New Cutoffs for the Biochemical Diagnosis of Adrenal Insufficiency after ACTH Stimulation using Specific Cortisol Assays
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Bibliographic record
Abstract
CONTEXT: ) is considered to be ≥18 μg/dL (500 nmol/L). This threshold is based on older serum cortisol assays. Specific monoclonal antibody immunoassays or LC-MS/MS may have lower thresholds for a normal response. OBJECTIVE: To calculate serum cortisol cutoff values for adrenocorticotropic hormone (ACTH) stimulation testing with newer specific cortisol assays. METHODS: Retrospective analysis of ACTH stimulation tests performed in ambulatory and hospitalized patients suspected of adrenal insufficiency (AI). Serum samples were assayed for cortisol in parallel using Elecsys I and Elecsys II immunoassays, and when volume was available, by Access immunoassay and LC-MS/MS. RESULTS: A total of 110 patients were evaluated. Using 18 μg/dL as the cortisol cutoff after ACTH stimulation, 14.5%, 29%, 22.4%, and 32% of patients had a biochemical diagnosis of AI using the Elecsys I, Elecsys II, Access, and LC-MS/MS assays, respectively. Deming regressions of serum cortisol were used to calculate new cortisol cutoffs based on the Elecsys I cutoff of 18 μg/dL. For 30-minute values, new cutoffs were 14.6 μg/dL for Elecsys II, 14.8 μg/dL for Access, and 14.5 μg/dL for LC-MS/MS. Baseline cortisol <2 μg/dL was predictive of subnormal stimulated cortisol values. CONCLUSION: To reduce false positive ACTH stimulation testing, we recommend a new serum cortisol cutoff of 14 to 15 μg/dL depending on the assay used (instead of the historical value of 18 μg/dL with older polyclonal antibody assays). Clinicians should be aware of the new cutoffs for the assays available to them when evaluating patients for AI.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| 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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it