Abstract W MP18: Baseline-24h CT ASPECTS Mismatch. A Predictor Variable of Successful Trhrombectomy
Bibliographic record
Abstract
BACKGROUND: In acute thromboembolic stroke, mechanical recanalization with retrieval stents may result in immediate flow restoration. A selection criteria to treatment is a small volume of infarct in baseline CT scan, usually it is identified as an infarct <1/3 MCA or mild early ischemic changes (ASPECTS>7). We assess whether evaluation of basal and 24h CT using Alberta Stroke Program Early Computed Tomography Score (ASPECTS) have predictive value for functional independence after stroke on noncontrast CT (NCCT). METHODS: We performed an retrospective analysis of 257 consecutive patients treated with thrombectomy (Solitaire, Trevo) , from April of 2010 to June of 2013, that met inclusion criteria for intervention. Vessel patency pre and post procedural were measured by TIMI and TICI score.Successful recanalization (TICI 2b-3), functional and clinical good outcome (mRankin 0-2) and mortality at day 90 and symptomatic hemorrhage were prospectively assessed. We evaluated baseline NCCT, mean final infarct extension measuring by 24h-ASPECTS and change in ASPECTS from baseline to 24h CT. RESULTS: A total of 168 patients with ischemic stroke of the MCA territory (M1 segment or terminal internal carotid occlusion) were included in this study. We calculated ASPECTS mismatch as 24H NCCT ASPECTS/Baseline NCCT ASPECTS*100. Low percentage represents a reduced infarct and an higher efficacy of the neurointerventionism (TICI 2b-3, p:0.001) . Basal and 24h ASPECTS were dichotomized at >=8 vs <8 according with ROC analysis. Higher scores >=8 in NCCT ASPECTS implied a higher probability of an independent functional outcome at 90 days (mRankin 0-2) when compared to <8 ASPECTS group (OR 1.47, 95% CI 1.21-1.83) and likewise in 24h NCCT (OR 1.65, 95% CI 1.35-2.1). The mismatch between basal ASPECTS in NCCT and 24h ASPECTS demonstrated important predictive value (OR 0.54, 95% CI 0.42-0.68) of clinical prognosis (cut-off value <20%, Sensivity 81%, Specificity 72%; AUC 0,74; p:0001), mainly in the group of 24h ASPECTS <8. CONCLUSIONS: The baseline and 24h NCCT ASPECTS were a strong predictor of functional outcome. Moreover lower mismatch between basal and 24h ASPECTS was also reliable as predictive value in good functional outcome.
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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 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".