3 results
An example of medical device-based projection of clinical trial enrollment: Use of electrocardiographic data to identify candidates for a trial in acute coronary syndromes
- Harry P. Selker, Manlik Kwong, Robin Ruthazer, Sheeona Gorman, Giuliana Green, Elizabeth Patchen, James E. Udelson, Howard A. Smithline, Michael R. Baumann, Paul A. Harris, Rashmee U. Shah, Sarah J. Nelson, Theodora Cohen, Elizabeth B. Jones, Brien A. Barnewolt, Andrew E. Williams
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- Journal:
- Journal of Clinical and Translational Science / Volume 2 / Issue 6 / December 2018
- Published online by Cambridge University Press:
- 14 May 2019, pp. 377-383
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Background:
To identify potential participants for clinical trials, electronic health records (EHRs) are searched at potential sites. As an alternative, we investigated using medical devices used for real-time diagnostic decisions for trial enrollment.
Methods:To project cohorts for a trial in acute coronary syndromes (ACS), we used electrocardiograph-based algorithms that identify ACS or ST elevation myocardial infarction (STEMI) that prompt clinicians to offer patients trial enrollment. We searched six hospitals’ electrocardiograph systems for electrocardiograms (ECGs) meeting the planned trial’s enrollment criterion: ECGs with STEMI or > 75% probability of ACS by the acute cardiac ischemia time-insensitive predictive instrument (ACI-TIPI). We revised the ACI-TIPI regression to require only data directly from the electrocardiograph, the e-ACI-TIPI using the same data used for the original ACI-TIPI (development set n = 3,453; test set n = 2,315). We also tested both on data from emergency department electrocardiographs from across the US (n = 8,556). We then used ACI-TIPI and e-ACI-TIPI to identify potential cohorts for the ACS trial and compared performance to cohorts from EHR data at the hospitals.
Results:Receiver-operating characteristic (ROC) curve areas on the test set were excellent, 0.89 for ACI-TIPI and 0.84 for the e-ACI-TIPI, as was calibration. On the national electrocardiographic database, ROC areas were 0.78 and 0.69, respectively, and with very good calibration. When tested for detection of patients with > 75% ACS probability, both electrocardiograph-based methods identified eligible patients well, and better than did EHRs.
Conclusion:Using data from medical devices such as electrocardiographs may provide accurate projections of available cohorts for clinical trials.
Red Blood Cell Transfusion: Experience in a Rural Aeromedical Transport Service
- George L. Higgins III, Michael R. Baumann, Kevin M. Kendall, Michael A. Watts, Tania D. Strout
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- Journal:
- Prehospital and Disaster Medicine / Volume 27 / Issue 3 / June 2012
- Published online by Cambridge University Press:
- 12 June 2012, pp. 231-234
- Print publication:
- June 2012
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Introduction
The administration of blood products to critically ill patients can be life-saving, but is not without risk. During helicopter transport, confined work space, communication challenges, distractions of multi-tasking, and patient clinical challenges increase the potential for error. This paper describes the in-flight red blood cell transfusion practice of a rural aeromedical transport service (AMTS) with respect to whether (1) transfusion following an established protocol can be safely and effectively performed, and (2) patients who receive transfusions demonstrate evidence of improvement in condition.
MethodsA two-year retrospective review of the in-flight transfusion experience of a single-system AMTS servicing a rural state was conducted. Data elements recorded contemporaneously for each transfusion were analyzed, and included hematocrit and hemodynamic status before and after transfusion. Compliance with an established transfusion protocol was determined through structured review by a multidisciplinary quality review committee.
ResultsDuring the study, 2,566 missions were flown with 45 subjects (1.7%) receiving in-flight transfusion. Seventeen (38%) of these transports were scene-to-facility and 28 (62%) were inter-facility. Mean bedside and in-flight times were 22 minutes (range 3-109 minutes) and 24 minutes (range 8-76 minutes), respectively. The most common conditions requiring transfusion were trauma (71%), cardiovascular (13%) and gastrointestinal (11%). An average of 2.4 liters (L) of crystalloid was administered pre-transfusion. The mean transfusion was 1.4 units of packed red blood cells. The percentages of subjects with pre- and post-transfusion systolic blood pressures of <90 mmHg were 71% and 29%, respectively. The pre- and post-transfusion mean arterial pressures were 62 mmHg and 82 mmHg, respectively. The pre- and post- transfusion mean hematocrit levels were 17.8% and 30.4%, respectively. At the receiving institution, 9% of subjects died in the Emergency Department, 18% received additional transfusion within 30 minutes of arrival, 36% went directly to the operating room, and 36% were directly admitted to intensive care. Thirty-one percent of subjects died prior to hospital discharge. There were no protocol violations or reported high-risk provider blood exposure incidents or transfusion complications. All transfusions were categorized as appropriate.
ConclusionsIn this rural AMTS, transfusion was an infrequent, likely life-saving, and potentially high-risk emergent therapy. Strict compliance with an established transfusion protocol resulted in appropriate and effective decisions, and transfusion proved to be a safe in-flight procedure for both patients and providers.
Higgins GL 3rd, Baumann MR, Kendall KM, Watts MA, Strout TD. Red blood cell transfusion: experience in a rural aeromedical transport service. Prehosp Disaster Med. 2012;27(3):1-4.
Contributors
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- By Brian Abaluck, Imran M. Ahmed, Torbjörn Åkerstedt, Sonia Ancoli-Israel, Anna Anund, Donna L. Arand, Isabelle Arnulf, Fiona C. Baker, Thomas J. Balkin, Christian R. Baumann, Michel Billiard, Michael H. Bonnet, Meredith Broderick, Christian Cajochen, Scott S. Campbell, Sarah Laxhmi Chellappa, Fabio Cirignotta, Yves Dauvilliers, David F. Dinges, Christopher L. Drake, Neil T. Feldman, Catherine S. Fichten, Charles F. P. George, Namni Goel, Christian Guilleminault, Shelby F. Harris, Melinda L. Jackson, Joseph Kaleyias, Göran Kecklund, William D. S. Killgore, Sanjeev V. Kothare, Andrew D. Krystal, Clete A. Kushida, Luc Laberge, Gert Jan Lammers, Christopher P. Landrigan, Sandrine H. Launois, Patrick Levy, Eva Libman, Yinghui Low, Jennifer L. Martin, Una D. McCann, Renee Monderer, Patricia J. Murphy, Sona Nevsimalova, Seiji Nishino, Eric A. Nofzinger, Maurice M. Ohayon, Masashi Okuro, Jean-Louis Pepin, Fabio Pizza, Anil N. Rama, David B. Rye, Paula K. Schweitzer, Hideto Shinno, Renaud Tamsier, Michael J. Thorpy, Astrid van der Heide, Hans P. A. Van Dongen, Mari Viola-Saltzman, Jim Waterhouse, Nathaniel F. Watson, Rajive Zachariah
- Edited by Michael J. Thorpy, Michel Billiard
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- Book:
- Sleepiness
- Published online:
- 04 February 2011
- Print publication:
- 27 January 2011, pp vii-x
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