What predicts poor outcome after successful thrombectomy in late time windows?

BACKGROUND: Thrombectomy for acute ischemic stroke treatment leads to improved outcomes, but many patients do not achieve a good outcome despite successful reperfusion. We determined predictors of poor outcome after successful thrombectomy (TICI 2b-3) with an emphasis on modifiable factors. METHODS: Patients from the randomized DEFUSE 3 trial who underwent thrombectomy with TICI 2b-3 revascularization were included. Primary outcome was a poor outcome at 90 days (modified Rankin Scale score 3-6). RESULTS: 70 patients were included. Poor outcome patients were older (73.5 vs 66.5 years; P=0.01), more likely to be female (68% vs 39%; P=0.02), had higher NIHSS scores (20 vs 13; P<0.001), and had poor cerebral perfusion collaterals (hypoperfusion intensity ratio) (median 0.45 vs 0.38; P=0.03). Following thrombectomy, poor outcome patients had larger 24 hour' core infarctions (median 59.5 vs 29.9 mL; P=0.01), more core infarction growth (median 33.6 vs 13.4 mL; P<0.001), and more mild (65% vs 50%; P=0.02) and severe (18% vs 0%; P=0.01) reperfusion hemorrhage. In a logistic regression analysis, the presence of any reperfusion hemorrhage (OR 3.3 [95% CI, 1.67 to 5]; P=0.001), age (OR 1.1 [95% CI, 1.03 to 1.11], P=0.004), higher NIHSS (OR 1.25 [95% CI, 1.07 to 1.41], P=0.002), and time from imaging to femoral artery puncture (OR 5 [95% CI, 1.16 to 16.67], P=0.03) independently predicted poor outcomes. CONCLUSIONS: In late time windows, both mild and severe reperfusion hemorrhage were associated with poor outcomes. Older age, higher NIHSS, and increased time from imaging to arterial puncture were also associated with poor outcomes despite successful revascularization. TRIAL REGISTRATION: https://clinicaltrials.gov/ct2/show/NCT02586415.

Development of a Mobile Tool That Semiautomatically Screens Patients for Stroke Clinical Trials.

BACKGROUND AND PURPOSE: Despite several national coordinated research networks, enrollment in many cerebrovascular trials remains challenging. An electronic tool was needed that would improve the efficiency and efficacy of screening for multiple simultaneous acute clinical stroke trials by automating the evaluation of inclusion and exclusion criteria, improving screening procedures and streamlining the communication process between the stroke research coordinators and the stroke clinicians. METHODS: A multidisciplinary group consisting of physicians, study coordinators, and biostatisticians designed and developed an electronic clinical trial screening tool on a HIPAA (Health Insurance Portability and Accountability Act)-compliant platform. RESULTS: A web-based tool was developed that uses branch logic to determine eligibility for simultaneously enrolling clinical trials and automatically notifies the study coordinator teams about eligible patients. After 12 weeks of use, 225 surveys were completed, and 51 patients were enrolled in acute stroke clinical trials. Compared with the 12 weeks before implementation of the tool, there was an increase in enrollment from 16.5% of patients screened to 23.4% of patients screened (P<0.05). Clinicians and coordinators reported increased satisfaction with the process and improved ease of screening. CONCLUSIONS: We created a semiautomated electronic screening tool that uses branch logic to screen patients for stroke clinical trials. The tool has improved efficiency and efficacy of screening, and it could be adapted for use at other sites and in other medical fields.