Multimodal CT Imaging: Time to Treatment and Outcomes in the IMS III Trial
Bibliographic record
Abstract
BACKGROUND AND PURPOSE: The importance of time in acute stroke is well-established. Using the Interventional Management of Stroke III trial data, we explored the effect of multimodal imaging (CT perfusion and/or CT angiography) versus noncontrast CT alone on time to treatment and outcomes. MATERIALS AND METHODS: We examined 3 groups: 1) subjects with baseline CTP and CTA (CTP+CTA), 2) subjects with baseline CTA without CTP (CTA), and 3) subjects with noncontrast head CT alone. The demographics, treatment time intervals, and clinical outcomes in these groups were studied. RESULTS: Of 656 subjects enrolled in the Interventional Management of Stroke III trial, 90 (13.7%) received CTP and CTA, 216 (32.9%) received CTA (without CTP), and 342 (52.1%) received NCCT alone. Median times for the CTP+CTA, CTA, and NCCT groups were as follows: stroke onset to IV tPA (120.5 versus 117.5 versus 120 minutes; P = .5762), IV tPA to groin puncture (77.5 versus 81 versus 91 minutes; P = .0043), groin puncture to endovascular therapy start (30 versus 38 versus 44 minutes; P = .0001), and endovascular therapy start to end (63 versus 46 versus 74 minutes; P < .0001). Compared with NCCT, the CTA group had better outcomes in the endovascular arm (OR, 2.12; 95% CI, 1.36-3.31; adjusted for age, NIHSS score, and time from onset to IV tPA). The CTP+CTA group did not have better outcomes compared with the NCCT group. CONCLUSIONS: Use of CTA with or without CTP did not delay IV tPA or endovascular therapy compared with NCCT in the Interventional Management of Stroke III trial.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".