Sensitivity and Specificity of Ultrasonography in Early Diagnosis of Metatarsal Bone Stress Fractures: A Pilot Study of 37 Patients
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Bibliographic record
Abstract
OBJECTIVE: To date, early diagnosis of stress fractures depends on magnetic resonance imaging (MRI) or bone scan scintigraphy, as radiographs are usually normal at onset of symptoms. These examinations are expensive or invasive, time-consuming, and poorly accessible. A recent report has shown the ability of ultrasonography (US) to detect early stress fractures. Our objective was to evaluate sensitivity and specificity of US versus dedicated MRI (0.2 Tesla), taken as the gold standard, in early diagnosis of metatarsal bone stress fractures. METHODS: A case-control study from November 2006 to December 2007 was performed. All consecutive patients with mechanical pain and swelling of the metatarsal region for less than 3 months and with normal radiographs were included. US and dedicated MRI examinations of the metatarsal bones were performed the same day by experienced rheumatologists with expertise in US and MRI. Reading was undertaken blind to the clinical assessment and MRI/US results. RESULTS: Forty-one feet were analyzed on US and dedicated MRI from 37 patients (28 women, 9 men, mean age 52.7 +/- 14.1 yrs). MRI detected 13 fractures in 12 patients. Sensitivity of US was 83%, specificity 76%, positive predictive value 59%, and negative predictive value 92%. Positive likehood ratio was 3.45, negative likehood ratio 0.22. CONCLUSION: In cases of normal radiographs, US is indicated in the diagnosis of metatarsal bone stress fractures, as it is a low cost, noninvasive, rapid, and easy technique with good sensitivity and specificity. From these data, we propose a new imaging algorithm including US.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 it