Development and validation of a simplified Stroke-Thrombolytic Predictive Instrument.
OBJECTIVE
The Stroke-Thrombolytic Predictive Instrument (Stroke-TPI) predicts the probability of good and bad outcomes with and without recombinant tissue plasminogen activator (rtPA). We sought to rebuild and externally validate a simpler Stroke-TPI to support implementation in routine clinical care.


METHODS
Using the original derivation cohort of 1,983 patients from a combined database of randomized clinical trials (NINDS [National Institute of Neurological Disorders and Stroke] 1 and 2; ATLANTIS [Alteplase Thrombolysis for Acute Noninterventional Therapy in Ischemic Stroke] A and B; and ECASS [European Cooperative Acute Stroke Study] II), we simplified the Stroke-TPI by reducing variables and interaction terms and by exploring simpler (3- and 8-item) stroke severity scores. External validation was performed in the ECASS III trial (n = 821).


RESULTS
The following 6 variables were most predictive of good outcomes: age, systolic blood pressure, diabetes, stroke severity, symptom onset to treatment time, and rtPA therapy. Treatment effect modifiers included onset to treatment time and systolic blood pressure. For the models predicting a bad outcome (modified Rankin Scale [mRS] score ≥5), significant variables included age, stroke severity, and serum glucose. rtPA therapy did not change the risk of a poor outcome. Compared with models using the full NIH Stroke Scale, models using the 3-item severity score showed similar discrimination and excellent calibration. External validation on ECASS III showed similar performance (C statistics 0.75 [mRS score ≤1] and 0.80 [mRS score ≤2]).


CONCLUSIONS
A simpler model using a 3-item stroke severity score, instead of the 15-item NIH Stroke Scale, has similar prognostic value and may be easier to use in routine care. Future studies are needed to test whether it can improve process and clinical outcomes.
From the Predictive Analytics and Comparative Effectiveness Center (D.M.K., R.R.), Institute for Clinical Research and Health Policy Studies, Tufts Medical Center/Tufts University School of Medicine, Boston, MA; Saint Luke's Mid America Heart Institute (C.D., P.G.J., J.A.S.), Kansas City, MO; University of Missouri-Kansas City (C.D., P.G.J., J.A.S.); Stroke Center and Department of Neurology (J.L.S.), University of California, Los Angeles; and Boehringer Ingelheim (E.B.), Germany. dkent1@tuftsmedicalcenter.org.
David M
DM
Kent
From the Predictive Analytics and Comparative Effectiveness Center (D.M.K., R.R.), Institute for Clinical Research and Health Policy Studies, Tufts Medical Center/Tufts University School of Medicine, Boston, MA; Saint Luke's Mid America Heart Institute (C.D., P.G.J., J.A.S.), Kansas City, MO; University of Missouri-Kansas City (C.D., P.G.J., J.A.S.); Stroke Center and Department of Neurology (J.L.S.), University of California, Los Angeles; and Boehringer Ingelheim (E.B.), Germany.
Robin
R
Ruthazer
From the Predictive Analytics and Comparative Effectiveness Center (D.M.K., R.R.), Institute for Clinical Research and Health Policy Studies, Tufts Medical Center/Tufts University School of Medicine, Boston, MA; Saint Luke's Mid America Heart Institute (C.D., P.G.J., J.A.S.), Kansas City, MO; University of Missouri-Kansas City (C.D., P.G.J., J.A.S.); Stroke Center and Department of Neurology (J.L.S.), University of California, Los Angeles; and Boehringer Ingelheim (E.B.), Germany.
Carole
C
Decker
From the Predictive Analytics and Comparative Effectiveness Center (D.M.K., R.R.), Institute for Clinical Research and Health Policy Studies, Tufts Medical Center/Tufts University School of Medicine, Boston, MA; Saint Luke's Mid America Heart Institute (C.D., P.G.J., J.A.S.), Kansas City, MO; University of Missouri-Kansas City (C.D., P.G.J., J.A.S.); Stroke Center and Department of Neurology (J.L.S.), University of California, Los Angeles; and Boehringer Ingelheim (E.B.), Germany.
Philip G
PG
Jones
From the Predictive Analytics and Comparative Effectiveness Center (D.M.K., R.R.), Institute for Clinical Research and Health Policy Studies, Tufts Medical Center/Tufts University School of Medicine, Boston, MA; Saint Luke's Mid America Heart Institute (C.D., P.G.J., J.A.S.), Kansas City, MO; University of Missouri-Kansas City (C.D., P.G.J., J.A.S.); Stroke Center and Department of Neurology (J.L.S.), University of California, Los Angeles; and Boehringer Ingelheim (E.B.), Germany.
Jeffrey L
JL
Saver
From the Predictive Analytics and Comparative Effectiveness Center (D.M.K., R.R.), Institute for Clinical Research and Health Policy Studies, Tufts Medical Center/Tufts University School of Medicine, Boston, MA; Saint Luke's Mid America Heart Institute (C.D., P.G.J., J.A.S.), Kansas City, MO; University of Missouri-Kansas City (C.D., P.G.J., J.A.S.); Stroke Center and Department of Neurology (J.L.S.), University of California, Los Angeles; and Boehringer Ingelheim (E.B.), Germany.
Erich
E
Bluhmki
From the Predictive Analytics and Comparative Effectiveness Center (D.M.K., R.R.), Institute for Clinical Research and Health Policy Studies, Tufts Medical Center/Tufts University School of Medicine, Boston, MA; Saint Luke's Mid America Heart Institute (C.D., P.G.J., J.A.S.), Kansas City, MO; University of Missouri-Kansas City (C.D., P.G.J., J.A.S.); Stroke Center and Department of Neurology (J.L.S.), University of California, Los Angeles; and Boehringer Ingelheim (E.B.), Germany.
John A
JA
Spertus
D000368:Aged; D002545:Brain Ischemia / Q000175:diagnosis* / Q000628:therapy; D002543:Cerebral Hemorrhage / Q000175:diagnosis* / Q000628:therapy; D005260:Female; D005343:Fibrinolytic Agents / Q000627:therapeutic use; D006801:Humans; D008297:Male; D008875:Middle Aged; D012306:Risk; D020521:Stroke / Q000175:diagnosis* / Q000628:therapy*; D015912:Thrombolytic Therapy / Q000295:instrumentation* / Q000379:methods; D010959:Tissue Plasminogen Activator / Q000627:therapeutic use; D016896:Treatment Outcome
D005343:Fibrinolytic Agents; D010959:Tissue Plasminogen Activator