The Relationship between Diffusion Anisotropy and Time of Onset after Stroke
Bibliographic record
Abstract
Diffusion anisotropy changes in stroke lesions less than 24 h after onset have been reported to be elevated, decreased, or both. To address these mixed findings, we sought to characterize temporal changes of diffusion anisotropy by analyzing anatomically distinct ischemic white matter (WM) regions at 3 time phases within the first 34 h of ischemic stroke onset in 26 stroke patients (2 to 5 h, N = 7; 7 to 14 h, N = 11; 18 to 34 h, N = 8). Mean diffusivity (Trace/3 apparent diffusion coefficient (ADC)), fractional anisotropy (FA), and T2-weighted signal intensity were measured for major and subcortical WM in lesions defined by a > 30% drop in Trace/3 ADC. Major WM tract lesions with mean decreases of ~40% in relative (r) Trace/3 ADC showed an increased rFA of 1.11 ± 0.18 ( P < 0.01) during the hyperacute phase (2 to 5h), whereas rFA declined to 0.90 ± 0.20 ( P < 0.01) and 0.88 ± 0.12 ( P < 0.01) in the acute (7 to 14 h) and subacute (18 to 34h) phases, respectively. Of those patients with lesions in major WM, 4 of 8 patients ≤ 7 h showed elevated rFA as opposed to none of the remaining 13 patients after 7 h. A greater proportion of the evaluated WM regions-of-interest (ROI) in the hyperacute phase revealed increases in rFA (60%), whereas conversely large proportions of ROIs (55% and 59%) in the acute and subacute phases showed reduced rFA. Similar anisotropy changes were noted in subcortical WM regions in the gyri.
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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) | 0.002 | 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".