MON-136 Reducing Unnecessary Inpatient Adrenocorticotropin Stimulation Tests
Bibliographic record
Abstract
Abstract Background: Outpatient adrenocorticotropin (ACTH) stimulation tests can be challenging to interpret due to heterogeneously reported cut-offs. Inpatient stimulation tests present additional challenges due to the presence of acute illness and unreliable coordination of dynamic function testing on a busy inpatient service. This study aims to characterize the use of ACTH stimulation tests in hospitalized patients to determine necessity of testing. Methods: We conducted an inpatient audit of ACTH simulation tests done to rule out adrenal insufficiency between April 2018 to March 2019 at our institution. Normal post-ACTH response was defined as peak cortisol ≥500 nmol/L. Testing was considered inappropriate in patients with normal post-ACTH response who had a serum cortisol ≥250 nmol/L drawn during the same admission prior to stimulation testing. Cut-offs were based on previous analysis of 195 outpatient stimulation tests. Results: During the one-year study period there were 40 inpatients who had an ACTH stimulation test. Nineteen (48%) were considered unnecessary because patients either had a pre-ACTH serum cortisol ≥250 nmol/L and/or a 0-minute cortisol value just prior to the ACTH stimulation test ≥250 nmol/L. Except for a single instance where the patient was inappropriately on prednisone when basal cortisol was tested, all patients with any pre-ACTH cortisol ≥250 nmol/L had a normal post-ACTH response Conclusion: Institutions may avoid unnecessary inpatient ACTH stimulation tests by implementing protocols which ensure that basal cortisol levels are drawn and below locally determined cut-offs before proceeding to dynamic testing. To characterize further, a three-year analysis of inpatient ACTH stimulation tests is underway.
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 | 0.002 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 0.002 |
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".