Addition of Hyperacute MRI Aids in Patient Selection, Decreasing the Use of Endovascular Stroke Therapy
Bibliographic record
Abstract
BACKGROUND AND PURPOSE: The failure of recent trials to show the effectiveness of acute endovascular stroke therapy (EST) may be because of inadequate patient selection. We implemented a protocol to perform pretreatment MRI on patients with large-vessel occlusion eligible for EST to aid in patient selection. METHODS: We retrospectively identified patients with large-vessel occlusion considered for EST from January 2008 to August 2012. Patients before April 30, 2010, were selected based on computed tomography/computed tomography angiography (prehyperacute protocol), whereas patients on or after April 30, 2010, were selected based on computed tomography/computed tomography angiography and MRI (hyperacute MRI protocol). Demographic, clinical features, and outcomes were collected. Univariate and multivariate analyses were performed. RESULTS: We identified 267 patients: 88 patients in prehyperacute MRI period and 179 in hyperacute MRI period. Fewer patients evaluated in the hyperacute MRI period received EST (85 of 88, 96.6% versus 92 of 179, 51.7%; P<0.05). The hyperacute-MRI group had a more favorable outcome of a modified Rankin scale 0 to 2 at 30 days as a group (6 of 66, 9.1% versus 33 of 140, 23.6%; P=0.01), and when taken for EST (6 of 63, 9.5% versus 17 of 71, 23.9%; P=0.03). On adjusted multivariate analysis, the EST in the hyperacute MRI period was associated with a more favorable outcome (odds ratio, 3.4; 95% confidence interval, 1.1-10.6; P=0.03) and reduced mortality rate (odds ratio, 0.16; 95% confidence interval, 0.03-0.37; P<0.001). CONCLUSIONS: Implementation of hyperacute MRI protocol decreases the number of endovascular stroke interventions by half. Further investigation of MRI use for patient selection is warranted.
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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".