Ischemic core thresholds change with time to reperfusion: A case control study
Bibliographic record
Abstract
INTRODUCTION: We aimed to identify whether acute ischemic stroke patients with known complete reperfusion after thrombectomy had the same baseline computed tomography perfusion (CTP) ischemic core threshold to predict infarction as thrombolysis patients with complete reperfusion. METHODS: Patients who underwent thrombectomy were matched by age, clinical severity, occlusion location, and baseline perfusion lesion volume to patients who were treated with intravenous alteplase alone from the International Stroke Perfusion Imaging Registry. A pixel-based analysis of coregistered pretreatment CTP and 24-hour diffusion-weighted imaging (DWI) was then undertaken to define the optimum CTP thresholds for the ischemic core. RESULTS: There were 132 eligible thrombectomy patients and 132 matched controls treated with alteplase alone. Baseline National Institutes of Health Stroke Scale (median, 15; interquartile range [IQR], 11-19), age (median, 65; IQR, 59-80), and time to intravenous treatment (median, 153 minutes; IQR, 82-315) were well matched (all p > 0.05). Despite similar baseline CTP ischemic core volumes using the previously validated measure (relative cerebral blood flow [rCBF], <30%), thrombectomy patients had a smaller median 24-hour infarct core of 17.3ml (IQR, 11.3-32.8) versus 24.3ml (IQR, 16.7-42.2; p = 0.011) in alteplase-treated controls. As a result, the optimal threshold to define the ischemic core in thrombectomy patients was rCBF <20% (area under the curve [AUC], 0.89; 95% CI, 0.84, 0.94), whereas in alteplase controls the optimal ischemic core threshold remained rCBF <30% (AUC, 0.83; 95% CI, 0.77, 0.85). INTERPRETATION: Thrombectomy salvaged tissue with lower CBF, likely attributed to earlier reperfusion. For patients who achieve rapid reperfusion, a stricter rCBF threshold to estimate the ischemic core should be considered. Ann Neurol 2017;82:995-1003.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| 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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".