Extensive ischemic change on stroke presentation is uncommon: A population-based study
Bibliographic record
Abstract
BACKGROUND: Acute ischemic stroke (AIS) treatment and prognosis depend on the extent of ischemia sustained at time of presentation. The Alberta Stroke Program Early CT Score (ASPECTS) is used for anterior circulation stroke triage and decision making. We sought to determine the distribution of baseline ASPECTS at a population level. METHODS: Clinical imaging was collected from hospitalized AIS patients ascertained in a metropolitan population of 1.3 million as part of the Greater Cincinnati/Northern Kentucky Stroke Study. Patients presenting to an emergency department (ED) in 2015 within 24 hours of anterior circulation ischemic stroke were included. Events were excluded if last known normal (LKN) was unavailable, occurred in the inpatient setting, if CTH was unavailable, or if a previous ischemic event was already adjudicated during the study period. Blinded central neuroradiologists evaluated presenting ASPECTS. National Institutes of Health Stroke Scale (NIHSS) score ≥6 was used as a surrogate for large vessel occlusion, as routine baseline vessel imaging was performed inconsistently during the 2015 study period. RESULTS: Among 1,518 events of AIS presenting within 24 hours of LKN, 949 were anterior circulation first-time events with baseline ASPECTS status available, of which 520 (55 %) had baseline vessel imaging. Among these 949 patients (mean age 71 [SD 14] years, median ED arrival time 5.2 [IQR 1.3-13.2] hours, median NIHSS 4 [IQR 1-9]), 920 (96.9 %) had an ASPECTS ≥6, of which 844 had ASPECTS 9-10. Of the 373 patients with a NIHSS ≥6 at presentation, 344 (92.2 %) had an ASPECTS ≥6. Of the 150 patients presenting with NIHSS ≥6 beyond 6 hours of LKN time, 129 (86.0 %) had an ASPECTS ≥6. CONCLUSIONS: In our population, most patients presenting within 24 hours of LKN had ASPECTS ≥6. Even in patients with NIHSS ≥6, only 14 % of patients presenting in the extended time window had ASPECTS <6. These results can inform resource utilization and clinical trial design.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".