Abstract TP373: Tracts Enfolded by Small Hematomas Remain Intact in Acute Intracerebral Hemorrhage
Bibliographic record
Abstract
Background: Mortality can be predicted by intracerebral hemorrhage (ICH) volume, but motor recovery in survivors is variable. Motor impairment is likely related to the spatial relationship between the hematoma and corticospinal tract (CST). Diffusion Tensor Imaging (DTI) tractography can be used to visualize white matter tracts in three dimensions. We hypothesized that the interaction between the hematoma and CST would predict motor impairment in ICH patients. Methods: ICH patients with small-moderate hematomas were prospectively imaged with CT and DTI within 14 days of onset. Hematoma volume was assessed on CT using planimetric techniques. Three-dimensional recreations of the ipsilateral CST and the hematoma were made for each patient. The CST was categorized by interaction with the ICH as CST: Unaffected, Displaced, Partially Severed, Completely Severed, and Splitting the ICH. Motor function was classified as 'good' (NIHSS motor subscale 0-2) or 'poor' (3-8). Results: Thirty patients (mean age 68±13) underwent CT at a median (IQR) of 2.3 (3.5)h and DTI at 2.0 (3.6, range 0.6-13) days. Median hematoma volume was 8.2 (23) ml. Lesion distribution was: lobar 11 (37%), basal ganglia 18 (60%), brainstem 1 (3%). CSTs were primarily Displaced (n=9) or Unaffected (8), with the remainder being Partially Severed (4), Completely Severed (5), and Splitting the ICH (4). The latter 4 (13%) patients had small (<6ml, median 2.5 [3.0] ml) basal ganglia bleeds which enfolded the intact CST. Motor score at Day 7 was good in 50% of patients. Good outcome was seen in 8 (100%) Unaffected, 4 (44%) Displaced, 1 (25%) Partially Severed, 0 (0%) Severed and 2 (50%) Splitting the ICH patients. Logistic regression indicated that good motor score was predicted by CST category (r=2.3, p=0.016). Conclusion: CST integrity can be maintained when enfolded by small basal ganglia bleeds. Diffusion tractography patterns may be useful for predicting motor scores in small to moderate-sized 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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| 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".