Incidental Vertebral Fractures Discovered With Chest Radiography in the Emergency Department
Bibliographic record
Abstract
BACKGROUND: Vertebral fractures are common and usually an indication for osteoporosis treatment. However, screening is not recommended, and many fractures go undetected. Our objectives were to determine the utility of chest radiographs for detecting previously unrecognized vertebral fractures; document rates of recognition; and evaluate osteoporosis treatments. METHODS: In 2001, we conducted a cohort study in a random sample of 500 patients older than 60 years who presented to our emergency department and underwent chest radiography for any indication. The primary outcome was prevalence of moderate-to-severe vertebral fractures determined by independent radiograph review using validated semiquantitative techniques. Secondary outcomes were rates of fracture recognition according to official radiologists' reports and rates of osteoporosis diagnosis and treatment. We conducted multivariable regression analyses to determine correlates of study-defined and officially reported fractures. RESULTS: We excluded 36 patients with inadequate radiographs and 5 for other reasons. Mean age was 75.2 years; 47% were women; and 80% were white. The prevalence of moderate-to-severe vertebral fractures according to independent review was 72 (16%) of 459; 29 (40%) of these fractures were not recorded in the official radiologists' report (kappa = 0.64; 95% confidence interval [CI], 0.53-0.75). A history of osteoporosis was the only independent correlate of having a vertebral fracture identified by independent review (adjusted odds ratio [OR], 2.18; 95% CI, 1.14-4.17) or by official report (adjusted OR, 4.97; 95% CI, 0.95-25.86). Of the 72 patients with fractures, only 18 (25%) had histories of osteoporosis or received osteoporosis medications. CONCLUSIONS: One in 6 elderly patients who underwent chest radiography in our emergency department had clinically important vertebral fractures. Nevertheless, only 43 (60%) of these fractures were reported, and only 25% of patients with fractures received a diagnosis of or treatment for osteoporosis.
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.
How this classification was reachedexpand
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) | 0.000 | 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 teacher head, 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".