alexa Statistical Approaches to Assess the Effects of Disease
ISSN: 2155-6180

Journal of Biometrics & Biostatistics
Open Access

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Research Article

Statistical Approaches to Assess the Effects of Disease on Neurocognitive Function Over Time

Tracy L Bergemann1,6*, Paul Bangirana2,3, Michael J Boivin4,5, John E Connett1, Bruno J Giordani5 and Chandy C John7

1Division of Biostatistics, School of Public Health, University of Minnesota, Minneapolis, Minnesota, USA

2Department of Psychiatry, Makerere University School of Medicine, Kampala, Uganda

3Department of Public Health Sciences, Karolinska Institutet, Stockholm, Sweden

4International Neurologic and Psychiatric Epidemiology Program, College of Osteopathic Medicine, Michigan State University, East Lansing, Michigan, USA

5Neuropsychology Section, Department of Psychiatry, University of Michigan, Ann Arbor, Michigan

6Cardiac Rhythm Disease Management, Medtronic, Mounds View, Minnesota, USA

7Division of Global Pediatrics, Department of Pediatrics, University of Minnesota Medical School, Minneapolis, Minnesota, USA

*Corresponding Author:
Tracy L Bergemann
Division of Biostatistics
School of Public Health
University of Minnesota
Minneapolis, Minnesota, USA
E-mail: [email protected]

Received date: November 08, 2012; Accepted date: December 17, 2012; Published date: December 19, 2012

Citation: Bergemann TL, Bangirana P, Boivin MJ, Connett JE, Giordani BJ, et al.(2012) Statistical Approaches to Assess the Effects of Disease on Neurocognitive Function Over Time. J Biomet Biostat S7:016. doi: 10.4172/2155-6180.S7-016

Copyright: © 2012 Bergemann TL, et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

 

Abstract

 Introduction: Assessment of the effects of disease on neurocognitive outcomes in children over time presents several challenges. These challenges are particularly pronounced when conducting studies in low-income countries, where standardization and validation is required for tests developed originally in high-income countries. We present a statistical methodology to assess multiple neurocognitive outcomes over time. We address the standardization and adjustment for age in neurocognitive testing, present a statistical methodology for development of a global neurocognitive score, and assess changes in individual and global neurocognitive scores over time in a cohort of children with cerebral

malaria.
Methods: Ugandan children with cerebral malaria (CM, N = 44), uncomplicated malaria (UM, N = 54) and community controls (N = 89) were assessed by cognitive tests of working memory, executive attention and tactile learning at 0, 3, 6 and 24 months after recruitment. Tests were previously developed and validated for the local area. Test scores were adjusted for age, and a global score was developed based on the controls that combined the assessments of impairment in each neurocognitive domain. Global normalized Z-scores were computed for each of the three study groups. Model-based tests compare the Z-scores between groups.
Results: We found that continuous Z-scores gave more powerful conclusions than previous analyses of the dataset. For example, at all four time points, children with CM had significantly lower global Z-scores than controls and children with UM. Our methods also provide more detailed descriptions of longitudinal trends. For example, the Z-scores of children with CM improved from initial testing to 3 months, but remained at approximately the same level below those of controls or children with UM from 3 to 24 months. Our methods for combining scores are more powerful than tests of individual cognitive domains, as testing of the individual domains revealed differences at only some but not all time points.

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