Report for: Automated real-time text messaging as a means for rapidly identifying acute stroke patients for clinical trials

Title	Automated real-time text messaging as a means for rapidly identifying acute stroke patients for clinical trials
Published in	Trials, July 2014
DOI	10.1186/1745-6215-15-304
Pubmed ID	25073719
Authors	Kati Jegzentis, Tim Nowe, Peter Brunecker, Matthias Endres, Bernd Haferkorn, Christoph Ploner, Jens Steinbrink, Gerhard Jan Jungehulsing
Abstract	Recruiting stroke patients into acute treatment trials is challenging because of the urgency of clinical diagnosis, treatment, and trial inclusion. Automated alerts that identify emergency patients promptly may improve trial performance. The main purposes of this project were to develop an automated real-time text messaging system to immediately inform physicians of patients with suspected stroke and to test its feasibility in the emergency setting.

X Demographics

The data shown below were collected from the profiles of 5 X users who shared this research output. Click here to find out more about how the information was compiled.

Country	Count	As %
United Kingdom	3	60%
Unknown	2	40%

Type	Count	As %
Members of the public	3	60%
Scientists	1	20%
Practitioners (doctors, other healthcare professionals)	1	20%

Mendeley readers

The data shown below were compiled from readership statistics for 39 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Country	Count	As %
Unknown	39	100%

Readers by professional status	Count	As %
Researcher	6	15%
Student > Ph. D. Student	5	13%
Student > Master	4	10%
Professor > Associate Professor	3	8%
Other	3	8%
Other	7	18%
Unknown	11	28%

Readers by discipline	Count	As %
Medicine and Dentistry	7	18%
Neuroscience	4	10%
Computer Science	3	8%
Decision Sciences	2	5%
Nursing and Health Professions	2	5%
Other	8	21%
Unknown	13	33%

Automated real-time text messaging as a means for rapidly identifying acute stroke patients for clinical trials