Successful patient-oriented research requires that careful thought be given to trial design and conduct in order to provide the most accurate and efficient results. Heterogeneity of risk characteristics in acute ischemic stroke patients increases the likelihood of unmatched clinically relevant patient characteristics in comparative research and can result in underestimates of treatment effect. The use of accurate prediction models in the design of trials and analysis of data can address these potentially confounding issues and improve the accuracy and efficiency of stroke studies. This proposal aims to use logistic regression techniques to: 1: Assess the relationships between each of 11 routinely available acute physiology measures (blood pressure, heart rate, temperature, glucose, blood urea nitrogen, creatinine, sodium, potassium, billirubin, hematocrit and white blood count) and death in 2,250 critically ill acute ischemic stroke patients to create the Acute Physiology of Stroke Score (APSS). 2: Combine the APSS with a previously validated acute ischemic stroke model that predicts devastating outcome (nursing home level disability/death) and validate it in an independent data set. We will use the stroke subgroup of the Cerner critical illness data set as well as the RANTTAS and NINDS tPA clinical trial data sets to develop the score, validate it and improve our existing prediction model. This research will result in an improved method of predicting individual probability of devastating outcome in ischemic stroke patients and allow improved clinical stroke trial design and analysis. It will also provide a patient-oriented research basis for individual mentoring of trainees as well as contribute to the development of a novel 1 month clinical research elective to be offered to house staff and neuroscience students at the University of Virginia with the goal of increasing the proportion of trainees with clinical research training.

Agency
National Institute of Health (NIH)
Institute
National Institute of Neurological Disorders and Stroke (NINDS)
Type
Midcareer Investigator Award in Patient-Oriented Research (K24)
Project #
5K24NS052141-05
Application #
7637838
Study Section
NST-2 Subcommittee (NST)
Program Officer
Moy, Claudia S
Project Start
2005-08-29
Project End
2011-06-30
Budget Start
2009-07-01
Budget End
2011-06-30
Support Year
5
Fiscal Year
2009
Total Cost
$95,875
Indirect Cost
Name
University of Virginia
Department
Neurology
Type
Schools of Medicine
DUNS #
065391526
City
Charlottesville
State
VA
Country
United States
Zip Code
22904
Johnston, Karen C; Yan, Guofen (2011) Acute physiology of stroke score. Stroke 42:2336-8
Barrett, Kevin M; Ding, Yong Hong; Wagner, Douglas P et al. (2009) Change in diffusion-weighted imaging infarct volume predicts neurologic outcome at 90 days: results of the Acute Stroke Accurate Prediction (ASAP) trial serial imaging substudy. Stroke 40:2422-7
Wasiewski, Warren W; Johnston, Karen C (2009) Clinical trials, devices, unproven treatments, and clinical equipoise. Stroke 40:e441-2
Johnston, Karen C; Wagner, Douglas P (2006) Relationship between 3-month National Institutes of Health Stroke Scale score and dependence in ischemic stroke patients. Neuroepidemiology 27:96-100