Abstract WP248: Pre-treatment Perfusion CT in Stroke Thrombolysis Can Predict Disability-free Life
Bibliographic record
Abstract
Introduction: Stroke shortens an individual’s disability-free life. We aimed to assess the relative prognostic influence of pre- and post-treatment perfusion CT imaging variables (e.g. ischemic core and penumbral volumes) compared to standard clinical predictors (such as onset-to-treatment time) on long-term stroke disability in patients undergoing thrombolysis. Methods: We used data from a prospectively collected international, multicenter, observational registry of acute ischemic stroke patients who had perfusion CT and CT angiography before treatment with intravenous alteplase. Baseline perfusion CT and follow-up MRI were analysed to derive the baseline penumbra volume, baseline ischemic core volume, and penumbra salvaged from infarction. The primary outcome measure was the effect of imaging and clinical variables on disability-adjusted life years (DALY). Clinical variables were age, sex, NIHSS score, and onset-to-treatment time. Age, sex, country, and 3-month modified Rankin Scale were extracted from the registry to calculate DALY due to stroke, such that one year of DALY equates to 1 year of healthy life lost due to stroke. Results: Seven hundred seventy two patients were treated with alteplase therapy. 17.5 DALY-days were lost per 1 mL of baseline ischemic core volume (95%CI, 13.2 - 21.9 days, p < 0.001). For every mL of penumbra salvaged, 7.2 days of DALY-days were saved (95%CI, 4.1 - 10.4 days, p < 0.001). Each minute of earlier onset-to-treatment time resulted in a saving of 4.4 disability-free days after stroke (1.3 - 7.5 days, p = 0.006). However, after adjustment for imaging variables, onset-to-treatment time was not significantly associated with savings in DALY-days. Conclusions: Pre-treatment perfusion CT scan defined penumbra (independently of clinical variables) predict significant gains, or loss, of disability-free life in patients undergoing reperfusion therapy for stroke. The effect of earlier treatment on disability-free life appears explained by salvage of penumbra.
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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 | 0.002 | 0.009 |
| 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 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".