Bibliographic record
Abstract
Abdominal x-ray series (AXR) and abdominal CT scans (ACT) are commonly performed to aid in the diagnosis for patients who present to the emergency room with abdominal pain. Patients commonly receive both an AXR and ACT, due to a lack of knowledge regarding imaging appropriateness among healthcare professionals who order these exams. A primary simple retrospective data-analysis was performed to understand the prevalence of how often both exams were ordered in three Nova Scotia emergency departments. A literature review was also conducted to compare the diagnostic accuracy of each diagnostic imaging modality. Several articles showed that patients who have an AXR also have an ACT that demonstrates an abnormal finding. Emergency department physicians are not reassured when abdominal x-rays are negative and do not show abnormal findings, and as a result, a CT scan is also performed. Radiation dose must be considered when ordering multiple diagnostic imaging exams. A low-dose CT (LDCT) can be used to reduce the radiation exposure to the patient, while maintaining high diagnostic quality images. Image quality can be enhanced at a reduced radiation dose by using an image reconstruction technique such as adaptive statistical iterative reconstruction (ASIR). Understanding the most appropriate abdominal imaging modality for emergency department patients allows for fewer examinations being ordered and a reduction of radiation dose to the patient. When the most appropriate imaging is performed, a definitive diagnosis can be made and the best treatment can be provided to patients. This information can help to create an imaging appropriateness protocol for emergency departments.Additional research can help determine the cost differences between the two exams and the influence a protocol change could have on the emergency and diagnostic imaging departments.Keywords: AXR – Abdominal x-ray series, ACT – Abdominal computed tomography scan, CT – Computed tomography, SDCT – Standard-dose CT, LDCT – Low-dose CT, ASIR – Adaptative statistical iterative reconstruction FBP – Filtered back projection, CTDIvol – Volume computed tomography dose index
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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 | 0.000 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 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".