Prognosis of adrenalectomy guided by computed tomography versus adrenal vein sampling in patients with primary aldosteronism: A systematic review and meta‐analysis
Bibliographic record
Abstract
Adrenal vein sampling (AVS) is recommended to be the gold standard for patients with unilateral subtypes of primary aldosteronism to clinical diagnosis and surgery therapy. However, it is uncertain whether AVS is better for prognosis than computed tomography (CT), which is the most widely used. Pubmed, Embase, and Cochrane Library were searched for articles with no start date restriction. The last search was conducted on Jun 15, 2021. Eligible studies compared the distinct subtypes of primary aldosteronism by AVS with CT (as a control group) and reported the prognosis at follow-up. Evaluation of cohort studies referred to Newcastle - Ottawa Quality Assessment Scale, and randomized controlled trials referred to Updated Cochrane Collaboration tool. A random-effect model or fixed-effect model was chosen according to the heterogeneity test. All processes were performed following the PRISMA 2020 statement. Eleven studies were identified, including 1325 patients based on AVS and 907 patients based on CT. Compared with patients guided by CT, patients who underwent AVS had an increased possibility of complete biochemical success (odds ratio [OR] 2.78, 95% CI 1.88-4.12) and a decreased chance of absent biochemical success (OR 0.23, 95% CI 0.13-0.40) at follow-up. Nevertheless, the rate of complete clinical success (OR 1.09, 95% CI 0.89-1.35) and absent clinical success (OR 0.96, 95% CI 0.68-1.33) had no significant difference. Therefore, distinguishing subtypes by AVS for early treatment may be crucial since it can promote biochemical improvement.
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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 | 0.009 | 0.025 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.017 | 0.034 |
| Bibliometrics | 0.005 | 0.006 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.002 | 0.001 |
| 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".