Abstract WP38: Lower Fluid Attenuated Inversion Recovery Magnetic Resonance Imaging Signal Intensity After Acute Ischemic Stroke is Associated With Better Discharge Outcomes in Thrombolysed Patients
Bibliographic record
Abstract
Background: Increases in FLAIR MRI signal intensity (SI) after acute ischemic stroke (AIS) have been proposed as “tissue clocks”, reflecting the degree of ischemic injury and potential for recovery in brain tissue. We hypothesize that lower SI increases will be a biomarker for less severe tissue injury and hence is potentially salvageable. To test this, we investigated patients who were treated with tPA to determine whether better outcomes were associated with lower FLAIR SI. Methods: Using our Get with the Guidelines database, we retrospectively analyzed AIS patients admitted between 2011 to 2013 who received full-dose tPA based on institutional protocols. Patients were included if they received a CT scan at our hospital before tPA therapy, and MRI performed < 1 h post CT included a usable FLAIR scan and evidence of stroke on acute DWI. SI ratio (SIR) was calculated on the FLAIR by selecting region of interests in hyperintense FLAIR areas that coincided with the acute DWI lesion and matching contralateral regions. Logistic regression analysis was performed using forward stepwise analysis to combine age, sex, admission NIHSS, SIR and onset-to-treatment (OTT) time to predict discharge outcome. Good outcome was defined as discharge to home or in-patient rehabilitation hospital. Results: There were 129 AIS patients who received tPA, and 57 met our imaging criteria. Patient characteristics were: mean±SD age 70±15 years, median [IQR] NIHSS 13 [7-18], OTT 2.1±1.1 h, time-to-MRI 2.1±1.0 h, 58% female and median SIR 1.13 [1.05-1.26]. On a univariate basis, only age (P<0.0001) and NIHSS (P=0.005) were significant predictors of outcome. However, multivariate analysis showed that combining age (P=0.019), NIHSS (P=0.022), and SIR (P=0.018) was able to predict good discharge outcome with 100% [95% CI 63-100%] specificity and 90% [77-96%] sensitivity. Using age and NIHSS alone, resulted in the same specificity but only 71% [56-83%] sensitivity. Discussion: Controlling for age and admission NIHSS, we found that lower FLAIR SIR was a significant predictor of discharge outcome while OTT was not. This suggests that “tissue clocks” may be more accurate than “time clocks” for predicting tissue outcome, and ultimately functional outcome.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".