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O1‐05‐03: Stability of the diagnosis of mild cognitive impairment
Author(s) -
Petersen Ronald,
Knopman David,
Boeve Bradley,
Geda Yonas,
Ivnik Robert,
Pankratz Ver S.,
Cha Ruth,
Roberts Rosebud O.
Publication year - 2010
Publication title -
alzheimer's and dementia
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 6.713
H-Index - 118
eISSN - 1552-5279
pISSN - 1552-5260
DOI - 10.1016/j.jalz.2010.05.235
Subject(s) - concordance , dementia , cognitive impairment , medical diagnosis , neuropsychology , medicine , incidence (geometry) , cognition , pediatrics , disease , psychiatry , gerontology , pathology , physics , optics
Background: Intra-individual variability on cognitive testing increases with age and may be an underappreciated challenge to the early and accurate identification of Mild Cognitive Impairment (MCI). We previously reported high initial prevalence estimates of MCI from a community sample, the Adult Changes in Thought (ACT;E.Larson,PI) cohort. The current study aimed to examine the patterns of change in classification at a biennial follow-up to assess the stability of results in this elderly population. Methods: Cognitive examinations are conducted biennially and include tests known to be sensitive to the early effects of cognitive decline. Prevalence of MCI at timepoint1 and at timepoint2 was determined based on published definitions using individualized estimates of premorbid ability as benchmarks rather than age-referenced normative information. A cut-off of 1.5 standard deviations(sd) below these individualized premorbid estimates prompted classification into MCI subtypes. Trends across the two visits were assessed. Results: Of the first sequential 200 subjects, N 1⁄4 180 agreed to participate at timepoint1. Seventeen met criteria for dementia and were excluded from follow-up. Of the remaining participants, 113/163 had complete data at timepoint2. About 20% of participants diagnosed with MCI at baseline no longer met MCI criteria at follow-up and a similar number (18.5%) who were initially defined as ‘‘normal control’’ met criteria for MCI at timepoint2. Diagnostic stability across time points was seen in only 61% of the sample. Within the MCI diagnostic category, heterogeneity was noted as well, with many shifts between sub-types. In this sample, no specific measures or cognitive domains could be identified to suggest which participants would remain diagnostically stable versus those who did not. Conclusions: These data highlight the need to attend to intra-individual variability, which may influence the reliability of the MCI diagnosis. Although some argue that a wider range of within-person fluctuations on cognitive testing is a natural part of aging, others have suggested that these fluctuations are a hallmark of impending decline. Given the importance of early identification of cognitive decline predictive of incipient dementia, larger sample sizes and an analysis of broader patterns of change, perhaps including functional indices, might be necessary to accurately identify those individuals most at risk for dementia.