Primary Aldosteronism in CKD Increases CV Risk and Death Independent of Adrenalectomy vs. Medical Management
Bibliographic record
Abstract
Background: Primary aldosteronism (PA) is common and is associated with increased cardiovascular (CV) risk. Diagnosis and treatment of PA in CKD is often deferred for safety and efficacy concerns. Aim was to assess clinical outcomes in patients with confirmed PA and underlying CKD. Methods: We conducted a retrospective cohort study of patients with biochemical PA and eGFR < 60 cc/min/1.73m2 from 3 academic medical centers, who underwent adrenal vein sampling (AVS) between 2009-2019. Primary outcomes were BP control and number of antihypertensive medications (AHM). Secondary outcomes included CV and renal clinical events and all-cause mortality. Results: Of 239 patients, 159 lateralized on AVS (67%); 158 (66 %) underwent adrenalectomy and 81 (34%) were treated medically. Mean (SD) age was 57 (10) years, 33% were female with mean BMI of 33 (6) kg/m2. At baseline 1/3 had DM and CVD with mean serum values: K 3.9 (0.6) mmol/L, creatinine 1.9 (4.5) mg/dL and eGFR (2021 CKD-EPI without race) 54 (21) mL/min; 49% of subjects were on K supplements with 47% receiving K sparing diuretics. Subjects were followed for a median of 4.5 years. At 5 years mean BP decreased from 149/85 to 131/78 mm Hg and serum K increased from 3.9 to 4.2 mmol/L. Subjects who underwent adrenalectomy vs. medical management (MM) had 3.5 mm Hg lower SBP (p = 0.022) and required 1.8 fewer AHM at 5 years (p < 0.001). Every SD higher baseline eGFR (˜20 mL/min/1.73m2) was associated with a 2 mm Hg lower SBP and reduced AHM requirement. Clinical event rates were high: MI 12(5%), TIA 11(5%), CHF 14(6%), Afib 21 (9%), dialysis 15(6%), death 23(10%). Using Cox models baseline non race-based eGFR was significantly associated with an increase in RRT and death even after adjustment for age, sex, CKD and DM (Table). No difference in clinical outcomes was detected if patients had adrenalectomy vs MM. Conclusions: PA patient with CKD have a high risk for incident CV events, progression to RRT and death. PA patients with higher baseline eGFR had greater reductions in BP and AHM and are more likely to respond favorably to PA therapy, regardless if treated with adrenalectomy or MM.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".