Clinical Outcome and Recurrence Risk of Chronic Subdural Hematoma After Surgical Drainage
Bibliographic record
Abstract
Introduction Chronic subdural hematoma (CSDH) is one of the most encountered neurosurgical cases. CSDH is defined as the accumulation of liquified blood products in the space between the dura and the arachnoid. A reported incidence of 17.6/100,000/year has more than doubled in the past 25 years in parallel with an aging population. Surgical drainage remains the mainstay of treatment, yet it is challenged by variable recurrence risks. Less invasive embolization methods of the middle meningeal artery (EMMA) could reduce the recurrence risks. Before adopting a newer treatment (EMMA), it is prudent to establish the outcomes from surgical drainage. The purpose of this study is to assess the clinical outcome and recurrence risk in surgically treated CSDH patients in our center. Methods A retrospective search of our surgical database was done to identify CSDH patients undergoing surgical drainage in the year 2019-2020. Demographic and clinical details were collected, and quantitative statistical analysis was performed. Peri-procedural radiographic information and follow-ups were also included as per the standard of care. Results A total of 102 patients (mean age: 69 years; range: 21-100 years; male: 79) with CSDH underwent surgical drainage with repeat surgery in 13.7% of the patients (n=14). Peri-procedural mortality and morbidity were 11.8%(n=12) and 19.6% (n=20), respectively. Overall, among our patient population, recurrence was seen in 22.55% (n=23). The mean total hospital stay was 10.6 days. Conclusions Our retrospective cohort study showed an institutional CSDH recurrence risk of 22.55%, in keeping with what is reported in the literature. This baseline information is important for a Canadian setting and provides a basis for comparison for future Canadian trials.
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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 | 0.001 | 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".