia, n (%) | 21 (16.28) | 22 (17.05) | 1.000 |
| Coronary artery disease, n (%) | 5 (3.90) | 10 (7.80) | 0.287 |
| Left ventricular hypertrophy, n (%) | 24 (18.6) | 13 (10.1) | 0.068 |
| Biochemical parameters | |||
| Potassium (mmol/L) | 3.39 (0.85) | 3.86 (0.49) | <0.001 |
| FBG (mmol/L) | 5.10 (1.47) | 5.23 (1.20) | 0.549 |
| UA (mmol/L) | 329.56 ± 78.09 | 334.73 ± 77.24 | 0.593 |
| TG (mmol/L) | 1.35 (0.93) | 1.40 (0.97) | 0.815 |
| HDL-C (mmol/L) | 1.27 (0.46) | 1.19 (0.44) | 0.554 |
| LDL-C (mmol/L) | 2.56 (0.89) | 2.45 (1.16) | 0.503 |
| TC (mmol/L) | 4.35 (1.10) | 4.30 (1.33) | 0.429 |
| eGFR (mL/min/1.73 m2) | 100.00 (26.81) | 94.32 (28.37) | 0.106 |
| Hormone parameters – radioimmunoassaya | |||
| PAC (ng/dL) | 28.69 (14.84) | 23.05 (10.96) | <0.001 |
| PRA (ng/mL·h) | 0.17 (0.51) | 2.86 (4.37) | <0.001 |
| ARR (ng/dL:ng/mL·h) | 142.36 (529.89) | 7.93 (10.69) | <0.001 |
| Hormone parameters – chemiluminescence assayb | |||
| PAC (ng/dL) | 29.00 (20.68) | 16.55 (11.60) | <0.001 |
| DRC (µIU/mL) | 2.41 (3.28) | 26.15 (67.21) | <0.001 |
| ARR (ng/dL:µIU/mL) | 11.95 (24.06) | 0.47 (1.39) | <0.001 |
Data are presented as mean (±s.d.), median (interquartile range) or number (%).
aBefore November 2020, radioimmunoassays were used to measure PAC and PRA.
bAfter November 2020, chemiluminescence assays were used to measure PAC and DRC.
ARR, aldosterone-to-renin ratio; BP, blood pressure; DRC, direct renin concentration; eGFR, estimated glomerular filtration rate; FBG, fasting blood glucose; HDL-C, high-density lipoprotein cholesterol; LDL-C, low-density lipoprotein cholesterol; PA, primary aldosteronism; PAC, plasma aldosterone concentration; PH, primary hypertension; PRA, plasma renin activity; PSM, propensity score matching; TC, total cholesterol; TG, triglycerides; UA, uric acid.
Comparison of Holter monitoring and HRV data of patients before and after PSM
Before PSM, the mean heart rate was slower in the PA group than in the PH group (73.25 vs 76.08 bpm, P = 0.001), and the proportion of frequent atrial premature beats (13.9 vs 7.3%, P = 0.026) and QT interval prolongation (14.4 vs 8.0%, P = 0.040) was higher in the PA group. HRV indexes showed that PA patients had higher meanNN (818 (137.2) vs 790 (150) ms, P = 0.003), SDNN (133 (39.25) vs 124 (46.00) ms, P = 0.040), and LF/HF (1.40 (0.46) vs 1.45 (0.49), P = 0.033) than PH patients.
After PSM, the PA group still had a lower mean heart rate than the PH group (72.98 vs 75.95 bpm, P = 0.013) as well as a higher percentage of transient atrial tachycardia (16.3 vs 7.0%, P = 0.032) and frequent atrial premature beats (14.0 vs 4.7%, P = 0.018). As for HRV indexes, the PA group had higher meanNN (816 (125) vs 798 (117) ms, P = 0.031), ASDNN (52 (16) vs 47 (17) ms, P = 0.003), PNN50 (7.0 (11.2) vs 5.8 (9.8) %, P = 0.042), VLF (29.07 (9.14) vs 26.63 (10.47) ms, P = 0.015), and LF (16.38 (8.18) vs 14.75 (6.48) ms, P = 0.037) than the PH group (Table 2).
Holter monitoring and heart rate variability parameters in the PA and PH groups after PSM.
| PA (n = 129) | PH (n = 129) | P | |
|---|---|---|---|
| Holter monitoring | |||
| Mean heart rate (bpm) | 72.98 ± 8.91 | 75.85 ± 9.58 | 0.013 |
| Atrial premature beats, n (%) | 118 (93.65) | 115 (89.14) | 0.673 |
| Paired atrial premature beats, n (%) | 49 (37.98) | 45 (34.88) | 0.698 |
| Atrial premature beats of bigeminy, n (%) | 13 (10.08) | 6 (4.65) | 0.153 |
| Transient atrial tachycardia, n (%) | 21 (16.30) | 9 (6.98) | 0.032 |
| Frequent atrial premature beats, n (%) | 18 (13.95) | 6 (4.65) | 0.018 |
| AF, n (%) | 0 (0.00) | 1 (0.78) | 1.000 |
| Ventricular premature beats, n (%) | 51 (39.53) | 49 (37.98) | 0.989 |
| Multiple ventricular premature beats, n (%) | 40 (31.01) | 30 (23.26) | 0.207 |
| Paired ventricular premature beats, n (%) | 14 (10.85) | 14 (10.85) | 1.000 |
| Ventricular premature beats of bigeminy, n (%) | 3 (2.33) | 1 (0.78) | 0.614 |
| Transient ventricular tachycardia, n (%) | 4 (3.10) | 3 (2.33) | 1.000 |
| Frequent ventricular premature beats, n (%) | 12 (9.30) | 11 (8.52) | 1.000 |
| Conduction block, n (%) | 14 (10.85) | 22 (17.05) | 0.209 |
| ST-T change, n (%) | 36 (27.91) | 26 (89.66) | 0.189 |
| QT interval prolongation, n (%) | 15 (11.63) | 7 (5.43) | 0.119 |
| HRV | |||
| meanNN (ms) | 816 (125.00) | 798 (117.00) | 0.031 |
| SDNN (ms) | 132.41 ± 30.44 | 126.63 ± 34.83 | 0.242 |
| SDANN (ms) | 118.38 ± 28.72 | 116.29 ± 33.67 | 0.592 |
| ASDNN (ms) | 52 (16.00) | 47 (17.00) | 0.003 |
| rMSSD (ms) | 27 (16.00) | 26 (14.00) | 0.064 |
| pNN50 (%) | 7.0 (11.20) | 5.8 (9.80) | 0.042 |
| VLF (ms) | 29.07 (9.14) | 26.63 (10.47) | 0.015 |
| LF (ms) | 16.38 (8.18) | 14.75 (6.48) | 0.037 |
| HF (ms) | 11.45 (6.45) | 10.43 (5.90) | 0.155 |
| LF/HF | 1.43 (0.51) | 1.42 (0.50) | 0.301 |
AF, atrial fibrillation; ASDNN, mean of the standard deviations of all the R–R intervals for each 5-min segment; HF, high-frequency component; HRV, heart rate variability; LF, low-frequency component; MeanNN, mean of all normal R–R intervals; PA, primary aldosteronism; PH, primary hypertension; PNN50, percentage of NN intervals that were more than 50 ms different from the previous interval; PSM, propensity score matching; rMSSD, square root of the mean squared differences of successive NN intervals; SDANN, standard deviation of the average R–R intervals for each 5-min segment; SDNN, standard deviation of all normal R–R intervals; VLF, very-low-frequency component.
Comparison of Holter monitoring data of unilateral PA and bilateral PA
Further comparison of the monitoring data of 131 unilateral PA patients and 59 bilateral PA patients showed that the proportion of unilateral PA combined with multiple ventricular premature beats (33.6 vs 16.9%, P = 0.029) was higher than that of bilateral PA. The rest of the Holter indicators were not significantly different (P > 0.05). Metabolic parameters suggested that unilateral PA had lower concentrations of serum potassium and renin and higher PAC and ARR than bilateral PA.
Risk factors for arrhythmias
Risk factors for arrhythmias in all hypertensive patients
The following factors were included as independent variables: diagnosis, age, sex, BMI, duration of hypertension, grade 3 hypertension (SBP ≥ 180 mmHg or DBP ≥ 110 mmHg), hyperuricemia, dyslipidemia, diabetes mellitus, history of hypokalemia, PAC, renin, and ARR. The hormone parameters were classified as categorical variables around the median.
For all hypertensive patients, univariate logistic regression analysis revealed that older age, grade 3 hypertension, duration of hypertension, history of diabetes mellitus, and diagnosis of PA were significant risk factors for frequent atrial premature beats (P ≤ 0.05). Multivariate logistic regression demonstrated that older age, grade 3 hypertension, and diagnosis of PA were independently associated with frequent atrial premature beats (Table 3).
Independent risk factors for arrhythmias in all hypertensive patients.
| Risk factors | Frequent atrial premature beats | Transient atrial tachycardia | ||||
|---|---|---|---|---|---|---|
| OR | 95% CI | P | OR | 95% CI | P | |
| Older age | 4.61 | 2.96–7.55 | <0.001 | 2.70 | 1.88–4.01 | <0.001 |
| Diagnosis of PA | 2.98 | 1.49–6.21 | 0.003 | 1.99 | 1.08–3.72 | 0.028 |
| Grade 3 hypertension | 2.98 | 1.30–7.82 | 0.016 | - | - | - |
PA, primary aldosteronism.
Multivariate logistic regression analysis also suggested that older age, grade 3 hypertension, and diagnosis of PA were independent risk factors for transient atrial tachycardia in all hypertensive patients (Table 3).
Hypokalemia (OR = 2.85, 95% CI (1.59–5.20), P < 0.001) and a diagnosis of PA (OR = 1.92, 95% CI (1.07–3.48), P = 0.029) were significant risk factors for QT interval prolongation in all hypertensive patients. Hypokalemia was the only independent risk factor (OR = 2.54, 95% CI (1.36–4.83), P = 0.004).
Risk factors for arrhythmias in PA patients
Table 4 shows the multivariate logistic regression analysis, which demonstrated that older age and grade 3 hypertension were independently associated with frequent premature atrial and transient atrial tachycardia in patients with PA. Moreover, hypokalemia (OR = 2.55, 95% CI (1.12–6.36), P = 0.032) was an independent risk factor for developing QT interval prolongation in PA patients.
Independent risk factors for arrhythmia in PA patients.
| Risk factors | Frequent atrial premature beats | Transient atrial tachycardia | ||||
|---|---|---|---|---|---|---|
| OR | 95% CI | P | OR | 95% CI | P | |
| Older age | 3.20 | 1.90–5.71 | <0.001 | 2.62 | 1.66–4.30 | <0.001 |
| Grade 3 hypertension | 9.53 | 2.59–62.07 | 0.003 | 3.32 | 1.26–10.50 | 0.024 |
PA, primary aldosteronism.
Arrhythmias in patients with hypokalemia and normokalemia
We further compared the incidence of arrhythmias between patients with and without hypokalemia. In the PH group, the rate of ventricular premature beats was significantly higher in the hypokalemia patients than in the normokalemia patients. The same result was found in the PA group; the incidences of ventricular premature beats and QT interval prolongation were significantly increased in hypokalemic PA patients (Table 5).
Incidence of arrhythmia in patients with hypokalemia and normokalemia.
| PH (n = 261) | P | PA (n = 216) | P | |||
|---|---|---|---|---|---|---|
| Hypokalemia (n = 55) | Normokalemia (n = 206) | Hypokalemia (n = 121) | Normokalemia (n = 95) | |||
| Atrial premature beats, n (%) | 45 (81.81) | 183 (88.83) | 0.245 | 113 (93.39) | 84 (88.42) | 0.299 |
| Paired atrial premature beats, n (%) | 17 (37.78) | 70 (33.98) | 0.789 | 40 (33.06) | 40 (42.11) | 0.221 |
| Atrial premature beats of bigeminy, n (%) | 4 (7.27) | 13 (6.31) | 1.000 | 10 (4.63) | 9 (9.47) | 0.945 |
| Transient atrial tachycardia, n (%) | 3 (5.45) | 21 (10.19) | 0.398 | 20 (16.53) | 13 (13.68) | 0.413 |
| Frequent atrial premature beats, n (%) | 3 (5.45) | 16 (7.77) | 0.768 | 17 (14.05) | 13 (13.68) | 1.000 |
| AF, n (%) | 0 (0.00) | 1 (0.49) | 1.000 | 0 (0.00) | 1 (1.05) | 0.903 |
| Ventricular premature beats, n (%) | 19 (34.55) | 81 (39.32) | 0.623 | 46 (38.02) | 33 (34.74) | 0.723 |
| Multiple ventricular premature beats, n (%) | 19 (34.55) | 39 (18.93) | 0.021 | 35 (28.93) | 30 (31.58) | 0.785 |
| Paired ventricular premature beats, n (%) | 8 (15.55) | 11 (5.34) | 0.041 | 11 (9.10) | 10 (10.53) | 0.901 |
| Ventricular premature beats of bigeminy, n (%) | 2(3.63) | 2(0.97) | 0.416 | 2(1.65) | 2(2.10) | 1.000 |
| Transient ventricular tachycardia, n (%) | 4 (7.27) | 1 (0.49) | 0.006 | 5 (4.13) | 0 (0.00) | 0.121 |
| Frequent ventricular premature beats, n (%) | 11 (20.00) | 13 (6.31) | 0.004 | 16 (13.22) | 4 (4.21) | 0.042 |
| Conduction block, n (%) | 10 (18.18) | 35 (16.99) | 0.995 | 17 (14.05) | 9 (9.47) | 0.415 |
| ST-T change, n (%) | 13 (23.64) | 45 (21.84) | 0.919 | 39 (32.23) | 21 (22.11) | 0.135 |
| QT interval prolongation, n (%) | 8 (14.55) | 13 (6.31) | 0.086 | 23 (19.01) | 8 (8.42) | 0.044 |
AF, atrial fibrillation; PA, primary aldosteronism; PH, primary hypertension.
Discussion
PA patients are much more likely to suffer from cardiovascular complications than PH patients. According to the meta-analysis by Monticone et al. (9), individuals with PA had a higher risk of stroke, LV hypertrophy, coronary artery disease, AF, and heart failure than patients with PH who had comparable blood pressure levels (OR = 2.58, 2.09, 1.77, 3.52, and 2.05). The prevalence of AF was reported to be 7.1–7.3% in PA patients (10, 11), and the incidence of other atrial or ventricular arrhythmias was 5.2% (11). Furthermore, compared to the general population, patients with AF have a higher prevalence of PA. An epidemiological analysis of more than two million persons in Sweden revealed that the prevalence of PA in patients with AF was more than twice as high as that in the general population without AF (12). Another study included 411 patients with unexplained AF, of whom 73 were diagnosed with PA (13). However, there are relatively few data on arrhythmias in the Chinese PA population.
Most studies on PA and AF have focused on patients with a relatively long course of disease. For instance, one study (14) found that the average duration of hypertension in PA patients with AF was 14 years. Two additional studies that proposed that PA patients had a significantly higher risk of developing AF than PH subjects involved monitoring for longer than ten years (15, 16). However, individuals with significant AF symptoms or rhythm already have severe cardiac disorders and an adverse prognosis. Cardiac electrical regulation and the development of AF in PA patients with a short course of illness are being investigated further. In this study, Chinese patients with PA of short duration (mean duration 3–5 years) were enrolled to identify early signs of cardiac rhythm abnormalities and to provide an empirical basis for the development of early prevention strategies for cardiovascular lesions in PA.
In this study, most of the PA participants did not have structural heart disease when they first presented, only 3.9% having combined coronary artery disease and 18.6% having left ventricular hypertrophy (Table 1). Although no difference in the incidence of AF was found between the two groups in this study, the proportion of PA patients who had paroxysmal atrial tachycardia and frequent atrial premature beats was considerably higher than that of the PH group after PSM. Paroxysmal atrial tachycardia and frequent atrial premature beats reduce left cardiac function, increasing the risk of AF (17). It has also been proposed that frequent premature atrial is an independent predictor of AF (18); it can cause acute electrical remodeling of the atria, slow atrial conduction velocity, prolong the nonreturn period, and further promote reentry and shortening of the action potential to cause new-onset AF. A few studies have reported PA patients with malignant arrhythmias (ventricular fibrillation, tip-twisting ventricular tachycardia) as the first presentation (19). Therefore, frequent atrial premature beats and paroxysmal atrial tachycardia in PA patients are probably markers of impending AF. To prevent the development of cardiac lesions (20), malignant arrhythmias, or even sudden death, the Holter monitor should be checked periodically for timely intervention (drug control or radio frequency ablation, etc.) once PA has been diagnosed regardless of the presence of palpitations and other symptoms.
Arrhythmias may develop in PA for various reasons, including arterial hypertension, electrolyte disturbances, and structural and electrical remodeling of the heart due to excessive aldosterone (21). Chronic elevated blood pressure can lead to left ventricular hypertrophy and diastolic dysfunction, a conventional risk factor for AF. Hypokalemia also plays a role in the development of arrhythmias, including resting membrane hyperpolarization, inhibition of Na+/K+ ATPase, and suppression of K+ channel conductance, which lead to prolonged action potential duration, reduced repolarization reserve, early after depolarization, delayed after depolarization, and automaticity and may eventually contribute to the development of AF (22). Nevertheless, the effect of excessive aldosterone concentration on the structural and electrical conduction system of the heart continues to be the most important mechanism (23). Aldosterone hypersecretion causes cardiac cells to produce reactive oxygen species, which stimulates the expression of pro-inflammatory and pro-fibrotic mediators and results in the infiltration of cardiac interstitial macrophages, promoting myocardial fibrosis. It also stimulates collagen secretion and synthesis in cardiomyocytes and fibroblasts as well as collagen deposition, leading to ventricular hypertrophy and ultimately causing cardiac diastolic and systolic dysfunction and increasing the occurrence of AF and other arrhythmias. Aldosterone-induced atrial fibrosis, altered calcium and potassium channel activity, intracellular sodium–calcium dysregulation, slowed conduction velocity, and shortened effective refractory period are the causes of atrial electrical remodeling, all of which can lead to AF.
The direct action of aldosterone on autonomic nerves (sympathetic and parasympathetic) is also associated with the development of arrhythmias. HRV is an indicator of cardiac autonomic function. Parasympathetic action dominates dual cardiac autonomic innervation, increasing HRV when activity is hyperactive and decreasing HRV when hypoactive. One study found that aldosterone infusion increased R–R intervals and HRV in healthy individuals, suggesting that aldosterone tends to increase cardiac parasympathetic activity (24), while an animal experiment (25) found that aldosterone infusion increased sympathetic activity. The differences between races and the complexity of the regulation of autonomic activity may have led to the differences in the above results. Our study found significant differences in autonomic activity (described by HRV variables) between the PA and PH groups. First, the PA group had a lower mean heart rate and higher levels of meanNN than the PH group. meanNN refers to the mean R–R interval. A large cohort study (26) reported a strong positive correlation between a higher meanNN as a manifestation of cardiac autonomic dysfunction and the incidence of AF. Therefore, although the PA patients in this study did not have a high incidence of AF, an elevated meanNN points to an increased chance of developing AF in the future.
Additionally, this study discovered that the ASDNN, pNN50, VLF, and LF values of the PA group were higher than those of the PH group. ASDNN reflects the role of sympathetic nerves in heart rate regulation, and its increase represents a decrease in sympathetic activity. pNN50 was mainly positively correlated with parasympathetic activity. VLF is generally thought to reflect parasympathetic activity. LF represents the dual influence of sympathetic and parasympathetic nerves, but the latter influence predominates (27). As a result, elevated HRV metrics in PA patients demonstrate the predominance of parasympathetic hyperactivity in their autonomic functions. Parasympathetic hyperfunction can contribute to atrial arrhythmias by promoting potassium outflow and delaying calcium inward flow, shortening the atrial refractory period, and reducing atrioventricular conduction (28). This is also consistent with the increased proportion of frequent atrial premature beats and paroxysmal atrial tachycardia occurring in the PA group in this study. Conversely, one study has also shown that reduced HRV predicts increased cardiac damage (29). Its inclusion of patients with a definitive diagnosis of organic heart disease distinguishes it from our study with its shorter disease course. In conclusion, excessive aldosterone in PA patients causes changes in autonomic activity, which is one of the warning signals of an arrhythmia event.
We also discovered that hypertensive patients were significantly at risk of developing arrhythmia due to the diagnosis of PA, aging, grade 3 hypertension, and hypokalemia, while older age, grade 3 hypertension, and hypokalemia independently increased the probability of arrhythmias in PA patients. Earlier studies found a higher risk of AF in hypertensive patients with a high ARR (30). A Japanese study discovered that PA patients with hypokalemia, unilateral subtypes, and increased PAC were more likely to experience cardiovascular events. Our study did not find a significant relationship between PAC, renin concentration, or ARR ratio and arrhythmia, which was first thought to be related to the fluctuation of PAC and renin concentration in patients. Second, the PAC does not correspond to the cardiac regional aldosterone concentration, which was 17 times higher in cardiac tissues than in PAC in a previous study (31). Similarly, our study found a higher percentage of unilateral PA combined with ventricular arrhythmias compared to bilateral PA, the main reasons probably related to the lower serum potassium and higher PAC and/or ARR in unilateral than in bilateral PA. According to the German Conn’s Registry (11), atrial arrhythmia was more common in those with hypokalemic PA (12.3%) than in those with normokalemic PA (7.8%). Our study further suggests that PA patients with hypokalemia are more likely to have a prolonged QT interval and ventricular premature beats than patients with normokalemic PA. The QT interval is the time between the beginning of ventricular depolarization and the end of ventricular repolarization, also known as the time of electrical contraction of the ventricles. QT interval prolongation can lead to ventricular arrhythmias. In conclusion, these risk factors should be aggressively addressed early on, with appropriate attention given to elevated blood pressure and hypokalemia, for example.
Limitations
There are a few limitations to this study. First, it was a retrospective cohort study. It was impossible to analyze all potential causes of arrhythmias, such as obstructive sleep apnea, smoking, alcohol use, and exercise habits. Second, long-term ECG recordings are ideal for HRV time-domain measurements, while frequency-domain measurements are more suitable for short-term recordings (32); we used 24-h ECG recordings to calculate the HRV data, which may also be the reason why some of the HRV data in the study were not significantly different between groups. The HRV index is influenced by more factors and has lower specificity, which limits its clinical application.
Conclusion
Chinese patients with PA had a higher risk of arrhythmia than patients with PH, mainly in the form of frequent atrial premature beats and paroxysmal atrial tachycardia. The higher HRV in PA may be caused by increased parasympathetic activity. These anomalies could be early warning signs of future AF. These findings imply that in clinical practice, we should closely evaluate PA for indications of adverse cardiovascular events, such as changes in ECG and HRV, immediately upon first diagnosis.
Declaration of interest
There is no conflict of interest that could be perceived as prejudicing the impartiality of the study reported.
Funding
This work was supported by the Sichuan Science and Technology Program (No. 23ZDYF2116).
Author contribution statement
SW, YR, and TC designed the study; CCZ, LT, and JT undertook the literature search; SW, CCZ, LT, and JT collected the data; SW and YR performed data analysis; SW wrote the first draft of the manuscript; HMT, TC, and YR revised the manuscript; all authors made critical revisions on the manuscript.
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