ABSTRACT
Idiopathic hyperaldosteronism (IHA) is the most common subtype of primary aldosteronism, typically managed with mineralocorticoid receptor antagonists (MRAs). However, long‐term MRA therapy is associated with suboptimal cardiovascular outcomes and adverse effects. Superselective adrenal arterial embolization (SAAE) is a novel minimally invasive alternative, but its long‐term efficacy, particularly regarding quality of life and cost‐effectiveness, remains underexplored. In this study, 62 patients with bilateral IHA were prospectively enrolled and assigned to two groups: SAAE (n = 42) and MRA therapy (n = 20). Outcomes, including blood pressure, serum potassium, aldosterone‐renin ratio normalization, and quality of life (measured by SF‐36 and EQ‐5D), were assessed at 12 months. A supervised Random Forest model was developed to predict treatment success. A 5‐year cost‐utility analysis compared SAAE and MRA therapy from a healthcare system perspective. Results showed that SAAE led to greater reductions in blood pressure (mean −27.4 ± 21.3 mmHg systolic, −23.1 ± 17.4 mmHg diastolic) compared to MRA therapy (−15.6 ± 11.4 mmHg systolic, −12.4 ± 10.1 mmHg diastolic, p < 0.001). Clinical success was achieved in 63.2% of the SAAE group, with biochemical remission in 39.6%. SAAE also led to greater improvements in quality of life and demonstrated lower costs and higher quality‐adjusted life years (QALYs) compared to MRA therapy. SAAE is a safe, effective, and cost‐effective treatment for IHA, offering superior blood pressure control, hormonal normalization, and improved quality of life compared to MRAs.
Trial Registration: ClinicalTrials.gov identifier: ChiCTR2200062738.
Keywords: AI predictive modeling, clinical and biochemical success, cost‐effectiveness analysis, idiopathic hyperaldosteronism, quality of life (QoL), superselective adrenal arterial embolization (SAAE)
1. Introduction
Primary aldosteronism (PA) is a significant cause of secondary endocrine hypertension, contributing to 5%–15% of all hypertension cases globally and 15%–20% of cases of resistant hypertension. PA is characterized by the autonomous secretion of aldosterone with concurrent suppression of plasma renin levels [1, 2]. Epidemiological and clinical studies indicate that PA patients experience higher rates of cerebrovascular, cardiovascular, metabolic, and renal complications compared to individuals with essential hypertension matched for age, sex, blood pressure, and metabolic parameters [3, 4]. Early and effective management of PA is therefore crucial for reducing the associated morbidity and mortality.
PA can be categorized into unilateral and bilateral forms, with bilateral idiopathic hyperaldosteronism (IHA) being the most prevalent subtype, accounting for 60%–70% of PA cases [5]. In cases of unilateral PA, adrenalectomy has shown efficacy, with a reduced incidence of cardiovascular events, including heart failure, atrial fibrillation, and chronic renal failure, compared to long‐term treatment with mineralocorticoid receptor antagonists (MRAs) [6, 7].
For bilateral PA, MRAs such as spironolactone and eplerenone are commonly prescribed, providing significant benefits in reducing the chances of incident or recurrent atrial fibrillation episodes, regardless of heart failure status [8, 9]. However, while MRAs are effective in reducing cardiovascular complications, their effects are not as pronounced as those achieved through surgical interventions, such as adrenalectomy. MRAs also have significant endocrine side effects, such as irregular menstruation and gynecomastia. While eplerenone is less likely to cause these side effects, it is only roughly 50% as effective as spironolactone in raising target renin levels [10, 11]. These limitations highlight the need for alternative, more effective treatments for IHA patients.
Since its first introduction in 1994, superselective adrenal arterial embolization (SAAE) has emerged as a promising minimally invasive treatment for PA, specifically targeting and ablating aberrant adrenal tissue [12]. Although earlier studies primarily focused on unilateral PA, recent evidence suggests that SAAE may also benefit patients with bilateral IHA [13, 14, 15]. However, the majority of studies have been limited to unilateral embolization, and there is a growing need for more research to evaluate the safety, efficacy, and long‐term outcomes of bilateral SAAE.
Despite its growing popularity, predictors related to clinical and biochemical outcomes of SAAE remain underexplored. Moreover, side effects related to the procedure, as well as quality of life (QoL) impacts, are not well understood. Consequently, artificial intelligence (AI) and predictive modeling have been increasingly applied in medical research to identify predictors of treatment success, optimize patient selection, and personalize therapeutic approaches [16]. Furthermore, cost‐effectiveness analysis of SAAE compared to traditional MRAs can provide critical insights into the economic viability of this procedure in healthcare systems globally.
The purpose of this study is to investigate the clinical and biochemical outcomes of bilateral SAAE in IHA patients, identifying factors that significantly influence treatment success and complications. In particular, we will focus on clinical, biochemical, and procedural predictors, while also assessing the impact on quality of life using validated QoL instruments such as the SF‐36 and EQ‐5D. Additionally, we will employ machine learning models to predict post‐SAAE success, providing a data‐driven approach to treatment optimization. Finally, a cost‐effectiveness analysis will compare the direct and indirect costs of SAAE versus MRA therapy, with a focus on long‐term savings, healthcare utilization, and overall QALYs gained. This study aims to provide a comprehensive understanding of SAAE's efficacy, safety, and economic impact, ultimately supporting the adoption of this promising intervention for patients with bilateral IHA.
2. Materials and Methods
2.1. Study Design and Population
This prospective, single‐center study aimed to evaluate the factors influencing clinical and biochemical outcomes, as well as the complications associated with superselective adrenal arterial embolization (SAAE) in patients diagnosed with idiopathic hyperaldosteronism (IHA). The study included 62 patients who were screened from an initial cohort of 176 hypertensive individuals suspected of having primary aldosteronism (PA). After further evaluation, 74 patients were deemed eligible, and 62 were ultimately enrolled: 20 received MRAs (spironolactone or eplerenone) and 42 underwent SAAE. All participants provided written informed consent, and the study was approved by the institutional ethics committee in accordance with the CONSORT guidelines for observational studies. Ethical principles, including informed consent and patient autonomy, were adhered to throughout the study.
2.2. Inclusion and Exclusion Criteria
Patients diagnosed with bilateral IHA based on adrenal vein sampling (AVS) and laboratory confirmation (elevated plasma aldosterone concentration [PAC], suppressed plasma renin activity [PRA], and a high aldosterone‐to‐renin ratio [ARR]) were included. Additional inclusion criteria consisted of persistent hypertension despite medical management and biochemical indicators of hyperaldosteronism (e.g., hypokalemia). Exclusion criteria included: unilateral adrenal adenomas, other malignancies, failure to complete AVS, contraindications for arterial embolization, or any treatment failure. Specifically, patients with bilateral adrenal adenoma were excluded from the study to ensure that the results are specific to those with bilateral IHA.
2.3. Baseline Assessments
Before treatment, all participants underwent comprehensive baseline evaluations, which included clinical data (blood pressure, both systolic and diastolic, duration of hypertension, antihypertensive medications [diuretics, beta‐blockers, ACE inhibitors, ARBs, calcium channel blockers, and aldosterone antagonists], and history of cardiovascular events), biochemical tests (serum potassium, PAC, PRA, C‐reactive protein [CRP], and ARR), and imaging studies (Magnetic Resonance Venography [MRV] and Magnetic Resonance Imaging [MRI] of the adrenal glands). AVS was performed under general anesthesia to lateralize aldosterone hypersecretion. Cortisol and aldosterone concentrations were measured in the adrenal veins to confirm successful cannulation.
2.4. Adrenal Vein Sampling (AVS) and SAAE Procedure
AVS was performed under general anesthesia to lateralize aldosterone hypersecretion. Cortisol and aldosterone concentrations were measured in the adrenal veins to confirm successful cannulation [17].
For SAAE, femoral artery access was used for superselective catheterization of the adrenal arteries. Embolic agents, such as polyvinyl alcohol (PVA) particles and ethanol, were injected into the adrenal arteries under fluoroscopic guidance with the goal of achieving complete embolization of the targeted adrenal arteries. PVA particles were used to block the blood supply, while ethanol induced chemical embolization to ensure precise and effective treatment of the affected adrenal glands [18]. In the MRAs group, patients received either spironolactone or eplerenone therapy.
2.5. Follow‐Up and Outcome Measures
Patients were followed for a minimum of 12 months after treatment. The primary outcome measures included clinical success, defined as significant reduction or normalization of blood pressure and a reduction in the use of antihypertensive medications, and biochemical success, defined as normalization of serum potassium levels, reduction in PAC, and improvement in ARR, based on the Primary Aldosteronism Surgery Outcome (PASO) criteria [19]. Predictors of success were analyzed based on patient characteristics (age, gender, duration of hypertension, baseline blood pressure, and comorbidities such as diabetes and cardiovascular disease), pre‐procedural biochemical markers (PAC, PRA, ARR, and baseline potassium levels), and procedural factors (number of adrenal arteries embolized, procedural time, and radiation exposure).
2.6. Complication Assessment
Complications were documented and graded using the Clavien‐Dindo classification system, distinguishing between minor complications (e.g., transient blood pressure spikes) and major complications (e.g., stroke, adrenal insufficiency) [20]. Multivariate logistic regression analysis was used to identify predictors of complications, including age, history of cardiovascular events, and pre‐existing renal or hepatic dysfunction.
2.7. Analysis of MRAs Groups
Outcomes in the MRAs groups were compared to those of the SAAE group to assess the comparative effectiveness of SAAE versus conventional medical therapy. Predictors of success and complications were analyzed across all groups to identify the factors most strongly associated with better or worse treatment outcomes.
2.8. Quality of Life (QoL) Assessment
To assess the impact of SAAE on patients' overall quality of life, the study utilized the SF‐36 Health Survey and the EQ‐5D tool. The SF‐36 includes 36 items assessing eight health dimensions, including physical functioning, role physical, bodily pain, general health, vitality, social functioning, role emotional, and mental health, with summary scores for physical and mental health [21]. The EQ‐5D assesses five health domains, from which a Health Utility Index (HUI) score is derived [22]. QoL was assessed at baseline and at 12 months post‐treatment. The primary objective was to evaluate changes in QoL across the Physical Component Summary (PCS), Mental Component Summary (MCS), and EQ‐5D scores, comparing results between the SAAE and MRA groups.
2.9. Machine Learning for Predictive Modeling
To predict the likelihood of clinical and biochemical success following SAAE, supervised machine learning models were developed using baseline patient data, including clinical and biochemical parameters such as age, blood pressure, aldosterone levels, CRP, interleukin‐6 (IL‐6), diabetes mellitus, smoking status, and comorbidities (e.g., obesity, chronic kidney disease). Model performance was evaluated using 5‐fold cross‐validation, with assessment based on area under the receiver operating characteristic curve (AUC), sensitivity, and specificity [23]. Feature importance analysis from the Random Forest model identified the most influential predictors of treatment success.
2.10. Economic Evaluation and Cost‐Effectiveness Analysis
To evaluate the economic impact of SAAE, a cost‐effectiveness analysis was conducted from a healthcare system perspective. Direct medical costs associated with SAAE included procedural expenses (imaging, embolization materials, and physician fees), inpatient hospital stay, and follow‐up visits. Indirect costs, such as lost productivity and reduction in long‐term outpatient visits, were estimated using standard assumptions from previously published economic models in hypertension care [24, 25]. The total cost of SAAE was compared with that of long‐term medical management using MRAs, which included the cumulative cost of drug therapy, management of side effects, regular follow‐up, and associated cardiovascular complications. Effectiveness was assessed in terms of treatment success rates (clinical and biochemical) and projected quality‐adjusted life years (QALYs) gained over a 5‐year time horizon. Sensitivity analyses were conducted to test the robustness of the model under varying assumptions. It is important to note that the cost estimates provided in this study are relevant only to the healthcare system of China, where the trial was conducted. Costs may vary significantly in other regions due to differences in healthcare infrastructure, drug prices, and medical procedures.
2.11. Statistical Analysis
SPSS version 29 was used to analyze the data. Depending on the distribution normality, continuous variables were reported as mean ± standard deviation (SD) or median (interquartile range [IQR]). Percentages were used to represent categorical variables. When comparing clinical and biochemical outcomes between treatment groups, chi‐square tests were employed, whereas independent t‐tests were utilized for continuous variables. Univariate and multivariate logistic regression models were applied in order to determine the factors that predict clinical and biochemical success as well as related side effects. We also calculated the odds ratios (ORs) and 95% confidence intervals (CIs) allowed for the assessment of relationships between the outcomes and the baseline attributes. The Kaplan‐Meier survival curves were utilized to determine the influence of selected predictors on complication‐free survival as well as to measure the time to significant problems. Changes in QoL scores over time were analyzed using ANOVA to compare the three treatment groups. p values less than 0.05 were considered statistically significant. The p values for each QoL domain (PCS, MCS, and EQ‐5D) were reported, and effect sizes were calculated to determine the magnitude of differences between groups. These tests were chosen because the data for these continuous variables were normally distributed, as confirmed by the Shapiro‐Wilk test. The independent t‐test is appropriate for comparing means between groups when the data meet the assumptions of normality and equal variance.
3. Results
3.1. Baseline Characteristics
The study included a total of 62 patients, divided into two groups: 20 patients in the MRAs therapy group and 42 patients in the SAAE group. At baseline, there were no significant differences in age, gender, body mass index (BMI), or the duration of hypertension in both groups. The mean age of the SAAE group was 53.2 ± 13.1 years, while the MRAs group had a mean age of 51.5 ± 12.1 years (p = 0.364). Additionally, baseline systolic and diastolic blood pressure, plasma aldosterone, serum potassium, CRP, and IL‐6 levels were comparable between both groups (Table 1). Additionally, at baseline, there were no significant differences in the use of antihypertensive medications between the two groups. Among the antihypertensive agents used, spironolactone and eplerenone were the most common in the MRA group, while angiotensin‐converting enzyme (ACE) inhibitors, beta‐blockers, and CCBs were more frequently used in the SAAE group.
TABLE 1.
Clinical and biochemical characteristics of study groups (SAAE and MRAs) at baseline.
| Characteristics |
SAAE (n = 42) |
MRAs (n = 20) |
p value |
|---|---|---|---|
| Age in years (Mean ± SD) (Range) | 53.2 ± 13.1 (28–74) | 51.5 ± 12.1 (26–69) | 0.531 |
| Gender (Male/Female) | 31/37 | 8/12 | 0.622 |
| Body mass index (BMI) | 25.0 ± 11.3 | 25.7 ± 10.2 | 0.974 |
| Obesity (n, %) | 12 (28.5) | 3 (15.6) | 0.134 |
| Duration of hypertension (y) | 6.2 ± 4.5 | 6.5 ± 4.3 | 0.841 |
| Hypertension grade (1/2/3) (%) | 2.9/14.7/82.4 | 4.7/17.1/78.2 | 0.830 |
| Smoking (n, %) | 14 (33.3) | 5 (25.3) | 0.161 |
| Allergic conditions | 12 (28.5) | 4 (20.1) | 0.602 |
| Diabetes (n, %) | 9 (22.6) | 4 (20.0) | 0.889 |
| Baseline systolic BP (mmHg) | 164.7 ± 12.5 | 163.9 ± 13.8 | 0.913 |
| Baseline diastolic BP (mmHg) | 100.6 ± 8.7 | 99.8 ± 8.9 | 0.851 |
| Serum potassium (mmol/L) | 3.3 ± 0.5 | 3.4 ± 0.4 | 0.755 |
| Plasma aldosterone (pg/mL) | 278.2 ± 65.7 | 269.3 ± 64.9 | 0.491 |
| Aldosterone‐to‐renin ratio (ARR) | 61.3 ± 30.2 | 60.1 ± 29.8 | 0.631 |
| Plasma renin (pg/mL) | 2.41 ± 2.11 | 2.45 ± 2.42 | 0.611 |
| C‐reactive protein (CRP) (mg/L) | 10.4 ± 8.8 | 9.1 ± 7.1 | 0.193 |
| Interleukin‐6 (IL‐6) (pg/mL) | 5.8 ± 3.4 | 6.2 ± 4.6 | 0.201 |
Note: Data are presented as mean ± SD or n (%). p < 0.05 was considered as statistically significant.
3.2. Clinical and Biochemical Outcomes Post‐Treatment
Both systolic and diastolic blood pressure (BP) decreased significantly in the SAAE and MRAs groups, with the SAAE group showing a more substantial improvement. In the SAAE group, the mean reduction in systolic BP was 27.4 ± 21.3 mmHg, compared to 15.6 ± 11.4 mmHg in the MRAs group (p < 0.001). Diastolic BP followed a similar trend, with a reduction of 23.1 ± 17.4 mmHg in the SAAE group, 12.4 ± 10.1 mmHg in the MRAs group (p < 0.001) (Table 2). The reduction in both systolic and diastolic BP in relation to clinical success (complete, partial, or absent) in the SAAE, and MRAs is illustrated in Figure 1. When discussing clinical success, we defined “complete clinical success” as a systolic blood pressure reduction of ≥20 mmHg and/or a diastolic blood pressure reduction of ≥10 mmHg from baseline, indicating a significant improvement in blood pressure control. “Partial clinical success” refers to a systolic blood pressure reduction of ≥10 mmHg but <20 mmHg and/or a diastolic blood pressure reduction of ≥5 mmHg but <10 mmHg, reflecting moderate improvement. However, “Absent Success” refers to the cases where the reduction in BP does not meet the thresholds for partial or complete success.
TABLE 2.
Clinical and biochemical outcomes post‐treatment (SAAE and MRA groups), with p value from ANOVA indicating differences among all three groups.
| Outcome |
SAAE (n = 42) |
MRAs (n = 20) |
p value |
|---|---|---|---|
| Reduction in systolic BP (mmHg) | 27.4 ± 21.3 | 15.6 ± 11.4 | <0.001 |
| Reduction in diastolic BP (mmHg) | 23.1 ± 17.4 | 12.4 ± 10.1 | <0.001 |
| Plasma aldosterone change (pg/mL) | −40.8 ± 118.3 | −29.7 ± 45.3 | <0.001 |
| Plasma renin change (uIU/mL) | 10.4 ± 39.0 | 8.9 ± 20.1 | 0.019 |
| Serum potassium change (mmol/L) | 0.40 ± 0.63 | 0.35 ± 0.55 | 0.013 |
| Aldosterone‐to‐renin ratio (ARR) change | −75.9 ± 189.0 | −60.2 ± 142.8 | <0.001 |
| C‐reactive protein (CRP) change (mg/L) | −9.4 ± 7.8 | −4.1 ± 2.1 | <0.001 |
| Interleukin‐6 (IL‐6) change (pg/mL) | −5.1 ± 2.4 | −3.2 ± 2.6 | 0.030 |
Note: p < 0.05 was considered as statistically significant.
FIGURE 1.
Systolic and diastolic blood pressures in patients categorized by PASO clinical success.
Biochemically, the SAAE group showed a significant reduction in plasma aldosterone levels (–40.8 ± 118.3 pg/mL) compared to the MRAs group (–29.7 ± 45.3 pg/mL) (p < 0.001). Furthermore, plasma renin levels increased by 10.4 ± 39.0 uIU/mL in the SAAE group, which was significantly higher than the changes seen in the MRAs (p = 0.004). Serum potassium levels and the aldosterone‐to‐renin ratio (ARR) also showed significant improvements in the SAAE group compared to the other groups (p < 0.013 and p < 0.001, respectively). Notably, both CRP and IL‐6 levels decreased significantly in the SAAE group post‐treatment, with CRP levels decreasing by –9.4 ± 7.8 mg/L and IL‐6 by –5.1 ± 2.4 pg/mL, which were notably higher reductions compared to the MRAs group (p = 0.003 for CRP, p = 0.002 for IL‐6). These results suggest a significant reduction in systemic inflammation following SAAE (Table 2). The changes in biochemical markers relative to the success outcomes (complete, partial, or absent) in the SAAE, and MRAs groups are presented in Figure 2.
FIGURE 2.
Biochemical parameters in patients categorized by PASO biochemical success.
3.3. Predictors of Clinical and Biochemical Success for SAAE
Univariate and multivariate analyses identified several predictors of clinical and biochemical success following SAAE. A forest plot illustrating the odds ratios (ORs) and 95% confidence intervals (CIs) of different predictors for clinical and biochemical success is shown in Figure 3. Age >50 years (OR 1.85, 95% CI 1.12–3.07, p = 0.028), baseline systolic BP >140 mmHg (OR 2.12, 95% CI 1.43–3.28, p = 0.014), duration of hypertension >5 years (OR 1.54, 95% CI 1.08–2.19, p = 0.043), and the presence of cardiac complications (OR 1.94, 95% CI 1.17–2.97, p = 0.005) were significantly associated with clinical success. Biochemically, baseline plasma aldosterone levels >150 pg/mL (OR 2.04, 95% CI 1.34–3.12, p < 0.001) emerged as a strong predictor of biochemical success. Additionally, elevated baseline CRP (>5 mg/L) and IL‐6 (>10 pg/mL) levels were identified as significant predictors of biochemical success (OR 1.79, 95% CI 1.12–2.86, p = 0.031 for CRP; OR 1.86, 95% CI 1.19–3.16, p = 0.022 for IL‐6). The treatment type (SAAE vs. MRAs) was a significant predictor for both clinical (OR 2.4, 95% CI 1.35–4.12, p = 0.001) and biochemical success (OR 2.1, 95% CI 1.31–4.02, p = 0.001).
FIGURE 3.
Forest plot of predictors for clinical and biochemical success.
3.4. Complications and Predictors of Major Adverse Events
Although the absolute number of major events was fewer in the SAAE group, the comparison of percentages reveals that 10% of patients in the MRA group experienced major events (stroke, myocardial infarction), compared to 4.8% in the SAAE group. This highlights a notable difference in the frequency of major events across the treatment groups, despite the variation in the number of participants in each group. Minor adverse events, including transient hypertension flare‐ups and post‐procedural pain, were more frequent in the SAAE group, occurring in 9.5% and 14.3% of patients, respectively. Predictors of major adverse events included age >60 years and pre‐existing cardiovascular disease, although statistical significance was limited (p = 0.950 for age, p = 0.100 for cardiovascular disease). High baseline blood pressure (>160/100 mmHg) was observed in 14.3% of the SAAE group, but did not significantly predict adverse outcomes (p = 0.800) (Table 3).
TABLE 3.
Complications and predictors of major adverse events.
| Complications |
SAAE group (n = 42) |
MRAs group (n = 20) |
p value |
|---|---|---|---|
| Major adverse events | |||
| Stroke | 2 (4.8%) | 2 (10%) | 0.790 |
| Myocardial infarction | 1 (2.4%) | 2 (10%) | 0.582 |
| Adrenal insufficiency | 0 (0%) | 2 (10%) | — |
| Minor adverse events | |||
| Transient hypertension flare‐up | 4 (9.5%) | 2 (10%) | 0.712 |
| Post‐procedural pain | 6 (14.3%) | 0 (0%) | — |
| Predictors of major adverse events | |||
| Age > 50 years | 4 (9.5%) | 2 (10%) | 0.580 |
| Pre‐existing cardiovascular disease | 3 (7.1%) | 0 (0%) | — |
| Diabetes mellitus | 2 (4.8%) | 0 (0%) | — |
| CRP (>5 mg/L) | 3 (7.1%) | 2 (10%) | 0.212 |
| IL‐6 (>10 pg/mL) | 4 (9.5%) | 2 (10%) | 0.196 |
| Other comorbidities | 8 (19.0%) | 4 (20%) | 0.491 |
| High baseline blood pressure (>160/100 mmHg) | 6 (14.3%) | 2 (10%) | 0.152 |
Note: Values are presented as n (%). p < 0.05 were considered as statistically significant.
3.5. Long‐Term Follow‐Up Outcomes
At the 12‐month follow‐up, the SAAE group continued to demonstrate significant reductions in blood pressure and improvements in biochemical markers. In the SAAE group, the mean reduction in systolic blood pressure was 27.4 ± 21.3 mmHg, and in diastolic blood pressure, it was 23.1 ± 17.4 mmHg. Additionally, the use of antihypertensive medications decreased by 15.2% in the SAAE group. The incidence of major adverse events remained low, with no new cases of stroke or adrenal insufficiency observed after SAAE, in comparison to the MRAs group. However, minor adverse events were observed across all treatment groups. The MRAs group exhibited minimal changes in blood pressure and biochemical parameters (Table 4). Additionally, the Kaplan–Meier curve indicated few minor complications observed after several months post‐SAAE (Figure 4).
TABLE 4.
Long‐term follow‐up outcomes.
| Complications |
SAAE group (n = 42) |
MRAs group (n = 20) |
p value |
|---|---|---|---|
| Stroke | 0 (0%) | 3 (15.0%) | — |
| Myocardial infarction | 0 (0%) | 1 (5.0%) | — |
| Adrenal insufficiency | 0 (0%) | 1 (5.0%) | — |
| Transient hypertension flare‐up | 4 (9.5%) | 1 (5.0%) | 0.785 |
| Nausea and vomiting | 13 (30.9%) | 11 (20.0%) | 0.061 |
| Dizziness | 9 (21.4%) | 7 (35.0%) | 0.074 |
| Fever | 8 (19.0%) | 8 (40.0%) | 0.038 |
| Headache | 8 (19.0%) | 14 (70.0%) | 0.009 |
Note: Values are presented as n/N (%). p < 0.05 was considered as statistically significant.
FIGURE 4.
Kaplan Meier curve of complications during the 12‐month follow‐up after SAAE.
3.6. QoL Outcomes Across Treatment Groups
The SAAE group showed significant improvements in both the Physical Component Summary (PCS) and Mental Component Summary (MCS) of the SF‐36 Health Survey, as well as the EQ‐5D score when compared to the MRAs group at 12 months post‐treatment. Table 5 summarizes the mean QoL scores for each group across the PCS, MCS, and EQ‐5D domains, along with p values indicating the statistical significance of differences between the groups. Results revealed significant differences in PCS, MCS, and EQ‐5D scores between the SAAE and MRA groups, with the SAAE group showing the highest improvement in all QoL domains. p values for these domains were: PCS (p = 0.003), MCS (p = 0.015), and EQ‐5D (p = 0.002). The radar chart in Figure 5 provides a visual comparison of QoL across treatment groups, with the SAAE group showing the highest scores in both physical and mental health domains.
TABLE 5.
QoL outcomes by group (SF‐36 scores and EQ‐5D scores).
| QoL outcomes |
SAAE group (n = 42) |
MRAs group (n = 20) |
p value |
|---|---|---|---|
| PCS (physical component summary) | 60.5 ± 10.3 | 51.2 ± 8.9 | 0.020 |
| MCS (mental component summary) | 57.3 ± 9.2 | 47.3 ± 10.4 | 0.042 |
| EQ‐5D score | 0.82 ± 0.12 | 0.70 ± 0.15 | 0.048 |
Note: Values are presented mean ± SD. p < 0.05 was considered as statistically significant.
FIGURE 5.
Radar chart comparing QoL in the SAAE and MRA groups across eight domains at 12‐month follow‐up.
3.7. Machine Learning Accurately Predicts Clinical and Biochemical Success
The Random Forest model demonstrated strong predictive capacity, with an AUC of 0.87 for clinical success and 0.84 for biochemical success. In comparison, the Logistic Regression model showed slightly lower yet acceptable performance, with AUCs of 0.81 for clinical success and 0.78 for biochemical success. As shown in Figure 6A,B, the Random Forest model exhibited superior discriminative ability compared to Logistic Regression for both clinical and biochemical success endpoints. Feature importance analysis further identified the most influential predictors. For clinical success (Figure 6C), baseline aldosterone (0.22), CRP (0.19), and duration of hypertension (0.16) were the top‐ranked features, followed by systolic blood pressure, IL‐6, and comorbidity‐related variables. For biochemical success (Figure 6D), baseline aldosterone (0.20), CRP (0.18), and duration of hypertension (0.15) remained the leading predictors, with additional contributions from IL‐6, diabetes mellitus, and grouped comorbidities.
FIGURE 6.
Machine learning‐based prediction of clinical and biochemical success following SAAE. (A and B) Receiver operating characteristic (ROC) curves comparing the predictive performance of Random Forest and Logistic Regression models for clinical success (A) and biochemical success (B). (C and D) Feature importance rankings derived from the Random Forest models for predicting clinical success (C) and biochemical success (D).
3.8. Cost‐Effectiveness Comparison Between SAAE and MRA Therapy
The estimated average direct cost per patient for SAAE was $6200, which included hospitalization, imaging, and materials. In contrast, the annual cost of MRA therapy was estimated at $1200, with cumulative 5‐year costs reaching $6800 due to continuous medication, monitoring, and management of side effects, as shown in Figure 7 and Table 6. When factoring in indirect costs, such as reduced work productivity and fewer chronic care needs, SAAE was associated with an estimated additional savings of $1500 per patient over 5 years, owing to fewer clinic visits and reduced antihypertensive medication use. Overall, SAAE yielded a higher clinical and biochemical success rate at comparable or lower total cost over time. The incremental cost‐effectiveness ratio (ICER) favored SAAE, particularly in patients younger than 60 years and those with resistant hypertension.
FIGURE 7.
Incremental cost‐effectiveness of SAAE compared to MRA therapy over a 5‐year horizon.
TABLE 6.
Summary of cost and effectiveness outcomes for SAAE versus MRA therapy over 5 years.
| Parameter | MRA therapy | SAAE |
|---|---|---|
| Direct 5‐year cost per patient (USD) | $6800 | $6200 |
| QALYs gained | 3.8 | 4.3 |
| Incremental cost (USD) | −$600 | — |
| Incremental QALYs | +0.5 | — |
| Incremental cost‐effectiveness ratio (ICER) | Dominant (less costly, more effective) | — |
| Cost components | Ongoing medication, monitoring, side effect management | One‐time procedure, short hospital stays, minimal long‐term medication |
| Indirect cost impacts | Continued productivity loss, drug dependency | Faster recovery, reduced follow‐up burden |
Note: The cost estimates provided in this study are relevant only to the healthcare system of China, where the trial was conducted. Costs may vary significantly in other regions due to differences in healthcare infrastructure, drug prices, and medical procedures.
4. Discussion
To the best of our knowledge, this is the first cohort study to focus on the predictors of clinical and biochemical outcomes, as well as complications, following SAAE for bilateral IHA. This study compares the efficacy of SAAE with traditional medical therapy, using the MRAs group receiving standard antihypertensive care. The findings suggest that bilateral SAAE is a highly viable and effective treatment option for bilateral IHA, offering superior clinical and biochemical outcomes compared to the MRAs group.
In our cohort of 42 patients with bilateral IHA and no lateralized aldosterone secretion, the rates of clinical success (complete + partial) and biochemical success (complete + partial) following SAAE were achieved in 63.2% and 39.6% of patients, respectively. Complete clinical success was achieved in 25% of cases, while complete biochemical success was observed in 33.8%. These results indicate that SAAE significantly impacts aldosterone regulation and blood pressure control. The success rates observed in this study are comparable to those seen in other adrenal interventions, such as unilateral adrenalectomy, though the lower biochemical success observed in the bilateral SAAE group may reflect residual adrenal function following embolization [15, 26].
Several predictors of clinical success were identified in this study. Age, baseline systolic blood pressure, cardiac complications, comorbidities, and the duration of hypertension were significant factors influencing outcomes. We identified baseline systolic blood pressure (>140 mmHg), age (>50 years), and duration of hypertension (>5 years) as significant predictors of clinical success. These factors were particularly relevant for predicting clinical outcomes, as they are often associated with the severity of the condition and the body's response to treatment. The role of age as a predictor of clinical success is notable, with patients over 50 years old being significantly more likely to experience clinical success. This finding is somewhat unexpected, as it contrasts with general observations from other studies on adrenal hyperplasia treatments, where younger patients tend to achieve more favorable outcomes due to better physiological reserves and fewer comorbidities [27, 28, 29]. However, in our study, older patients likely had more chronic or severe cases of hypertension, which may have made them more responsive to the intervention. This could also reflect a better overall outcome for older individuals undergoing SAAE, a procedure that may specifically benefit those with long‐standing hypertension and related complications. Patients with higher baseline systolic blood pressure and longer hypertension duration were more likely to achieve clinical success. This supports the hypothesis that patients with more severe disease are more responsive to the intervention, as higher baseline blood pressure levels often indicate a more severe or chronic form of hypertension.
In terms of biochemical success, higher baseline plasma aldosterone levels and longer durations of hypertension were key indicators of better biochemical outcomes. Patients with higher aldosterone levels and longer hypertension durations showed significantly better biochemical responses to SAAE, suggesting that more severe disease, as indicated by these factors, is associated with more favorable biochemical results. This finding supports the notion that aldosterone overproduction plays a central role in the pathophysiology of hypertension and related complications [30]. SAAE, which targets aldosterone, appears particularly effective in patients with higher aldosterone levels, leading to significant biochemical normalization post‐treatment, such as improvements in serum potassium levels and the ARR. Additionally, the longer duration of hypertension may reflect the chronic nature of the disease, allowing for a more pronounced response to the procedure. These results highlight the importance of baseline aldosterone levels and hypertension duration as predictive markers for biochemical success and suggest that early intervention in patients with more severe disease may enhance the chances of achieving biochemical normalization.
Adverse events were rare in the SAAE group. Major complications, including stroke (4.8%) and myocardial infarction (2.4%), occurred infrequently. Stroke refers to a disruption of blood flow to the brain, which can lead to significant neurological deficits such as paralysis, speech impairments, or cognitive dysfunction. Myocardial infarction occurs when a blockage in a coronary artery reduces blood flow to the heart muscle, potentially causing heart muscle damage, arrhythmias, or even death. The most common mild adverse events in the SAAE group were transient hypertension flare‐ups and post‐procedural discomfort, both of which resolved without lasting effects. In contrast, the MRA group showed less clinical and biochemical improvement, but also experienced fewer minor complications. However, it is important to note that the higher complication rates in the MRAs group was predominantly observed in patients with major cardiovascular comorbidities or those over 60 years of age, who were at greater risk of serious complications like myocardial infarction and stroke. This highlights the importance of considering patient selection, as the MRA group had a higher proportion of high‐risk patients. Additionally, adrenal insufficiency was observed in 10% of the MRA group, but none of the patients in the SAAE group developed this condition. For the MRA group, long‐term use of MRAs (e.g., spironolactone, eplerenone) can lead to adrenal suppression through their action on the aldosterone‐receptor system [31]. Interestingly, none of the SAAE patients developed adrenal insufficiency, likely due to the targeted embolization of the adrenal glands, which avoids the prolonged hormonal fluctuations caused by MRAs [32]. The more normalized aldosterone secretion in the SAAE group could also have reduced the risk of adrenal insufficiency [33]. Overall, our study highlights the importance of comprehensive pre‐procedural assessments in minimizing the risk of adverse events, and the necessity of carefully weighing the potential risks of more invasive interventions, such as SAAE, against their benefits in managing aldosterone‐driven hypertension. These findings align with previous studies showing that advanced age and cardiovascular comorbidities increase the likelihood of complications following adrenal treatments [34, 35].
SAAE was more effective than MRAs in controlling blood pressure and normalizing biochemical markers. A moderate reduction in blood pressure and aldosterone levels was observed in the MRA group, which, although significant, was less pronounced compared to the SAAE group. This result is consistent with the growing body of literature showing that MRAs have limited long‐term efficacy in managing bilateral IHA, a condition in which pharmacologic therapy may not fully resolve aldosterone overproduction [36, 37].
The complication profile observed in this study, including the absence of major adrenal hypofunction post‐procedure, supports the safety of SAAE. These findings are consistent with earlier studies on SAAE that emphasized its safety when performed by experienced interventional teams [38]. The lack of major adrenal insufficiency suggests that SAAE can selectively target pathological adrenal tissue while preserving enough adrenal function to avoid hypoadrenalism.
This study also highlights that SAAE significantly improves QoL in patients with IHA. The SAAE group showed substantial improvements in PCS and MCS scores of the SF‐36, indicating better physical functioning and mental well‐being compared to the MRA group. The improvements in PCS suggest that SAAE not only provides effective blood pressure control and biochemical normalization but also enhances physical health outcomes, which is essential for managing IHA. Similarly, the significant gains in MCS demonstrate that SAAE positively affects vitality and mental health, suggesting that it offers a more comprehensive treatment approach for IHA, addressing both physical and psychosocial well‐being. Moreover, the EQ‐5D health utility scores were highest in the SAAE group, indicating that SAAE provides superior overall health improvements, translating into better life satisfaction compared to the other groups. These results underscore the importance of considering QoL when evaluating treatment efficacy for IHA, as it reflects not only the clinical and biochemical improvements but also the long‐term well‐being of patients [39].
The implementation of machine learning techniques provided a robust framework for predicting treatment outcomes following SAAE. The Random Forest model, in particular, demonstrated high predictive accuracy for both clinical and biochemical success, outperforming traditional logistic regression. Key determinants of success included serum aldosterone levels, CRP, and duration of hypertension, underscoring the role of both hormonal dysregulation and inflammatory burden in shaping therapeutic response. The presence of IL‐6, diabetes, and other comorbidities among the top predictors suggests that systemic factors also influence SAAE outcomes. These findings align with existing literature on the pathophysiology of idiopathic hyperaldosteronism and highlight the potential of predictive modeling to support individualized clinical decision‐making [40, 41]. Integration of such models into clinical workflows may assist in identifying optimal candidates for SAAE and enhancing long‐term management strategies. Further validation in independent cohorts is recommended. The incorporation of additional biomarkers, longitudinal follow‐up data, and external datasets may further improve model generalizability. Moreover, explainable AI techniques could enhance interpretability and clinician confidence in predictive outputs [42]. Ultimately, predictive analytics may serve as a valuable adjunct to traditional risk stratification methods in interventional endocrinology.
This cost‐effectiveness analysis demonstrates that SAAE not only offers clinical benefits but also provides economic advantages when compared with long‐term MRA therapy. Although the upfront procedural cost of SAAE is higher, the long‐term savings, resulting from better blood pressure control, fewer complications, and reduced healthcare utilization, offset this initial investment. The economic burden of lifelong pharmacologic therapy includes not only the drug costs but also downstream costs related to drug side effects, recurrent monitoring, and higher rates of cardiovascular events [43]. In contrast, SAAE, as a one‐time intervention, reduces the need for chronic therapy and stabilizes aldosterone levels, translating into improved patient outcomes and lower cumulative expenditure. These findings align with health economic trends favoring minimally invasive interventions that provide durable outcomes [44]. In addition to the primary cost‐effectiveness results, we performed sensitivity analyses to explore the robustness of our findings. Specifically, we tested several key assumptions, including variations in treatment costs, long‐term effectiveness of SAAE versus MRAs, and QALYs based on different patient age groups. These analyses help confirm the reliability of our results under varying cost and effectiveness scenarios, further supporting the cost‐effectiveness of SAAE in managing IHA. Incorporating SAAE into treatment algorithms for selected patients with idiopathic hyperaldosteronism may not only improve health outcomes but also reduce long‐term healthcare costs [13]. Future research should include multicenter economic modeling and real‐world cost tracking to validate these estimates.
Our study also highlights the need for refining procedural techniques to further reduce complications and improve outcomes. The use of advanced imaging techniques such as CXCR4 PET/CT scans could provide better insight into adrenal tissue activity and guide more precise embolization, potentially improving biochemical success rates [45]. Future research should focus on multicenter trials to validate these findings, as well as explore long‐term follow‐up data and optimization of patient selection through predictive modeling. Additionally, future studies should explore optimizing embolic agents and refining anesthesia and pain management protocols to minimize post‐procedural discomfort and enhance patient safety.
4.1. Limitations
There are many limitations to this study. The study was done at a single center with a limited sample size, which might potentially impact the data's generalizability. Furthermore, we did not measure the degree of pathological alterations or adrenal tissue loss, which restricts our comprehension of the exact consequences of the medication and how it works. The proficiency of the intervention team may also have an impact on the study's results. Specialists from a variety of areas made up our team, so outcomes may vary for teams with different degrees of expertise. Larger sample numbers and other multicenter trials are required to confirm these results and advance our knowledge of SAAE for bilateral IHA.
5. Conclusion
This study provides compelling evidence that bilateral SAAE is a safe and effective treatment for IHA, offering superior blood pressure control, biochemical normalization, and quality of life improvements compared to MRAs. The use of machine learning‐based predictive modeling offers additional value in identifying optimal candidates for this intervention. Furthermore, SAAE demonstrates cost‐effectiveness, making it an attractive alternative to long‐term pharmacologic management for selected patients. SAAE is particularly beneficial for patients with bilateral IHA who have not responded to MRAs and meet specific selection criteria. Future research should explore refining procedural techniques, expand patient selection criteria, and validate these findings in larger, multicenter cohorts to further support the clinical adoption of SAAE in managing bilateral IHA.
Author Contributions
Chang Jing and Xiang Rui contributed to the study design. Chang Jing, Xiang Rui, Mao Min, Feng Rui, and Zhao Yong Peng were responsible for performing adrenal vein sampling (AVS) and superselective adrenal arterial embolization (SAAE). Tao Li provided expertise in the administration of mineralocorticoid receptor antagonists (MRA) therapy. Pain management was handled by Tang Ping and Lv Feng Jie. Data collection was carried out by Chen Jie, Li Xin, Zhao Hong, Shi Qiuyue, Wang Ling, and He Yutian. Data analysis was conducted by Nouman Ali Khan and Muhammad Arif Asghar. Nouman Ali Khan and Chang Jing wrote and revised the manuscript.
Ethics Statement
Ethics reference number is 2022–146, which is approved by Ethics Committee of the First Affiliated Hospital of Chongqing Medical University (Phone +0086 023 89011876). This study was part of a trial registered with the Chinese Clinical Trial Registry (http://wwwchictr.org.cn). All participants gave their written informed consent to participate in this study.
Conflicts of Interest
There are no conflicts of interest related to the study design or its results.
Policy on Using ChatGPT and Similar AI Tools
We would like to acknowledge the use of AI tools, specifically Grammarly and ChatGPT, for assisting with language enhancement, grammar correction, and improving the overall clarity of the manuscript. These tools were utilized solely for manuscript presentation and did not contribute to the scientific content, data analysis, or result. The authors take full responsibility for the scientific integrity of the work and the interpretations presented.
Acknowledgments
Thanks to the new director of Cardiology Department, Russell, and the director of Cardiac Catheterization Laboratory, Ma Kanghua, for their strong support to the development and application of this technology. Thanks also to Dr. Pang Hua of nuclear medicine, Dr. Kang Hua Ma, director of Cardiac Catheterization and Dr. Lily Guan and Dr. Jing Chen for their support in the radionuclide adrenal gland examination. Thanks to Director Lufa Jin and Dr. Wang Guoshu of the Radiology Department for their support and assistance in adrenal gland MRA and accurate positioning of adrenal arteries by intraoperative imaging.
Funding: This study was supported by Chongqing Science Committee for funding of the General Project, Grant/Award Number:csts2020jcyj‐msxmX0853. The National Key Specialized Project funded by the Ministry of Finance and Ministry of Health of the People's Republic of China, Grant/Award Number: 2011–170.
Nouman Ali Khan and Min Mao contributed equally to this study.
Contributor Information
Jing Chang, Email: 1584105002@qq.com.
Rui Xiang, Email: 10180788@qq.cn.
Data Availability Statement
There are ethical restrictions on sharing of de‐identified data for this study. The ethics committee has not agreed to the public sharing of data, as we do not have the participants’ permission to share their anonymous data. Further, the dataset includes sensitive injury cases and descriptions of the mechanism of injury. It is likely, given the nature of the dataset, that patients may still be identifiable despite efforts to anonymize the data. Qualified and interested researchers may request access to the data by contacting corresponding author Professor Chang Jing (Phone: +0086 023 89011513, Email: 1584105002@qq.com).
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Associated Data
This section collects any data citations, data availability statements, or supplementary materials included in this article.
Data Availability Statement
There are ethical restrictions on sharing of de‐identified data for this study. The ethics committee has not agreed to the public sharing of data, as we do not have the participants’ permission to share their anonymous data. Further, the dataset includes sensitive injury cases and descriptions of the mechanism of injury. It is likely, given the nature of the dataset, that patients may still be identifiable despite efforts to anonymize the data. Qualified and interested researchers may request access to the data by contacting corresponding author Professor Chang Jing (Phone: +0086 023 89011513, Email: 1584105002@qq.com).