Primary aldosteronism: pharmacotherapy vs surgery vs embolization efficacy – systematic review and network meta-analysis of studies predominantly conducted in China
Bibliographic record
Abstract
Background: Primary aldosteronism (PA) is one of major cause of resistant hypertension. This study compares the efficacy and safety of current treatments, including pharmacotherapy, adrenalectomy, and minimally invasive techniques, to guide clinical practice. Method: We systematically searched Embase, PubMed, Cochrane, Web of Science, CNKI, Wanfang, and VIP from inception to August 13, 2024, for randomized controlled trials and cohort studies involving adult patients with PA and hypertension. Reporting quality of the included studies was assessed using the Cochrane Risk of Bias 2 tool for RCTs and the Newcastle-Ottawa Scale (NOS) for cohort studies. Data analysis was performed using R 4.3.3 and STATA 15.0. Results: This study included 17 articles involving 1,496 patients, of which 13 studies (76%) were conducted in China. Meta-analysis showed that for systolic blood pressure (SBP), unilateral total adrenalectomy and renal nerve denervation (TADR+RND) was most effective (WMD = -12.53, 95% Crl -15.18 to -9.90). For diastolic blood pressure (DBP), Partial adrenalectomy (PADR) (WMD = -9.31, 95% Crl -12.97 to -5.68). PADR also maintained serum potassium levels effectively (0.64, 95% Crl 0.52 to 0.75). Among pharmacological treatments, mineralocorticoid receptor antagonists and irbesartan (MRAs+IRB) had the greatest antihypertensive effect (SBP: WMD = -18.90, 95% Crl -29.20 to -8.55; DBP: WMD = -22.14, 95% Crl -31.81 to -12.50). Mineralocorticoid receptor antagonists did not significantly reduce plasma aldosterone concentration (PAC), consistent with their known feedback-related tendency to increase PAC. Conclusions: This study showed TADR + RND and MRAs + IRB had best efficacy in surgical and pharmacological treatments, respectively, but 76% of the included studies were conducted in China, which may affect the generalizability of the findings. Therefore, the results need further validation.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.019 | 0.039 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.022 | 0.043 |
| Bibliometrics | 0.007 | 0.008 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".