Date of Award

January 2017

Document Type

Open Access Thesis

Degree Name

Medical Doctor (MD)

Department

Medicine

First Advisor

Kevin N. Sheth

Abstract

IV thrombolysis (rt-PA) for ischemic stroke treatment carries a substantial risk for symptomatic intracerebral hemorrhage (sICH) and adverse outcome. Our purpose was to develop a computationally simple and accurate clinical predictor of adverse outcome after rt-PA therapy.

Our derivation dataset consisted of 210 ischemic stroke patients receiving IV rt-PA from January 2009 until July 2013 at Yale New Haven Hospital. Our validation dataset included 303 patients who received IV rt-PA during the NINDS rt-PA trial. Predictive ability and goodness of fit were quantified by odds ratios (OR) and areas under the receiver operating characteristic curve (AUROC). Patient outcomes included sICH, brain swelling, 90-day severe outcome and 90-day mortality. Severe outcome was defined as 90-day modified Rankin Scale (mRS) scores ≥ 5, 90-day Barthel Index (BI) scores < 60 and 90-day Glasgow Outcome Scale (GOS) scores > 2.

Out of seventeen clinical parameters tested, three were independent predictors of sICH: prestroke mRS score (OR 1.54, P = 0.02), baseline National Institutes of Health Stroke Scale (NIHSS) score (OR 1.13, P = 0.002), and platelet count (OR 0.99, P = 0.04). We combined these three parameters to form the TURNP (Thrombolysis risk Using mRS, NIHSS and Platelets) score. For added simplicity, prestroke mRS score and baseline NIHSS score were also combined to form the TURN (Thrombolysis risk Using mRS and NIHSS) score, which predicted sICH without a significant drop in OR or AUROC. TURN predicted sICH with AUROC 0.74 (0.58 – 0.90) in the derivation dataset, and AUROC 0.65 (0.54 – 0.77) in the validation dataset. In the validation dataset, TURN predicted 24-hour brain swelling with AUROC 0.69 (0.63 - 0.75), 90-day mRS ≥ 5 with AUROC 0.83 (0.77, 0.89), 90-day BI < 60 with AUROC 0.81 (0.76 – 0.86), 90-day GOS > 2 with AUROC 0.81 (0.76 – 0.86) and 90-day mortality with AUROC 0.82 (0.76 – 0.88).

To improve the clinical utility of TURN, we developed and tested a mobile application Risk rtPA based on TURN for predicting 90-day outcome after rt-PA treatment. Risk rtPA returned predictions of severe outcome for a range of hypothetical patients with varying clinical characteristics, demonstrating broad applicability. This mobile application brings computationally simple prediction of post-thrombolysis risk to the bedside for real-time stroke prognostication.

Comments

This is an Open Access Thesis.

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