Age-adjusted infarct volume threshold for good outcome after endovascular treatment
Bibliographic record
Abstract
BACKGROUND AND PURPOSE: Infarct volume and age are strong predictors of outcome in patients with stroke. We aimed to determine the impact of infarct volume on outcome according to age. METHODS: Consecutive patients with acute stroke with documented internal carotid artery/middle cerebral artery occlusion who underwent endovascular procedures were studied. Patients were categorized in three age groups: <70 years (G1), 70-79 years (G2), ≥80 years (G3). The Alberta Stroke Program Early CT score (ASPECTS) was graded on initial CT. Time of successful recanalization (Thrombolysis In Cerebral Infarct (TICI) ≥2b )and good outcome at 3 months (modified Rankin Scale score ≤2) were recorded. Infarct volume was measured on the 24 h control CT. RESULTS: A total of 214 patients were studied (G1: 68; G2: 74; G3: 72). For all patients the mean infarct volume was 94.7±127 mL; 35.6% had a good outcome. We observed larger infarct volumes in patients with a bad outcome in each age group (G1: 22 vs 182 mL, p<0.01/G2: 22 vs 164 mL, p<0.01/G3: 7.6 vs 132 mL, p<0.01). However, the target cut-off infarct volume that better predicted a good outcome decreased as age increased: G1: 49 mL (sensitivity 80%, specificity 92.6%); G2: 32.5 mL (sensitivity 80%, specificity 81%); G3: 15.2 mL (sensitivity 81.3%, specificity 86.7%). Overall, after adjusting for age, occlusion location, baseline NIH Stroke Scale score and infarct volume, the only predictor of a good outcome was achieving a final infarct volume less than the age-adjusted target (OR 5.5, 95% CI 1.6 to 18.8; p<0.01). The probability of achieving an infarct volume less than the age-adjusted target decreased according to baseline ASPECTS, time and degree of recanalization. CONCLUSIONS: Age-adjusted infarct size might represent a powerful surrogate marker of stroke outcome and further refine the predictive accuracy of infarct volume on prognosis in patients with stroke undergoing endovascular treatment. This information may be used in the design of new trials to individualize selection criteria for different age groups.
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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) | 0.001 | 0.002 |
| 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) | 0.002 | 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 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".