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A web-based normative calculator for the uniform data set (UDS) neuropsychological test battery
INTRODUCTION: With the recent publication of new criteria for the diagnosis of preclinical Alzheimer's disease (AD), there is a need for neuropsychological tools that take premorbid functioning into account in order to detect subtle cognitive decline. Using demographic adjustments is one method...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2011
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3308021/ https://www.ncbi.nlm.nih.gov/pubmed/22078663 http://dx.doi.org/10.1186/alzrt94 |
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author | Shirk, Steven D Mitchell, Meghan B Shaughnessy, Lynn W Sherman, Janet C Locascio, Joseph J Weintraub, Sandra Atri, Alireza |
author_facet | Shirk, Steven D Mitchell, Meghan B Shaughnessy, Lynn W Sherman, Janet C Locascio, Joseph J Weintraub, Sandra Atri, Alireza |
author_sort | Shirk, Steven D |
collection | PubMed |
description | INTRODUCTION: With the recent publication of new criteria for the diagnosis of preclinical Alzheimer's disease (AD), there is a need for neuropsychological tools that take premorbid functioning into account in order to detect subtle cognitive decline. Using demographic adjustments is one method for increasing the sensitivity of commonly used measures. We sought to provide a useful online z-score calculator that yields estimates of percentile ranges and adjusts individual performance based on sex, age and/or education for each of the neuropsychological tests of the National Alzheimer's Coordinating Center Uniform Data Set (NACC, UDS). In addition, we aimed to provide an easily accessible method of creating norms for other clinical researchers for their own, unique data sets. METHODS: Data from 3,268 clinically cognitively-normal older UDS subjects from a cohort reported by Weintraub and colleagues (2009) were included. For all neuropsychological tests, z-scores were estimated by subtracting the raw score from the predicted mean and then dividing this difference score by the root mean squared error term (RMSE) for a given linear regression model. RESULTS: For each neuropsychological test, an estimated z-score was calculated for any raw score based on five different models that adjust for the demographic predictors of SEX, AGE and EDUCATION, either concurrently, individually or without covariates. The interactive online calculator allows the entry of a raw score and provides five corresponding estimated z-scores based on predictions from each corresponding linear regression model. The calculator produces percentile ranks and graphical output. CONCLUSIONS: An interactive, regression-based, normative score online calculator was created to serve as an additional resource for UDS clinical researchers, especially in guiding interpretation of individual performances that appear to fall in borderline realms and may be of particular utility for operationalizing subtle cognitive impairment present according to the newly proposed criteria for Stage 3 preclinical Alzheimer's disease. |
format | Online Article Text |
id | pubmed-3308021 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2011 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-33080212012-03-21 A web-based normative calculator for the uniform data set (UDS) neuropsychological test battery Shirk, Steven D Mitchell, Meghan B Shaughnessy, Lynn W Sherman, Janet C Locascio, Joseph J Weintraub, Sandra Atri, Alireza Alzheimers Res Ther Research INTRODUCTION: With the recent publication of new criteria for the diagnosis of preclinical Alzheimer's disease (AD), there is a need for neuropsychological tools that take premorbid functioning into account in order to detect subtle cognitive decline. Using demographic adjustments is one method for increasing the sensitivity of commonly used measures. We sought to provide a useful online z-score calculator that yields estimates of percentile ranges and adjusts individual performance based on sex, age and/or education for each of the neuropsychological tests of the National Alzheimer's Coordinating Center Uniform Data Set (NACC, UDS). In addition, we aimed to provide an easily accessible method of creating norms for other clinical researchers for their own, unique data sets. METHODS: Data from 3,268 clinically cognitively-normal older UDS subjects from a cohort reported by Weintraub and colleagues (2009) were included. For all neuropsychological tests, z-scores were estimated by subtracting the raw score from the predicted mean and then dividing this difference score by the root mean squared error term (RMSE) for a given linear regression model. RESULTS: For each neuropsychological test, an estimated z-score was calculated for any raw score based on five different models that adjust for the demographic predictors of SEX, AGE and EDUCATION, either concurrently, individually or without covariates. The interactive online calculator allows the entry of a raw score and provides five corresponding estimated z-scores based on predictions from each corresponding linear regression model. The calculator produces percentile ranks and graphical output. CONCLUSIONS: An interactive, regression-based, normative score online calculator was created to serve as an additional resource for UDS clinical researchers, especially in guiding interpretation of individual performances that appear to fall in borderline realms and may be of particular utility for operationalizing subtle cognitive impairment present according to the newly proposed criteria for Stage 3 preclinical Alzheimer's disease. BioMed Central 2011-11-11 /pmc/articles/PMC3308021/ /pubmed/22078663 http://dx.doi.org/10.1186/alzrt94 Text en Copyright ©2011 Shirk et al.; licensee BioMed Central Ltd. http://creativecommons.org/licenses/by/2.0 This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Research Shirk, Steven D Mitchell, Meghan B Shaughnessy, Lynn W Sherman, Janet C Locascio, Joseph J Weintraub, Sandra Atri, Alireza A web-based normative calculator for the uniform data set (UDS) neuropsychological test battery |
title | A web-based normative calculator for the uniform data set (UDS) neuropsychological test battery |
title_full | A web-based normative calculator for the uniform data set (UDS) neuropsychological test battery |
title_fullStr | A web-based normative calculator for the uniform data set (UDS) neuropsychological test battery |
title_full_unstemmed | A web-based normative calculator for the uniform data set (UDS) neuropsychological test battery |
title_short | A web-based normative calculator for the uniform data set (UDS) neuropsychological test battery |
title_sort | web-based normative calculator for the uniform data set (uds) neuropsychological test battery |
topic | Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3308021/ https://www.ncbi.nlm.nih.gov/pubmed/22078663 http://dx.doi.org/10.1186/alzrt94 |
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