Abstract TP50: Efficacy of Stent-retriever Thrombectomy in MRI Vs. CT Perfusion Selected Patients in SWIFT PRIME
Bibliographic record
Abstract
Background: The majority of patients enrolled in SWIFT PRIME had CT perfusion imaging immediately prior to randomization; 34 patients were randomized following a diffusion and perfusion MRI. Methods: Patients with MCA (M1) and distal carotid occlusions were randomized to treatment with tPA alone vs. tPA + Solitaire stent retriever. The primary outcome was the distribution of the mRS at 90 days. The same automated software (RAPID) was used for both MRI and CTP patients to identify patients with the Target mismatch profile for enrollment. Results: MRI selection was performed in 34 patients; CTP in 139. Mean age was 71 years (MRI) vs. 68 years (CTP), p=0.08; baseline NIHSS was 17 in both groups. Target mismatch profile was present in 95% (MRI) vs. 83% (CTP), p=0.3. Median time from ER arrival to randomization was 69 min (MRI) vs. 67 min (CTP), p=0.61. A higher percentage of the MRI group was transferred from an outside hospital (59% vs. 35%, p=0.02) and therefore the time from stroke onset to randomization was longer in the MRI group (236 minutes vs. 179 minutes, p=0.003.) Baseline median ischemic core volumes were similar in the MRI vs. CTP group (7 ml vs. 5 ml); baseline perfusion lesions were larger in the MRI group (133 ml vs. 97 ml, P=0.01) Reperfusion rates (> 90%/TICI 3) did not differ in the Solitaire treated patients in the MRI (94%) vs. CTP (85%) groups, p=0.7. The primary efficacy analysis (distribution of mRS at 90 days) demonstrated a statistically significant benefit in both the MRI (p=0.02) and CTP subgroups (p=0.01). Among MRI selected patients, mRS 0-2 at 90 days occurred in 63% of the Solitaire group vs. 33% of the tPA alone group (ARR 30%, p=0.17) and infarct growth was reduced (17 ml vs. 50 ml, p=0.089). CTP selected patients had mRS 0-2 rates at 90 days of 60% in the Solitaire group vs. 40% tPA alone (ARR 20%, p=0.025) and a reduction in infarct growth (14 vs. 27 ml, p=0.047). Conclusions: Although MRI selected patients in SWIFT PRIME were slightly older and treated longer after symptom onset, they demonstrated a statistically significant benefit on the primary efficacy endpoint. Reductions in infarct growth and rates of favorable clinical outcomes in the MR subgroup were also comparable to those seen in the CT perfusion subgroup.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 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 | 0.000 | 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".