Does This Patient With Diabetes Have Osteomyelitis of the Lower Extremity?
Bibliographic record
Abstract
CONTEXT: Osteomyelitis of the lower extremity is a commonly encountered problem in patients with diabetes and is an important cause of amputation and admission to the hospital. The diagnosis of lower limb osteomyelitis in patients with diabetes remains a challenge. OBJECTIVE: To determine the accuracy of historical features, physical examination, and laboratory and basic radiographic testing. We searched for systematic reviews of magnetic resonance imaging (MRI) in the diagnosis of lower extremity osteomyelitis in patients with diabetes to compare its performance with the reference standard. DATA SOURCES: MEDLINE search of English-language articles published between 1966 and March 2007 related to osteomyelitis in patients with diabetes. Additional articles were identified through a hand search of references from retrieved articles, previous reviews, and polling experts. STUDY SELECTION: Original studies were selected if they (1) described historical features, physical examination, laboratory investigations, or plain radiograph in the diagnosis of lower extremity osteomyelitis in patients with diabetes mellitus, (2) data could be extracted to construct 2 x 2 tables or had reported operating characteristics of the diagnostic measure, and (3) the diagnostic test was compared with a reference standard. Of 279 articles retrieved, 21 form the basis of this review. Data from a single high-quality meta-analysis were used to summarize the diagnostic characteristics of MRI in osteomyelitis. DATA EXTRACTION: Two authors independently assigned each study a quality grade using previously published criteria and abstracted operating characteristic data using a standardized instrument. DATA SYNTHESIS: The gold standard for diagnosis is bone biopsy. No studies were identified that addressed the utility of the history in the diagnosis of osteomyelitis. An ulcer area larger than 2 cm2 (positive likelihood ratio [LR], 7.2; 95% confidence interval [CI], 1.1-49; negative LR, 0.48; 95% CI, 0.31-0.76) and a positive "probe-to-bone" test result (summary positive LR, 6.4; 95% CI, 3.6-11; negative LR, 0.39; 95% CI, 0.20-0.76) were the best clinical findings. A erythrocyte sedimentation rate of more than 70 mm/h increases the probability of a diagnosis of osteomyelitis (summary LR, 11; 95% CI, 1.6-79). An abnormal plain radiograph doubles the odds of osteomyelitis (summary LR, 2.3; 95% CI, 1.6-3.3). A positive MRI result increases the likelihood of osteomyelitis (summary LR, 3.8; 95% CI, 2.5-5.8). However, a normal MRI result makes osteomyelitis much less likely (summary LR, 0.14; 95% CI, 0.08-0.26). The overall accuracy (ie, the weighted average of the sensitivity and specificity) of the MRI is 89% (95% CI, 83.0%-94.5%). CONCLUSIONS: An ulcer area larger than 2 cm2, a positive probe-to-bone test result, an erythrocyte sedimentation rate of more than 70 mm/h, and an abnormal plain radiograph result are helpful in diagnosing the presence of lower extremity osteomyelitis in patients with diabetes. A negative MRI result makes the diagnosis much less likely when all of these findings are absent. No single historical feature or physical examination reliably excludes osteomyelitis. The diagnostic utility of a combination of findings is unknown.
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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) | 0.001 | 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 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".