Survey of renin and aldosterone testing practices by Ontario laboratories – Providing insight into best practices
Bibliographic record
Abstract
OBJECTIVES: Testing for renin and aldosterone in clinical laboratories is complicated by pre-analytical considerations such as the posture for blood collection and susceptibility to cryoactivation of renin. From an analytical perspective, there are both renin activity and renin mass or concentration assays available. There can also be variability in result reporting practices and the aldosterone-renin ratio (ARR) cut-off applied to screen for primary aldosteronism (PA). The Institute for Quality Management in Healthcare (IQMH) Centre for Proficiency Testing surveyed laboratories on their handling of renin and aldosterone testing to better understand current practices. DESIGN AND METHODS: An online survey was prepared and sent to 134 Canadian laboratories enrolled in endocrinology proficiency testing with IQMH. RESULTS: One hundred twenty Ontario laboratories submitted responses. While only six (5%) laboratories perform testing for both renin and aldosterone, 108 (90%) collect and process specimens to be tested by reference laboratories. The survey revealed considerable variation in practices including the recommended state of patients prior to sample collection (for example, regarding medications or salt intake), the patient posture specifications for sample collection, the precautions taken against cryoactivation of renin, the choice of renin activity or mass assay, and the ARR cut-off used. The available literature on these factors was then reviewed. CONCLUSIONS: Although there is no standardized procedure for specimen collection, analysis, or result reporting for renin or aldosterone testing, we have attempted to summarize the available literature to develop evidence-based recommendations. Where laboratory practice differs from peers and/or recommended protocols, laboratories should review their practices.
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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 | 0.008 | 0.028 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.006 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".