Clinicopathological heterogeneity and complexity of polymicrobial brain abscesses
Bibliographic record
Abstract
Polymicrobial brain abscess (PBA) is a complex infection caused by two or more pathogens and a life-threatening condition with diagnostic and therapeutic challenges. We retrospectively identified PBAs in 31 patients (24 males and 7 females) and examined their clinical, radiological and pathological characteristics. These characteristics of PBAs were compared with those of monomicrobial BAs (MBAs) in a previously reported cohort of 113 patients in our institution. PBAs and MBAs had a few similarities such as nonspecific clinical presentations, a male predilection, and similar prognosis following surgical intervention with broad-spectrum antimicrobial therapy. However, PBAs were highly heterogeneous with more complexity on magnetic resonance imaging (MRI)/computed tomography imaging and histopathology. While PBAs were typically rim-enhancing lesions at late-stages, 30/31 (97 %) of PBAs showed lobulation of enhancing rims/walls; on MRI, 14/26 (54 %) of cases demonstrated marked variation in the thickness of enhancing rim, marked difference in the degree of diffusion-weighted imaging (DWI) signal, and/or marked variation in intra-lesional MRI signal. PBA histopathology was characterized mainly by alternating early-stage and late-stage features with regional differences, variable distribution and combinations of 2-4 pathogens. Compared to MBAs, PBAs were more frequently unifocal (94 % of cases) as well as caused by pathogens of otogenic, odontogenic and/or rhinogenic sources. Our findings suggest that, despite some shared features between PBAs and MBAs, PBAs are more heterogeneous with greater complexity on imaging and histopathology. Their diagnosis and disease staging require an integrative clinico-radiologico-pathological approach. PBAs deserve more awareness for prompt diagnosis and appropriate treatment.
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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 | 0.001 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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 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".