Association Between Time to Reperfusion and Outcome Is Primarily Driven by the Time From Imaging to Reperfusion
Bibliographic record
Abstract
BACKGROUND AND PURPOSE: A progressive decline in the odds of favorable outcome as time to reperfusion increases is well known. However, the impact of specific workflow intervals is not clear. METHODS: We studied the mechanical thrombectomy group (n=103) of the prospective, randomized REVASCAT (Randomized Trial of Revascularization With Solitaire FR Device Versus Best Medical Therapy in the Treatment of Acute Stroke due to Anterior Circulation Large Vessel Occlusion Presenting Within Eight Hours of Symptom Onset) trial. We defined 3 workflow metrics: time from symptom onset to reperfusion (OTR), time from symptom onset to computed tomography, and time from computed tomography (CT) to reperfusion. Clinical characteristics, core laboratory-evaluated Alberta Stroke Program Early CT Scores (ASPECTS) and 90-day outcome data were analyzed. The effect of time on favorable outcome (modified Rankin scale, 0-2) was described via adjusted odds ratios (ORs) for every 30-minute delay. RESULTS: Median admission National Institutes of Health Stroke Scale was 17.0 (14.0-20.0), reperfusion rate was 66%, and rate of favorable outcome was 43.7%. Mean (SD) workflow times were as follows: OTR: 342 (107) minute, onset to CT: 204 (93) minute, and CT to reperfusion: 138 (56) minute. Longer OTR time was associated with a reduced likelihood of good outcome (OR for 30-minute delay, 0.74; 95% confidence interval [CI], 0.59-0.93). The onset to CT time did not show a significant association with clinical outcome (OR, 0.87; 95% CI, 0.67-1.12), whereas the CT to reperfusion interval showed a negative association with favorable outcome (OR, 0.72; 95% CI, 0.54-0.95). A similar subgroup analysis according to admission ASPECTS showed this relationship for OTR time in ASPECTS<8 patients (OR, 0.56; 95% CI, 0.35-0.9) but not in ASPECTS≥8 (OR, 0.99; 95% CI, 0.68-1.44). CONCLUSIONS: Time to reperfusion is negatively associated with favorable outcome, being CT to reperfusion, as opposed to onset to CT, the main determinant of this association. In addition, OTR was strongly associated to outcome in patients with low ASPECTS scores but not in patients with high ASPECTS scores. CLINICAL TRIAL REGISTRATION: URL: http://www.clinicaltrials.gov. Unique identifier: NCT01692379.
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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) | 0.001 | 0.002 |
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; both teacher heads agree on what is shown here.
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".