Is It Relevant to Screen Subclinical Cushing’s Syndrome in Patients With Type 2 Diabetes Mellitus?
Bibliographic record
Abstract
Background: Subclinical Cushing’s syndrome (SCS) is defined as autonomous cortisol secretion in patients devoid of specific clinical symptoms of hypercortisolism, as in the classic CS. However, sustained exposure to chronic slightly elevated cortisol concentrations may result in some classical metabolic complications of CS such as impaired glucose tolerance and diabetes. Currently, the frequency of SCS is widely variable. We have conducted a cross-sectional study to prospectively evaluate the prevalence of SCS among type 2 diabetic (T2D) patients with poor control, and to determine whether systematic screening for SCS in T2D patients is worthwhile. Methods: It was a cross-sectional study including 221 T2D patients referred to the National Institute of Nutrition of Tunis for poor glycemic control (HbA1c >= 8%). The first screening step of SCS was the 1-mg overnight dexamethasone suppression test (ODST) using a revised criterion for cortisol suppression. In the second confirmatory step, patients with abnormal ODST underwent a 48-h, 2-mg low-dose dexamethasone suppression test (LDDST) to confirm the diagnosis. The cut-off for cortisol suppression was 50 nmol/L (1.8 µmol/dL) in the two tests. Results: Thirteen patients (5.9%) failed to suppress cortisol levels less than the cut-off after ODST. SCS was confirmed by LDDST in one patient among them (0.45%). The autonomous cortisol secretion was related to a pituitary adenoma. Our study revealed that the frequency of SCS of 0.45% did not allow performing an analytical study in order to identify predictive factors of SCS among T2D patients. Conclusion: SCS is rare among T2D patients. Systematic screening of SCS in T2D patients with poor glycemic control is not worthwhile. The screening should be performed only in patients with a particular clinical and/or biological context. J Endocrinol Metab. 2017;7(6):178-184 doi: https://doi.org/10.14740/jem454w
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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 | 0.002 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.002 | 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".