OPTimal IMAging strategy in patients suspected of non-traumatic pulmonary disease at the emergency department: chest X-ray or ultra-low-dose CT (OPTIMACT)—a randomised controlled trial chest X-ray or ultra-low-dose CT at the ED: design and rationale
Bibliographic record
Abstract
BACKGROUND: Chest X-ray has been the standard imaging method for patients suspected of non-traumatic pulmonary disease at the emergency department (ED) for years. Recently, ultra-low-dose chest computed tomography (ULD chest CT) has been introduced, which provides substantially more detailed information on pulmonary conditions that may cause pulmonary disease, with a dose in the order of chest X-ray (0.1 vs. 0.05 mSv). The OPTimal IMAging strategy in patients suspected of non-traumatic pulmonary disease at the emergency department: chest X-ray or CT (OPTIMACT) study is a randomized trial designed to evaluate the effectiveness of replacing chest X-ray for ULD chest CT in the diagnostic work-up of patients suspected of non-traumatic pulmonary disease at the ED. METHODS: Two thousand four hundred patients presenting at the ED with pulmonary complaints and suspected of non-traumatic pulmonary disease will be enrolled in this multicenter, pragmatic, randomized trial. During randomly assigned periods of one calendar month, either conventional chest X-ray or ULD chest CT scan will be used as the imaging strategy. Randomization will rely on computer-generated blocks of 2 months to control for seasonal effects. Chest X-ray and ULD chest CT will be performed in a standardized way, after obtaining the clinical history and performing physical examination and initial laboratory tests. The primary outcome measure is functional health at 28 days. Secondary outcome measures are mental health, length of hospital stay, mortality within 28 days, quality-adjusted life years (QALYs) during the first 28 days, correct diagnoses at ED discharge as compared to the final post hoc diagnosis, and number of patients in follow-up because of incidental findings on chest X-ray or ULD chest CT. In an economic evaluation, we will estimate total health care costs during the first 28 days. DISCUSSION: This pragmatic trial will clarify the effects of replacing chest X-ray by ULD chest CT in daily practice, in terms of patient-related health outcomes and costs, in the diagnostic work-up of patients suspected of non-traumatic pulmonary disease at the ED. TRIAL REGISTRATION: The OPTIMACT trial is registered in the Netherlands National Trial Register under number NTR6163. The date of registration is December 6, 2016.
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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 | 0.010 |
| Meta-epidemiology (narrow) | 0.004 | 0.002 |
| Meta-epidemiology (broad) | 0.008 | 0.004 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.006 | 0.004 |
| Insufficient payload (model declined to judge) | 0.009 | 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".