Bibliographic record
Abstract
A 48-year-old woman receiving hemodialysis via arterial-venous fistula presented with right gluteal region pain and fever. Initially, antibiotics were prescribed but her fever did not subside. Computed tomography (CT) pelvic images displayed low attenuation lesions on the right pyriformis muscle (Fig. 1, panel A) and psoas muscle (Fig. 1, panel B). Muscle abscess was suspected. The surgeon and radiologist suggested a CT-guided percutaneous drainage for pyriformis muscle and antibiotics. The drainage yielded a large amount of pus fluid. Three days later, the patient’s lower back pain and fever had not subsided. A second pelvic CT was done, which disclosed an enlarged lesion on the iliopsoas muscle (Fig. 2). Subsequently, exploratory retroperitoneum open drainage was performed for the abscess on the iliopsoas muscle. Cultures from the pus and blood showed methicillin-resistant Staphylococcus aureus. After a month of therapy with vancomycin and drainage, follow-up CT showed complete remission. Fig 1. Computed tomography scan reveals (A) a low-attenuation lesion on the right iliopsoas muscle (white arrow) and (B) a low-attenuation lesion on the right pyriformis muscle (black arrow). Fig 2. Computed tomography scan demonstrates the enlarged lesion on the right iliopsoas muscle (arrow). A single-muscle abscess in a uremic patient has been reported,1,2 which may arise through contiguous spread from adjacent structures or by the hematogenous route from a distant site. In our case, a uremic patient presented pyriformis and psoas muscle abscesses simultaneously. However, it is difficult to determine whether these two muscle abscesses occurred at the same time or developed one after the other. Neither could we determine the micro-organic cause of the muscle abscess. To our knowledge, this is the first case in which a uremic patient has presented multiple muscle abscesses.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".