What do we really know about the appropriateness of radiation emitting imaging for low back pain in primary and emergency care? A systematic review and meta-analysis of medical record reviews
Bibliographic record
Abstract
BACKGROUND: Since 2000, guidelines have been consistent in recommending when diagnostic imaging for low back pain should be obtained to ensure patient safety and reduce unnecessary tests. This systematic review and meta-analysis was conducted to determine the pooled proportion of CT and x-ray imaging of the lumbar spine that were considered appropriate in primary and emergency care. METHODS: Pubmed, CINAHL, The Cochrane Database of Systematic Reviews and Embase were searched for synonyms of "low back pain", "guidelines", and "adherence" that were published after 2000. Titles, abstracts, and full texts were reviewed for inclusion with forward and backward tracking on included studies. Included studies had data extracted and synthesized. Risk of bias was performed on all studies, and GRADE was performed on included studies that provided data on CT and x-ray separately. A random effect, single proportion meta-analysis model was used. RESULTS: Six studies were included in the descriptive synthesis, and 5 studies included in the meta-analysis. Five of the 6 studies assessed appropriateness of x-rays; two of the six studies assessed appropriateness of CTs. The pooled estimate for appropriateness of x-rays was 43% (95% CI: 30%, 56%) and the pooled estimate for appropriateness of CTs was 54% (95% CI: 51%, 58%). Studies did not report adequate information to fulfill the RECORD checklist (reporting guidelines for research using observational data). Risk of bias was high in 4 studies, moderate in one, and low in one. GRADE for x-ray appropriateness was low-quality and for CT appropriateness was very-low-quality. CONCLUSION: While this study determined a pooled proportion of appropriateness for both x-ray and CT imaging for low back pain, there is limited confidence in these numbers due to the downgrading of the evidence using GRADE. Further research on this topic is needed to inform our understanding of x-ray and CT appropriateness in order to improve healthcare systems and decrease patient harms.
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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 | 0.097 | 0.270 |
| Meta-epidemiology (narrow) | 0.003 | 0.003 |
| Meta-epidemiology (broad) | 0.034 | 0.051 |
| Bibliometrics | 0.015 | 0.014 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.008 | 0.007 |
| Open science | 0.004 | 0.003 |
| Research integrity | 0.004 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 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".