Big data determination and validation of reference range for 24 hour urine cortisol by LCMS/MS
Bibliographic record
Abstract
OBJECTIVE: Twenty-four-hour urine-free cortisol (UFC) is a first-line test for Cushing syndrome (CS). A new mass spectrometry assay for UFC requires a validated, relevant reference range appropriate to a screening population. DESIGN: Combined retrospective and prospective cohort study in a government health system and tertiary endocrinology clinic, Canada. Participants were patients with potential features of CS. METHODS: The refineR reference interval algorithm was used to derive a middle 95%ile reference interval from 4830 UFC results in non-CS patients, compared with 120 prospective patients where evaluation excluded CS. RESULTS: Urine-free cortisol and 24-h urine volume were correlated (r = 0.28, P < .0001). There was no significant difference between the volume-corrected UFC distributions in the prospective vs retrospective populations (P = .09). Urine-free cortisol distribution was highly skewed (P < .0001) and showed strong sex interaction. The refineR-generated adult male UFC upper reference limit was 238 nmol/day (86.3 μg/day) and for females was 147 nmol/day (53.3 μg/day); urine volume-corrected, the upper limits were 89 nmol/L (32.3 μg/L) and 91 nmol/L (32.9 μg/L), respectively. Applied to both populations, between 3% and 8% of all results would be flagged high; most are expected to represent nonneoplastic (pseudo)Cushing's. CONCLUSIONS: We used mass population data, where the prevalence of CS was likely very rare, plus a carefully phenotyped sample where CS was considered but excluded, to derive a validated reference interval for 24-h UFC by mass spectrometry in populations that reflect real-world use of the test. Given the highly skewed upper tail of the population distribution, it is probable that high test specificity for CS will require multimodality diagnostic confirmation.
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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 | 0.025 | 0.027 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".