Polymicrobial brain abscesses: A complex condition with diagnostic and therapeutic challenges
Bibliographic record
Abstract
Brain abscesses (BA) are focal parenchymal infections that remain life-threatening conditions. Polymicrobial BAs (PBAs) are complex coinfections of bacteria or bacterial and nonbacterial pathogens such as fungi or parasites, with diagnostic and therapeutic challenges. In this article, we comprehensively review the prevalence, pathogenesis, clinical manifestations, and microbiological, histopathological, and radiological features of PBAs, as well as treatment and prognosis. While PBAs and monomicrobial BAs have some similarities such as nonspecific clinical presentations, PBAs are more complex in their pathogenesis, pathological, and imaging presentations. The diagnostic challenges of PBAs include nonspecific imaging features at early stages and difficulties in identification of some pathogens by routine techniques without the use of molecular analysis. Imaging of late-stage PBAs demonstrates increased heterogeneity within lesions, which corresponds to variable histopathological features depending on the dominant pathogen-induced changes in different areas. This heterogeneity is particularly marked in cases of coinfections with nonbacterial pathogens such as Toxoplasma gondii. Therapeutic challenges in the management of PBAs include initial medical therapy for possibly underrecognized coinfections prior to identification of multiple pathogens and subsequent broad-spectrum antimicrobial therapy to eradicate identified pathogens. PBAs deserve more awareness to facilitate prompt 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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| 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".