Subdural and Systemic C-Reactive Protein in Patients with Chronic Subdural Hematoma Recurrence
Bibliographic record
Abstract
ABSTRACT Background: C-reactive protein (CRP) level in blood is a standard marker for systemic inflammation. Inflammation is central in chronic subdural hematoma (CSDH) pathophysiology, and inflammatory biomarkers may hold clinical potential in assessing the level of inflammation induced by a CSDH. This study explores the role of CRP in patients with CSDH by (1) measuring systemic and subdural CRP levels, (2) investigating CRP as a potential predictor for recurrent CSDH and (3) comparing CRP levels between the first and second operations in patients with CSDH recurrence. Methods: CRP levels were measured both in systemic blood and subdural fluid from adult CSDH patients. Recurrence rate and mortality within 90 days were recorded. In total, 111 patients were included, of whom 25 were operated on for CSDH recurrence. Results: Systemic CRP levels (2.54 mg/L (1.40–9.75)) were higher than subdural levels (2.09 mg/L [0.99–5.22]) ( p < 0.0001) but within the clinically defined normal CRP range of < 3 mg/L. Neither systemic nor subdural CRP levels could predict recurrence. Both systemic and subdural CRP levels in recurrent CSDH patients were higher at the time of the second surgery compared to the first surgery ( p systemic = 0.004 and p subdural < 0.0001). Conclusion: This is the first study to establish a correlation between systemic and subdural CRP levels in CSDH patients. The increased levels of CRP at the time of the second surgery may demonstrate a constantly evolving inflammatory process toward the development of a recurrence.
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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 | 0.001 |
| 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) | 0.002 | 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".