Imaging use for uncomplicated low back pain by emergency physicians according to the Smarter Medicine recommendations
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Background Low back pain (LBP) is one of the most common causes for emergency department’s (ED) consultation. Usually, LBP is non-specific and associations such as Choosing Wisely Canada (CWC) Emergency Medicine group or Smarter Medicine Switzerland recommend avoidance of lumbosacral imaging for patients with non-traumatic LBP in the absence of red flags. The objective of this study was to determine the adherence to this recommendation in the emergency department of Lausanne University Hospital, Switzerland. The second objective was to determine the factors that may influence the decision to order imaging. Methods We conducted a retrospective observational study over a 1-year period between January 1st and December 31st 2019. All data were collected from patients who presented themselves to the emergency department of Lausanne University Hospital with non-complicated LBP. Patients with red flags and/or who were admitted to the hospital were excluded from the analysis. Results Among a total of 756 eligible patients, 372 were included. Imaging was ordered in 64 (17.20%) of them, including 55 lumbar X-ray, 5 CT-scan and 4 MRI. None of these imaging lead to diagnostic a cause of LBP. Age was the only variable positively associated with imaging (p = .001). There was no statistical difference in the other variables analyzed between these two groups. Conclusions In overall, Choosing Wisely recommendation seems to be respected by the emergency physicians of Lausanne University Hospital although there is a trend toward performing more imaging for older patients.
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.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 it