Abstract Details

Title Pre-alert, Imaging-independent Stroke Prognosis with Circadian and Operational Context: A Calibrated 90-Day mRS Model that Outperforms NIHSS and SPAN-100

Topic Cerebrovascular Disease and Interventional Neurology

Presentation(s) P2 - Poster Session 2 (11:45 AM-12:45 PM)

Poster/Presentation
Number 4-001

Objective Develop and validate a pre-alert model that predicts 90-day poor outcome (mRS >2) using information available at stroke alert, including time-of-day and weekend context, and compare it with common clinical tools.

Background Key workflow and communication decisions often occur before CT or CTA is obtained or interpreted. Tools such as NIHSS and SPAN-100 help stratify severity, but do not provide calibrated probabilities or incorporate timing and operational context at the moment of alert.

Design/Methods Consecutive stroke alerts from a single health system with 90-day mRS (N = 928) were analyzed retrospectively. To emulate deployment, the newest 20% by alert time comprised the temporal Test set. Pre-treatment predictors included: age, NIHSS, transfer/LVO flags, hour-of-day (sin/cos), weekend, and nonnegative intervals from LKW/CSA to CT/CTA. Outcome/treatment fields were excluded by name. A logistic regression model with isotonic calibration produced calibrated probabilities. Comparators were NIHSS-only, age+NIHSS, and SPAN-100 (rule and calibrated). The frozen model was tested in a deduplicated clinical replication cohort from the same system and window (N = 386). Primary metrics were ROC AUC, PR-AUC, and Brier score; decision-curve analysis assessed net benefit. EVT was not a predictor; used only for subgroup reporting.

Results Temporal Test (N = 185, prevalence 0.465): AUC 0.793, PR-AUC 0.726, Brier 0.1854. Replication (N = 386, prevalence 0.521): AUC 0.749, PR-AUC 0.766, Brier 0.2288. On the Test set, the model outperformed NIHSS-only (AUC 0.770, PR-AUC 0.702, Brier 0.1945) and SPAN-100 (calibrated AUC 0.770, PR-AUC 0.746, Brier 0.1957; rule AUC 0.638, PR-AUC 0.590, Brier 0.3405), and matched age plus NIHSS on discrimination (AUC 0.799) while improving probability accuracy. Decision-curve analysis showed positive net benefit.

Conclusions A time-aware, imaging-independent pre-alert model provides calibrated 90-day risk estimates and improves on widely used scores. It supports faster readiness and clear prognosis before the scan. Findings justify a silent prospective run and multi-site validation.

Authors/Disclosures
Joshua Jimenez PRESENTER	Mr. Jimenez has nothing to disclose.
Joao Victor Sanders (Brain & Spine Institute, Advocate Health)	Joao Victor Sanders has nothing to disclose.
Kiffon Keigher (Brain & Spine Institute, Advocate Health)	Kiffon Keigher has received personal compensation for serving as an employee of Medtronic. Kiffon Keigher has or had stock in Medtronic.
Marion Oliver, MD (GRMEP)	Dr. Oliver has nothing to disclose.
Krishna Joshi (Brain & Spine Institute, Advocate Health)	No disclosure on file
Demetrius Lopes (Brain & Spine Institute, Advocate Health)	Demetrius Lopes has nothing to disclose.

��ɫ��

��ɫ��