Iliopsoas Abscesses: Whose Problem is it? Insights Gained by an Institutional 100-Patient Consecutive Case Series
Bibliographic record
Abstract
BACKGROUND: Iliopsoas abscess (IPA) is a rare but serious condition caused by hematogenous or contiguous spread of infection. Management typically involves broad-spectrum antibiotics, with percutaneous or surgical drainage for larger abscesses. METHODS: We retrospectively reviewed 113 IPA cases at the Swedish Neuroscience Institute (2015-2024), analyzing demographics, clinical features, imaging, treatment strategies, hospital course, and outcomes. RESULTS: Among 100 patients included, 86 presented with back or flank pain, 45 with abdominal pain, and 35 with lower extremity discomfort. The most common pathogens were Staphylococcus aureus (38%) and Escherichia coli (31%). Mean patient age was 56 years (range: 32-71); 29% had intra-abdominal inflammatory disease, 25% had bacteremia, and 32% were intravenous drug users. Antibiotics alone were successful in 16/21 patients (76%), while 5 (24%) required subsequent CT-guided percutaneous drainage (PCD). Among 72 patients undergoing PCD, 32 (44%) had successful treatment, 12 (17%) required multiple procedures, and 28 (39%) underwent surgery after failed drainage. Primary surgical drainage was performed in 7 patients (7%). Mean hospital stay was 21 days, and overall mortality was 5%, lower than reported rates (5%-15%). CONCLUSIONS: First-line treatment for IPA includes antibiotics and PCD, with surgery reserved for complex cases, gas formation, neurological involvement, proximity to vertebrae or spinal hardware, or failure of initial treatment.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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".