Late‐night salivary cortisol for diagnosis of Cushing’s syndrome by liquid chromatography/tandem mass spectrometry assay
Bibliographic record
Abstract
BACKGROUND: Late-night salivary cortisol (LNSC) measurements have been increasingly used by physicians as an initial diagnostic test for evaluation of patients with clinical suspicion of Cushing's syndrome (CS). Published studies include various numbers of cases, controls and importantly, various assay methods (vast majority various immunoassays), as well as various methods to generate cut-points. MATERIALS AND METHODS: The retrospective study evaluated the diagnostic utility of LNSC measurements in 249 patients evaluated for possibility of CS because of various clinical conditions using liquid chromatography/tandem mass spectrometry method (LC-MS/MS). CS was confirmed in 47 patients (18·9%) and excluded in 202 (81·1%) patients at the time of analysis. RESULTS: Late-night salivary cortisol was abnormal or >2·8 nmol/l in 35 of 47 patients with CS; sensitivity of 74·5% and elevated in 20 of 202 patients who were found not to have CS; specificity 90·1%. Using receiver-operator characteristic statistics for calculation of the most optimal sensitivity and specificity, the cut-off based on this data was LNSC > 2·1 nmol/l with sensitivity of 83·0% and specificity of 84·2%. CONCLUSION: Analysis of data at one referral institution showed somewhat limited sensitivity of LNSC for diagnosis of CS using current reference ranges.
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 | 0.003 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| 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) | 0.001 | 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".