NORMAL BASELINE CT PERFUSION PREDICTS SMALLER INFARCT VOLUMES AND BETTER FUNCTIONAL OUTCOME WITH INTRAVENOUS THROMBOLYSIS IN CLINICAL LACUNAR SYNDROME
Bibliographic record
Abstract
Background and aim:Lacunar infarction accounts for approximately 25% of acute ischaemic strokes. Previous studies have shown patients with lacunar infarction treated with intravenous thrombolysis had a favourable clinical course. This case series tested the hypothesis that patients with clinical lacunar syndrome with normal baseline CT perfusion treated with intravenous thrombolysis had a better outcome compared to patients demonstrating hypoperfusion on CT. Methods:A retrospective analysis of patients with clinical lacunar syndrome with baseline CT perfusion treated with intravenous thrombolysis in Calgary from 2015 to 2018. Results:There were 15 patients [(47%) female; median age 67 (range: 36-83) years] included. 6 patients had normal CTP. The median baseline NIHSS was 8 (range 5-13). The median onset to needle time was 237 (range 60-305) minutes. The median 24-hour NIHSS was 4 (range 1-13). The median 24-hour DWI infarct volume was 0.20 (range 0.04-0.76) ml. 5 (83%) patients achieved functional independence (modified Rankin Scale, mRS: 0-2) at 90 days. 9 patients had hypoperfusion on CTP. The median baseline NIHSS was 12 (range 2-17). The median onset to needle time was 227 (range 55-482) minutes. The median 24 hour NIHSS was 6 (range 0-12). The median 24-hour DWI infarct volume was 1.05 (0.15-1.19) ml. 4 (44%) patients achieved functional independence at 90 days. No patient died or had symptomatic intracerebral hemorrhage. Conclusions: Normal baseline CT perfusion appears to predict better 90-day functional outcome and smaller infarct volumes with intravenous thrombolysis in patients with clinical lacunar syndrome.
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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 | 0.002 |
| 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 | 0.001 |
| 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".