The Effect of Crystal Arthropathy on the Diagnostic Criteria of Native Septic Arthritis
Bibliographic record
Abstract
INTRODUCTION: Distinguishing between septic arthritis and crystal arthropathy flares can be challenging. The purpose of this study was to determine how the presence of synovial crystals affects the diagnostic criteria of septic arthritis. METHODS: A retrospective review identified patients undergoing joint aspirations to rule out native septic arthritis. Differences between septic arthritis presenting with and without synovial crystals were analyzed. A receiver-operating characteristic curve was plotted for laboratory markers to determine the area under the curve, or diagnostic accuracy, for septic arthritis and to evaluate thresholds that maximized sensitivity and specificity. RESULTS: There were 302 joint aspirations in 267 patients. Septic arthritis was diagnosed in 17.9% (54/302). Patients with synovial crystals were less likely to have septic arthritis (4.2% [5/119] vs. 26.8% [49/183], P < 0.0001). Septic arthritis in patients with no synovial crystals was associated with fever and a higher synovial white blood cell (WBC) count, synovial polymorphonuclear cell percentage (PMN%), serum WBC, and C-reactive protein (CRP) ( P < 0.05). Septic arthritis in patients with synovial crystals was only associated with inability to bear weight and a higher synovial WBC and CRP ( P < 0.05). Synovial PMN% was considered nondiagnostic of septic arthritis (area under the curve 0.56) in patients with crystals while synovial WBC and CRP had acceptable (0.76) and excellent (0.83) diagnostic utility, respectively. The WBC and CRP value thresholds that maximized sensitivity and specificity for septic arthritis were greater in patients with crystals (21,600 vs. 17,954 cells/μL and 125 vs. 69 mg/L, respectively). DISCUSSION: The presence of synovial crystals reduced the likelihood of septic arthritis and altered the laboratory diagnostic criteria. PMN% was nondiagnostic in the setting of synovial crystals.
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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 | 0.018 | 0.093 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".