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Static balance impairments under dual-task conditions in MCI
P484
Poster Presentations: P3
vertebral arteries (VA, F VA) in response to changes in MAP. End-tidal CO 2 (ETCO 2) was recorded simultaneously. Stepwise multiple linear regression analysis was used to examine the effects of MAP, ET CO 2, group (0 for control, 1 for MCI), age and gender (0 for female, 1 for male) on V MCA, F ICA, and F VA (, percentage changes to baseline). Results: The range of variations in MAP induced by drug infusion was 65w143 mm Hg associated with a concomitant change in ETCO2 (range: 22w48 mm Hg). The regression equations derived were: VMCA ¼ 0.170*MAP + 0.530* ETCO2 + 0.189*Group + 0.252*Age, R ¼ 0.719, P < 0.001; FICA ¼ 0.212* ETCO2, R ¼ 0.237, P < 0.01; FVA ¼ 0.221*MAP + 0.262* ETCO2 + 0.256*Group, R ¼ 0.475, P < 0.001. Significantly different CBF responses to MAP and ETCO2 between the MCI and control groups were observed in the MCA and VA, but not in the ICA. No gender differences were observed. Conclusions: Cerebral autoregulatory dysfunction was detected in patients with MCI, most prominently in the MCA and posterior cerebral territory (supplied mainly by the VA). These findings suggest that cerebrovascular dysfunction is detectable at the early stage of AD. A cause-effect relationship has yet to be established. P3-091
STATIC BALANCE IMPAIRMENTS UNDER DUALTASK CONDITIONS IN MCI
Julia Leach, Martina Mancini, Jeffrey Kaye, Fay Horak, Tamara Hayes, Oregon Heath & Science University, Portland, Oregon, United States. Background: Motor changes precede cognitive changes in MCI and may be predictive of the development of MCI and later transition to dementia. Furthermore, cognitively impaired older adults are at an increased risk of falls due to decreased motor function and compromised balance. Although there is increasing evidence that both dynamic and static balance is compromised in this population, the relationship between MCI and postural control remains poorly understood. Methods: Nine volunteers enrolled in the Intelligent Systems for Assessing Aging Change (ISAAC) cohort study were recruited for this pilot study (4 naMCI, 3 aMCI, 2 cognitively-intact agematched controls; mean age, 80.8 6 6.7). Subjects wore six wireless inertial sensors (mounted on the left wrist, right wrist, left ankle, right ankle, lumbar, and trunk) for balance testing; only the results from the lumbar sensor are reported here. The protocol included seven trials of standing in place. One balance trial had no secondary task; the remaining six trials included secondary tasks that tapped into a variety of cognitive domains (working memory, attention, short- and long-term memory and executive function). Data were analyzed with a two-way, fixed effects analysis of variance (ANOVA). Post-hoc between-group comparisons were done using Tukey’s HSD criterion. Results: Several measures of static balance were examined; jerk (the time derivative (rate of change) of acceleration) showed significant differences across subjects. Figure 1 shows the mean value of jerk across each group and test condition. There was a significant effect of MCI status (F 2,42 ¼4.77, P¼0.01). Cross-group comparisons showed that this was due to a difference between the aMCI and control groups; although there was
a difference between naMCI and aMCI groups this did not reach significance. There were no effects of dual-task condition (F 6,42 ¼0.70, P¼0.65). Conclusions: These preliminary results suggest that jerk and other objective measures of quiet stance may help differentiate early stages of cognitive decline. Cognitive loading during balance testing amplifies postural instability and may make measures of quiet stance more sensitive. Further research will help determine if these measures predict increased fall risk and allow for better differentiation of MCI from healthy subjects. P3-092
SUBJECTIVE COGNITIVE COMPLAINT AND COGNITIVE PERFORMANCE AMONG OLDER ADULTS
Katherine Gifford1, Aaron Der2, Raymond Romano2, Brett Martin2, Nicole Cantwell2, Neil Kowall2, Angela Jefferson1, 1Vanderbilt University, Nashville, Tennessee, United States; 2Boston University, Boston, Massachusetts, United States. Background: Cognitive complaint is necessary to diagnosis mild cognitive impairment (MCI), yet no consensus exists for assessing such complaints. Common methods for assessing complaints are compared to cognitive performances among older adults with normal cognition (NC) and MCI. Methods: Participants included 112 NC (7668 years, 63% female) and 43 MCI individuals (7767 years, 51% female) from the Boston University Alzheimer’s Disease Center. Participants completed a survey including commonly administered cognitive complaint questions (e.g., Do you have problems with your memory? Do you think that your memory is worse than two years ago?), and a neuropsychological evaluation assessing episodic memory, executive functioning, attention, processing-speed and language. Results: Among NC participants, correlation analyses, adjusting for age, sex, education and race, revealed significant associations between several questions and multiple measures of memory performance (i.e., story-memory, list-learning) with correlation coefficients ranging from -0.24 to -0.20. Questions with the strongest association included—Do you feel that your everyday life is difficult now due to your memory decline? and Do other people say you ask the same question or repeat the same story?. Complaint questions were also correlated with processing-speed (r¼-0.25, Do you often have trouble finding the word you want to use in everyday conversation?) and language (r¼-0.29, Do you lose objects more often than you did previously?) but not executive functioning or attention (p>0.05). Among the MCI participants, multiple questions were significantly correlated with multiple measures of memory with coefficients ranging from -0.48 to -0.34. Questions with the strongest association to memory measures included—Do you have difficulty remembering where you placed objects? and Do you have trouble remembering things from one moment to the next? Questions were correlated with executive function (r-0.37, Do other people say you ask the same question or repeat the same story?) but no other domains (p>0.05). Conclusions: Findings suggest methods for assessing cognitive complaints may differentially relate to objective cognitive performance. Additional research is needed to better understand the underlying neuroanatomical substrates associated with cognitive complaints and best methods for distinguishing between worried-well complaints and complaints that may represent the earliest clinical signs of an underlying neurodegenerative process. P3-093
RATES OF CONVERSION TO MCI AND ALZHEIMER’S IN THE AUSTRALIAN IMAGING, BIOMARKERS AND LIFESTYLE (AIBL) COHORT OVER 36 MONTHS
Kathryn Ellis1, Paul Maruff2, Ralph Martins3, Colin Masters4, Simon McBride5, Lance Macaulay5, Christopher Rowe6, Stephanie RaineySmith7, Alan Rembach8, Greg Savage9, Cassandra Szoeke10, Kevin Taddei11, Victor Villemagne12, Ping Zhang13, David Ames14, AIBL Research Group15, 1University of Melbourne, Mental Health Research Institute, Parkville, Australia; 2CogState Ltd, Melbourne, Australia; 3Edith Cowan University, Perth, Australia; 4Mental Health Research Institute, Melbourne, Australia; 5CSIRO, Parkville, Australia; 6CSIRO, Heidelberg, Australia; 7Edith Cowan University, Joondalup, Australia; 8Mental Health Research Institute, Parkville, Melbourne, Australia; 9Macquarie University,
Poster Presentations: P3
vertebral arteries (VA, F VA) in response to changes in MAP. End-tidal CO 2 (ETCO 2) was recorded simultaneously. Stepwise multiple linear regression analysis was used to examine the effects of MAP, ET CO 2, group (0 for control, 1 for MCI), age and gender (0 for female, 1 for male) on V MCA, F ICA, and F VA (, percentage changes to baseline). Results: The range of variations in MAP induced by drug infusion was 65w143 mm Hg associated with a concomitant change in ETCO2 (range: 22w48 mm Hg). The regression equations derived were: VMCA ¼ 0.170*MAP + 0.530* ETCO2 + 0.189*Group + 0.252*Age, R ¼ 0.719, P < 0.001; FICA ¼ 0.212* ETCO2, R ¼ 0.237, P < 0.01; FVA ¼ 0.221*MAP + 0.262* ETCO2 + 0.256*Group, R ¼ 0.475, P < 0.001. Significantly different CBF responses to MAP and ETCO2 between the MCI and control groups were observed in the MCA and VA, but not in the ICA. No gender differences were observed. Conclusions: Cerebral autoregulatory dysfunction was detected in patients with MCI, most prominently in the MCA and posterior cerebral territory (supplied mainly by the VA). These findings suggest that cerebrovascular dysfunction is detectable at the early stage of AD. A cause-effect relationship has yet to be established. P3-091
STATIC BALANCE IMPAIRMENTS UNDER DUALTASK CONDITIONS IN MCI
Julia Leach, Martina Mancini, Jeffrey Kaye, Fay Horak, Tamara Hayes, Oregon Heath & Science University, Portland, Oregon, United States. Background: Motor changes precede cognitive changes in MCI and may be predictive of the development of MCI and later transition to dementia. Furthermore, cognitively impaired older adults are at an increased risk of falls due to decreased motor function and compromised balance. Although there is increasing evidence that both dynamic and static balance is compromised in this population, the relationship between MCI and postural control remains poorly understood. Methods: Nine volunteers enrolled in the Intelligent Systems for Assessing Aging Change (ISAAC) cohort study were recruited for this pilot study (4 naMCI, 3 aMCI, 2 cognitively-intact agematched controls; mean age, 80.8 6 6.7). Subjects wore six wireless inertial sensors (mounted on the left wrist, right wrist, left ankle, right ankle, lumbar, and trunk) for balance testing; only the results from the lumbar sensor are reported here. The protocol included seven trials of standing in place. One balance trial had no secondary task; the remaining six trials included secondary tasks that tapped into a variety of cognitive domains (working memory, attention, short- and long-term memory and executive function). Data were analyzed with a two-way, fixed effects analysis of variance (ANOVA). Post-hoc between-group comparisons were done using Tukey’s HSD criterion. Results: Several measures of static balance were examined; jerk (the time derivative (rate of change) of acceleration) showed significant differences across subjects. Figure 1 shows the mean value of jerk across each group and test condition. There was a significant effect of MCI status (F 2,42 ¼4.77, P¼0.01). Cross-group comparisons showed that this was due to a difference between the aMCI and control groups; although there was
a difference between naMCI and aMCI groups this did not reach significance. There were no effects of dual-task condition (F 6,42 ¼0.70, P¼0.65). Conclusions: These preliminary results suggest that jerk and other objective measures of quiet stance may help differentiate early stages of cognitive decline. Cognitive loading during balance testing amplifies postural instability and may make measures of quiet stance more sensitive. Further research will help determine if these measures predict increased fall risk and allow for better differentiation of MCI from healthy subjects. P3-092
SUBJECTIVE COGNITIVE COMPLAINT AND COGNITIVE PERFORMANCE AMONG OLDER ADULTS
Katherine Gifford1, Aaron Der2, Raymond Romano2, Brett Martin2, Nicole Cantwell2, Neil Kowall2, Angela Jefferson1, 1Vanderbilt University, Nashville, Tennessee, United States; 2Boston University, Boston, Massachusetts, United States. Background: Cognitive complaint is necessary to diagnosis mild cognitive impairment (MCI), yet no consensus exists for assessing such complaints. Common methods for assessing complaints are compared to cognitive performances among older adults with normal cognition (NC) and MCI. Methods: Participants included 112 NC (7668 years, 63% female) and 43 MCI individuals (7767 years, 51% female) from the Boston University Alzheimer’s Disease Center. Participants completed a survey including commonly administered cognitive complaint questions (e.g., Do you have problems with your memory? Do you think that your memory is worse than two years ago?), and a neuropsychological evaluation assessing episodic memory, executive functioning, attention, processing-speed and language. Results: Among NC participants, correlation analyses, adjusting for age, sex, education and race, revealed significant associations between several questions and multiple measures of memory performance (i.e., story-memory, list-learning) with correlation coefficients ranging from -0.24 to -0.20. Questions with the strongest association included—Do you feel that your everyday life is difficult now due to your memory decline? and Do other people say you ask the same question or repeat the same story?. Complaint questions were also correlated with processing-speed (r¼-0.25, Do you often have trouble finding the word you want to use in everyday conversation?) and language (r¼-0.29, Do you lose objects more often than you did previously?) but not executive functioning or attention (p>0.05). Among the MCI participants, multiple questions were significantly correlated with multiple measures of memory with coefficients ranging from -0.48 to -0.34. Questions with the strongest association to memory measures included—Do you have difficulty remembering where you placed objects? and Do you have trouble remembering things from one moment to the next? Questions were correlated with executive function (r-0.37, Do other people say you ask the same question or repeat the same story?) but no other domains (p>0.05). Conclusions: Findings suggest methods for assessing cognitive complaints may differentially relate to objective cognitive performance. Additional research is needed to better understand the underlying neuroanatomical substrates associated with cognitive complaints and best methods for distinguishing between worried-well complaints and complaints that may represent the earliest clinical signs of an underlying neurodegenerative process. P3-093
RATES OF CONVERSION TO MCI AND ALZHEIMER’S IN THE AUSTRALIAN IMAGING, BIOMARKERS AND LIFESTYLE (AIBL) COHORT OVER 36 MONTHS
Kathryn Ellis1, Paul Maruff2, Ralph Martins3, Colin Masters4, Simon McBride5, Lance Macaulay5, Christopher Rowe6, Stephanie RaineySmith7, Alan Rembach8, Greg Savage9, Cassandra Szoeke10, Kevin Taddei11, Victor Villemagne12, Ping Zhang13, David Ames14, AIBL Research Group15, 1University of Melbourne, Mental Health Research Institute, Parkville, Australia; 2CogState Ltd, Melbourne, Australia; 3Edith Cowan University, Perth, Australia; 4Mental Health Research Institute, Melbourne, Australia; 5CSIRO, Parkville, Australia; 6CSIRO, Heidelberg, Australia; 7Edith Cowan University, Joondalup, Australia; 8Mental Health Research Institute, Parkville, Melbourne, Australia; 9Macquarie University,