Prevalence of “Ghost Infarct Core” after Endovascular Thrombectomy
Bibliographic record
Abstract
BACKGROUND AND PURPOSE: Baseline CTP sometimes overestimates the size of the infarct core ("ghost core" phenomenon). We investigated how often CTP overestimates infarct core compared with 24-hour imaging, and aimed to characterize the patient subgroup in whom a ghost core is most likely to occur. MATERIALS AND METHODS: Data are from the randomized controlled ESCAPE-NA1 trial, in which patients with acute ischemic stroke undergoing endovascular treatment were randomized to intravenous nerinetide or placebo. Patients with available baseline CTP and 24-hour follow-up imaging were included in the analysis. Ghost infarct core was defined as CTP core volume minus 24-hour infarct volume > 10 mL). Clinical characteristics of patients with versus without ghost core were compared. Associations of ghost core and clinical characteristics were assessed by using multivariable logistic regression. RESULTS: A total of 421 of 1105 patients (38.1%) were included in the analysis. Forty-seven (11.2%) had a ghost core > 10 mL, with a median ghost infarct volume of 13.4 mL (interquartile range 7.6-26.8). Young patient age, complete recanalization, short last known well to CT times, and possibly male sex were associated with ghost infarct core. CONCLUSIONS: CTP ghost core occurred in ∼1 of 10 patients, indicating that CTP frequently overestimates the infarct core size at baseline, particularly in young patients with complete recanalization and short ischemia duration.
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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 | 0.015 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".