Abstract W MP74: Development And Validation Of A Modified Stroke Thrombolytic Predictive Instrument To Improve Implementation And Ease Of Use
Introduction: The Stroke Thombolytic Predictive Instrument (Stroke TPI), derived on data from the first 5 randomized clinical trials of standard dose rtPA, predicts the probability of good and bad outcomes with and without rtPA. We sought to rebuild and externally validate a simpler Stroke TPI to support implementation in routine clinical care. Methods: Using a derivation cohort of 1,983 patients from a combined database of randomized clinical trials (NINDS 1 and 2; ATLANTIS A and B; ECASS 2), we simplified the Stroke TPI by: 1) removing lower credibility interaction terms; and 2) exploring reduced stroke severity scores, including previously developed 8-item and 3-item measures. Additionally, we included alternative thresholds of a good 90-day functional outcome (i.e. prediction of both modified Rankin Score [mRS] ≤ 1 and mRS ≤ 2). Bootstrapping methods were used for internal validation. External validation was performed on the ECASS 3 trial (n=821). Results: The following 6 variables were included to predict good outcomes: age, systolic blood pressure (SBP), diabetes, stroke severity, symptom onset to treatment time (OTT) and rtPA therapy. Treatment effect modifiers (interaction terms) included OTT and SBP. For the models predicting a bad outcome (mRS ≥ 5), significant variables included: age, stroke severity, and serum glucose. rtPA therapy did not change the risk of a poor outcome. As compared to models using the full NIHSS, models employing the 3-item severity score showed similar discrimination, with c-statistics on bootstrap (internal) validation of: 0.76 (mRS ≤ 1); 0.78 (mRS ≤ 2); and 0.76 (mRS ≥ 5), and with excellent calibration. External validation on ECASS 3 showed similar performance (c-statistics 0.75 [mRS ≤ 1] and 0.80 [mRS ≤ 2]), with good calibration. Conclusion: A simpler prediction model using a 3-item, instead of the 15-item NIHSS stroke severity score, has similar prognostic value and may be easier to use in routine care. Future studies are needed to test whether the reduced model can improve treatment rates, time to treatment, and outcomes.
Author Disclosures: D.M. Kent: Research Grant; Significant; Genentech. R. Ruthazer: Research Grant; Significant; Genentech. C. Decker: Research Grant; Significant; Genentech. P.G. Jones: Research Grant; Significant; Genentech. J.L. Saver: None. E. Bluhmki: Research Grant; Significant; Genentech. J.A. Spertus: Research Grant; Significant; Genentech.
- © 2015 by American Heart Association, Inc.