Factors influencing the presence of hemiparesis in chronic subdural hematoma
Bibliographic record
Abstract
OBJECTIVE: Chronic subdural hematoma (CSDH) has a variety of clinical presentations, including hemiparesis. Hemiparesis is of the utmost importance because it is one of the major indications for surgical intervention and influences outcome. In the current study, the authors intended to identify factors influencing the presence of hemiparesis in CSDH patients and to determine the threshold value of hematoma thickness and midline shift for development of hemiparesis. METHODS: The authors retrospectively reviewed 325 patients (266 with unilateral and 59 with bilateral hematomas) with CSDH who underwent surgical evacuation, regardless of presence or absence of hemiparesis. RESULTS: In univariate analysis, hematoma loculation, age, hematoma maximal thickness, and midline shift were significantly associated with hemiparesis. Moreover, patients with unilateral hematomas had a higher rate of hemiparesis than patients with bilateral hematomas. Sex, trauma history, anticoagulant and antiplatelet drug use, presence of comorbidities, Glasgow Coma Scale score, hematoma density characteristics on CT scan, and hematoma signal intensity on T1- and T2-weighted MRI were not associated with hemiparesis. In multivariate analysis, the presence of loculation and hematoma laterality (unilateral vs bilateral) influenced hemiparesis. For unilateral hematomas, maximal hematoma thickness of 19.8 mm and midline shift of 6.4 mm were associated with a 50% probability of hemiparesis. For bilateral hematomas, 29.0 mm of maximal hematoma thickness and 6.8 mm of shift were associated with a 50% probability of hemiparesis. CONCLUSIONS: Presence of loculations, unilateral hematomas, older patient age, hematoma maximal thickness, and midline shift were associated with a higher rate of hemiparesis in CSDH patients. Moreover, 19.8 mm of hematoma thickness and 6.4 mm of midline shift were associated with a 50% probability of hemiparesis in patients with unilateral hematomas.
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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) | 0.001 | 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".