The Crucial Role of Eosinophils in the Life Cycle, Radiographical Architecture, and Risk of Recurrence of Chronic Subdural Hematomas
Bibliographic record
Abstract
Chronic subdural hematomas (CSDHs) are a common neurological condition, whose incidence is expected to increase with an aging population. Although surgical evacuation is the mainstay of treatment, it results in a recurrence requiring reoperation (RrR) in 3-30% of cases. Recurrence is thought to be driven by a combination of inflammatory and angiogenic processes occurring within the CSDH outer membrane. Pathological specimens of 72 primary CSDHs were examined for eosinophilic infiltrate. For each case, the pre-operative computed tomography (CT) scan was graded according to the Nakaguchi grading scheme as homogeneous, laminar, separated, or trabecular. Rate of RrR was compared based on eosinophilic infiltrate and CT grade. A dense eosinophilic infiltrate was observed in 22% of specimens. The rate of RrR among specimens with a dense eosinophilic infiltrate was 0%, whereas it was 14.3% among specimens without a dense eosinophilic infiltrate. Incidence among homogeneous, laminar, separated, and trabecular CT subtypes was 4%, 27%, 58%, and 24%, respectively. A dense eosinophilic infiltrate found within the outer membrane of a CSDH may be a marker of hematoma maturation, signaling a transition toward healing and fibrosis, and a lower risk of RrR.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| 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) | 0.001 | 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".