CT Abdominal Tomography Indications: Are We All Sticking to the Plan?
Bibliographic record
Abstract
OBJECTIVE: Ultra-low radiation dose computed tomography (CT) abdominal tomography was introduced in our institution in 2016 to replace standard abdominal radiography in the investigation of emergency department patients. This project aims to ascertain whether investigation of emergency department patients using ultra-low radiation dose CT abdominal tomography complies with original indication guidelines and/or if there has been any "indication creep" 3 years after inception. METHODS: Retrospective, quality assurance project with research ethics waiver. A review of 200 consecutive patients investigated with CT abdominal tomography between February and May 2017 was performed. This was compared with 200 consecutive patients investigated between February and May 2019. Data analyzed included patient demographics, indication for scan, as well as scan and patient outcomes. RESULTS: < .05) regarding the use of approved indications. Forty of 200 scans performed in 2017 revealed additional findings which are not specifically addressed on the reporting template. Forty-one of 200 scans in 2019 revealed these findings. CONCLUSIONS: There has been no "indication creep" for CT abdominal tomography over time.
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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 | 0.008 | 0.062 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".