P.122 Radiologico-pathologic heterogeneity and complexity of polymicrobial brain abscesses
Bibliographic record
Abstract
Background: Polymicrobial brain abscess (PBA) is a complex infection caused by two or more pathogens and a life-threatening condition with diagnostic and therapeutic challenges. Methods: We retrospectively identified PBAs in 31 patients (a median of 58 years; 24 male, and 7 female) then examined their clinical, radiological and pathological characteristics. These characteristics of PBAs were compared with those of monomicrobial BAs (MBAs) in the previously reported 113 patients. Results: PBAs and MBAs had a few similarities such as nonspecific clinical presentations and overall similar prognosis following surgical intervention with broad-spectrum antimicrobial therapy. However, PBAs were highly heterogeneous with more complexity on MRI/CT imaging and histopathology. While PBAs were typically rim-enhancing lesions at late-stages, 30/31 (97%) of PBAs showed the lobulation of enhancing rims/walls; on MRI, 14/26 (54%) of cases demonstrated marked difference in the thickness of enhancing rim, marked difference in the degree of DWI signal, and/or marked variation in intra-lesional MRI signal. PBA histopathology was characterized by alternating early-stage and late-stage features with a combinations of 2-4 pathogens. Conclusions: BPAs share some features with MBAs, but they are more heterogeneous with greater complexity on imaging and histopathology. Their diagnosis and disease staging require a clinico-radiologico-pathological approach.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.006 | 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".