Screening Rates for Primary Aldosteronism Among Individuals With Hypertension Plus Hypokalemia: A Population-Based Retrospective Cohort Study
Bibliographic record
Abstract
Primary aldosteronism is a common, yet highly underdiagnosed, cause of hypertension that leads to disproportionately high rates of cardiovascular disease. Hypertension plus hypokalemia is a guideline-recommended indication to screen for primary aldosteronism, yet the uptake of this recommendation at the population level remains unknown. We performed a population-based retrospective cohort study of adults ≥18 years old in Ontario, Canada, with hypertension plus hypokalemia (potassium <3.5 mEq/L) from 2009 to 2015 with follow-up through 2017. We measured the proportion of individuals who underwent primary aldosteronism screening via the aldosterone-to-renin ratio based upon hypokalemia frequency and severity along with concurrent antihypertensive medication use. We assessed clinical predictors associated with screening via Cox regression. The cohort included 26 533 adults of which only 422 (1.6%) underwent primary aldosteronism screening. When assessed by number of instances of hypokalemia over a 2-year time window, the proportion of eligible patients who were screened increased only modestly from 1.0% (158/15 983) with one instance to 4.8% (71/1494) with ≥5 instances. Among individuals with severe hypokalemia (potassium <3.0 mEq/L), only 3.9% (58/1422) were screened. Among older adults prescribed ≥4 antihypertensive medications, only 1.0% were screened. Subspecialty care with endocrinology (hazard ratio [HR], 1.52 [95% CI, 1.10-2.09]), nephrology (HR, 1.43 [95% CI, 1.07-1.91]), and cardiology (HR, 1.39 [95% CI, 1.14-1.70]) were associated with an increased likelihood of screening, whereas age (HR, 0.95 [95% CI, 0.94-0.96]) and diabetes (HR, 0.66 [95% CI, 0.50-0.89]) were inversely associated with screening. In conclusion, population-level uptake of guideline recommendations for primary aldosteronism screening is exceedingly low. Increased education and awareness are critical to bridge this gap.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".