- Email: [email protected]
SIGNS OF EARLY COGNITIVE DECLINE WITHIN CONNECTED SPEECH: EVIDENCE FROM THE WISCONSIN REGISTRY FOR ALZHEIMER'S PREVENTION (WRAP)
P812
Poster Presentations: Monday, July 17, 2017
the Clinical Dementia Rating (CDR) scores. Conclusions: BPSD are found in even the very early stage of Alzheimer’s disease, apathy and depression being the most common symptoms. Physicians should be aware of this when managing dementia patients.
P2-455
WITHDRAWN
P2-456
ANALYSIS OF MACROLINGUISTIC DIMENSION IN INDIVIDUALS WITH ALZHEIMER’S DISEASE ORAL DISCOURSE
Juliana Onofre de Lira1, Karin Zazo Ortiz2, Paulo Henrique Ferreira Bertolucci3, Thais Minett4, 1University of Brasilia, Brasilia, Brazil; 2 Federal University of S~ ao Paulo, S~ao Paulo, Brazil; 3Federal University of S~ ao Paulo - UNIFESP, S~ ao Paulo, Brazil; 4University of Cambridge, Cambridge, United Kingdom. Contact e-mail: [email protected] Background: Alzheimer’s disease (AD) is a degenerative illness characterized by memory impairment and other cognitive functions, which might include language. Discourse is a natural form of communication, which can analyze language processing, organized in two interactive dimensions useful for evaluation: microlinguistic, which is responsible for phonological, lexical and syntactic measures and macrolinguistic (MaD), responsible for inter-phrasal functions as local cohesion and coherence besides global meaning. In terms of MaD, studies have shown great relevance in language assessment in AD. Nonetheless, there is a large diversity of methodologies proposed in the literature. Hence, this study aims to identify which MaD variables can better differentiate individuals with AD from the controls in oral discourse. Methods: Cross-sectional study that evaluated 121 individuals above 60 years old, divided in 2 groups: 60 control subjects and 60 AD patients, both with more than 4 years of education level. All participants answered the Mini Mental State Examination (MMSE), the cognitive subscale of the ‘Alzheimer Disease Assessment Scale’ (ADAS-Cog) and the individuals had been requested to tell a story about seven pictures that we presented to them. It was analyzed: content-related complete propositions, no-content-related complete propositions, incomplete propositions, macropropositions, appropriate local coherence, appropriate global coherence, modalizations, main information units. It was used linear regression to observe the differences between the groups and after that, it was used logistic regression (SFLR) to identify the most relevant MaD items, with variables that significantly distinguished between the two groups into the anterior regression analysis. Results: Linear regression analysis has shown worst performance in AD patients in content-related complete propositions b¼-0,52 (CI¼-0,38 to -0,19, p<0,001*), incomplete propositions b¼-0,47 (CI¼0,10 to 0,23, p<0,001*), macropropositions b¼-0,53 (CI¼-2,17 to -1,17, p<0,001*), main information units b¼-0,58 (CI¼-4,86 to -2,74, p<0,001*), cohesive devices b¼0,65 (CI¼-0,16 to -0,10, p<0,001*) and cohesive ruptures b¼0,52 (CI¼0,03 to 0,06, p<0,001*). It was observed that three variables were
selected for the logistic regression model: content-related complete propositions, macropropositions and cohesives devices. Conclusions: Content-related complete propositions, macropropositions and cohesives devices were considered better to differentiate individuals with AD from controls in oral discourse MaD analysis.
P2-457
SIGNS OF EARLY COGNITIVE DECLINE WITHIN CONNECTED SPEECH: EVIDENCE FROM THE WISCONSIN REGISTRY FOR ALZHEIMER’S PREVENTION (WRAP)
Kimberly D. Mueller1, Rebecca L. Koscik1, Lyn S. Turkstra2, Kristina M. Fiscus3, Sarah K. Riedeman3, Lindsay R. Clark4, Bruce P. Hermann5, Sterling C. Johnson1,4,6, 1Wisconsin Alzheimer’s Institute, University of Wisconsin School of Medicine and Public Health, Madison, WI, USA; 2Department of Communication Sciences and Disorders, University of Wisconsin - Madison, Madison, WI, USA; 3 University of Wisconsin - Madison, Madison, WI, USA; 4Wisconsin Alzheimer’s Disease Research Center, University of Wisconsin School of Medicine and Public Health, Madison, WI, USA; 5Department of Neurology, School of Medicine and Public Health, University of Wisconsin-Madison, Madison, WI, USA; 6Geriatric Research Education and Clinical Center, William S. Middleton Memorial Veterans Hospital, Madison, WI, USA. Contact e-mail: [email protected] Background: Alzheimer’s disease (AD) is primarily characterized by early memory impairment; however, many patients show deficits in language across all stages of AD. Typical language testing is insensitive to early language problems that may manifest in discourse. We examined connected speech longitudinally in a group of late-middle-aged adults at risk for AD. We hypothesized that those with early Mild Cognitive Impairment (eMCI) would show decline in connected speech over time compared to cognitively healthy (CH) adults. Methods: First, we submitted connected speech measures from a picture description task to exploratory and confirmatory factor analyses (EFA, CFA) from a subgroup of cognitively healthy WRAP participants (n¼399; mean age¼6067, 67% female). Next, we examined resulting factor scores as outcomes in a subset of participants with speech samples obtained at 2 time points (n¼219), using a linear mixed effects model (LME), with fixed effects of time point and baseline cognitive status (CH/eMCI), and a random effect of intercept nested within subjects. Secondary analyses used logistic regression to investigate the effect of speech factors on cognitive status at latest visit. Results: The EFA/CFA factor structure (Fig 1, Table 1) met goodness-of-fit criteria. Participant characteristics for longitudinal analyses are presented in Table 2. Cognitive status at time 1 was a significant predictor of Semantic (p ¼.007) and Syntax (p <.001) factors, with a significant interaction of time and cognitive status for the Semantic factor (p ¼.04) (Table 3, Fig.2). Syntax was a significant predictor of eMCI (p <.0001), as was change in Fluency (p¼.01) (Table 4). Conclusions: This is the first study to demonstrate a confirmed factor structure of connected speech measures in a prospective AD-risk-enriched cohort. Evident are baseline differences between eMCI and CH in syntax complexity. Baseline syntax and change in Fluency were significant predictors of
0.08 0.11 0.11 0.10 0.37 0.71 0.70 0.55 0.07 0.25 0.16 0.40 -0.26 -0.21 -0.29 0.00 0.25 0.86 0.56 0.05 -1.15 0.17 -0.58 2.02 0.85 1.19 1.19 1.03 0.09 0.02 0.07 0.20 0.76 0.49 0.49 0.68 1
-0.02 -0.01 -0.05 0.26 Lexical Semantic Syntax Fluency
*p-values are compared to a Bonferroni-corrected alpha of .0125. 95% Confidence Interval, lower bound; 2 95% confidence interval, upper bound; 3 standard error of the mean; 4 Coefficient of Repeatability, 2.77*SEM.
0.62 0.33 0.32 0.52 0.77 0.50 0.49 0.69 0.95 1.01 1.02 1.03 0.07 -0.02 0.01 0.06
p-value* t ICC r a SD Mean SD Mean
1.00 1.04 1.02 1.08
SEM3 Within subject variance 95%CI LB1 SD diff Between Subject Mean Diff (Bias) Time 2 Time 1
Discourse Factor
Figure 2. Boxplots of Connected Speech Factor by Visit and Consensus Diagnosis at Speech Time 1 (unadjusted means).
Table 1 Relative and absolute reliability indices of connected speech factors in a subset of cognitively stable individuals at 2 time points
eMCI at the latest visit. Unexpectedly, participants with eMCI performed higher on the Semantic factor at baseline; however, they declined more steeply than the CH group over time. Future analyses will continue to examine longitudinal relationships among speech factors and subtypes of cognitive impairment (memory, executive function, language), which may contribute to early identification of and intervention for AD.
95%CI UB2
Figure 1. Conceptual model submitted to confirmatory factor analysis using the cross-validation subsample(N¼149). Note: CFA met the following satisfactory fit indices: c2¼35.63, CFI ¼ .99, NNFI ¼ .99, RMSEA¼.04, 90% confidence interval¼.00, .08, GFI¼.98, AGFI¼.97, SRMR ¼ .07. Definitions: SUID is Semantic Unit Idea Density (number of information units/total words). Type-token ratio: number of unique words/total words. Pronoun index: total pronouns divided by nouns + pronouns. Maze Index: total number of revisions, repetitions, and filled pauses/total words. Verb Index: total number of verbs/utterances. Grammatical complexity: The number of grammatical relations that mark syntactic embeddings divided by the total number of grammatical relations. Density: ratio of the propositions corresponding to verbs, adjectives, adverbs, prepositions and conjunctions to the total number of words (excluding repetitions and fillers).
0.23 0.32 0.32 0.28
P813 CR4
Poster Presentations: Monday, July 17, 2017
P814
Poster Presentations: Monday, July 17, 2017
Table 2 Participant Demographics and Cognitive Characteristics of Linear Mixed-effects Regression Sample Variable
Total Sample
Cognitively Healthy
Early MCI
p-value
n, % Age at Speech Sample 1 Age at Speech Sample 2 Sex (F/M, %F) APOE-ε4 allele, ε4/non-ε4(%ε4) Family History (pos/neg) WRAT-3 Reading AVLT-Total Score Speed-Flexibility y Working Memory y Verbal Learning & Memory y Immediate Memory y
219 62.7 (6.5) 63.8 (6.4) 147/72 (67%) 94/125(43%) 185/34 (85%) 106.2 (9.4) 50.4 (9.4)
184 (84) 62.3 (6.6) 63.4 (6.6) 130/17 (59%) 79/105(43%) 156/28 (84%) 106.1(9.4) 52.1 (8.6) .23 (1.1) .14(1.0) .14(1.0) .17(1.1)
35 (16) 64.6 (5.4) 65.7 (5.4) 17/18(48%) 15/20(48%) 30/5 (85%) 106.7 (9.6) 41.7 (8.4) -.95 (.93) .99 (.91) -1.21(1.1) -.78(.88)
0.05 0.05 0.01* 0.57 0.84 0.64 <.0001** <.0001** <.0001** <.0001** <.0001**
y
Speed-Flexibility, Working Memory, Verbal Learning & Memory, and Immediate Memory are z-factor scores as described in Dowling et al., 2010. *Statistically significant at p<.05; **Statistically significant at p<.001.
Table 3 Parameters resulting from linear mixed effects regression models Semantic
Syntax
Lexical
Fluency
Variable
b (SE)
95% CI
b (SE)
95% CI
b (SE)
95%CI
b (SE)
95% CI
Intercept Age (centered) Sex (female) WRAT-III standard score Speech Visit (1,2) Consensus Diagnosis (eMCI) Speech Visit (1,2) X Consensus Diagnosis
-0.251 (.52) -.001 (.01) .06 (.11) -.06 (.06) 0.081 (.09) 1.05 (.39)**
-1.3 to .75 -.02 to .02 -.15 to .27 -.17 to .04 -0.1 to .27 0.3 to 1.8
.63(.23)** -.01(.01) -.22(.11) .19(.06)*** -.08(.08) -.53(.15)***
.18 to 1.09 -.02 to .01 -.44 to .01 .08 to .31 -.24 to .06 -.81 to -.24
.19 (.23) -.005(.01) .04(.11) -.37(.05)*** -.23(.07)*** .22(.15)
-.24 to .65 -.02 to .01 -.18 to .26 .59 to -.09 -.37 to -.1 -.06 to .51
-.58(.23) -.01(.01) .41(.11)*** -.16(.06)** -.01(.07) -.05(.15)
-.10 to -.14 -.02 to .01 .19 to .63 -.27 to -.05 -.15 to .12 -.33 to .24
-.48(.24)*
-.94 to -.08
Abbreviations: SE, standard error; CI, confidence interval; ConsensusDx, consensus diagnosis of either early MCI (eMCI) or cognitively healthy(CH); WRAT-III, Wide Range Achievement Test-3, reading subtest. *Statistically significant at p<.05; **Statistically significant at p<.01; ***Statistically significant at p<.001.
Table 4 Speech factor predictors of Latest Consensus Diagnosis in logistic regression model Fluency Variables
b
Syntax SE
OR (95% CI)
b
Semantic SE
OR (95% CI)
b
SE
Lexical OR (95% CI)
b
SE
OR (95% CI)
Intercept -2.32 1.78 .10 (.002-3.1) -1.96 1.77 .14 (.004-4.4) -2.43 1.74 .09 (.002- 2.55) -2.59 1.72 .07 (.002-2.1) Gender -.79* .37 .45 (.22-.94) -1.03** .38 .35 (.17-.74) -.89* .35 .4 (.2-.82) -.93* .36 .39 (.19-.79) Age at Speech Time 1 .04 .03 1.0 (.98-1.1) .04 .03 1.04 (.73-1.7) .04 .02 1.05 (.98-1.1) .05 .03 1.05 (.99- 1.11) WRAT-III SS -.14 .20 .86 (.58-1.3) .09 .21 1.1 (.73-1.7) -.07 .19 .93 (.64-1.4) .02 .21 1.01 (.67-1.6) Factor Chg. -.48* .22 .62 (.39-.95) .25 .22 1.28 (.84-2.0) .02 .19 1.02 (.69-1.5) -.01 .20 .99 (.66-1.5) Factor Time 1 -.37 .22 .69 (.44-1.1) -.76** .26 .47 (.27-.76) .26 .25 1.3 (.99-1.1) .24 .22 1.3 (.82-1.98) Abbreviations: WRAT-III SS, Wide Range Achievement Test-3rd Edition, reading subtest, standard score; Factor Chg, Change in factor score from speech visit 1 to speech visit 2 (negative values ¼ declining performance overtime); OR, Odds Ratio; CI, Confidence Interval. *Statistically significant at p<.05; **Statistically significant at p<.01.
Poster Presentations: Monday, July 17, 2017
the Clinical Dementia Rating (CDR) scores. Conclusions: BPSD are found in even the very early stage of Alzheimer’s disease, apathy and depression being the most common symptoms. Physicians should be aware of this when managing dementia patients.
P2-455
WITHDRAWN
P2-456
ANALYSIS OF MACROLINGUISTIC DIMENSION IN INDIVIDUALS WITH ALZHEIMER’S DISEASE ORAL DISCOURSE
Juliana Onofre de Lira1, Karin Zazo Ortiz2, Paulo Henrique Ferreira Bertolucci3, Thais Minett4, 1University of Brasilia, Brasilia, Brazil; 2 Federal University of S~ ao Paulo, S~ao Paulo, Brazil; 3Federal University of S~ ao Paulo - UNIFESP, S~ ao Paulo, Brazil; 4University of Cambridge, Cambridge, United Kingdom. Contact e-mail: [email protected] Background: Alzheimer’s disease (AD) is a degenerative illness characterized by memory impairment and other cognitive functions, which might include language. Discourse is a natural form of communication, which can analyze language processing, organized in two interactive dimensions useful for evaluation: microlinguistic, which is responsible for phonological, lexical and syntactic measures and macrolinguistic (MaD), responsible for inter-phrasal functions as local cohesion and coherence besides global meaning. In terms of MaD, studies have shown great relevance in language assessment in AD. Nonetheless, there is a large diversity of methodologies proposed in the literature. Hence, this study aims to identify which MaD variables can better differentiate individuals with AD from the controls in oral discourse. Methods: Cross-sectional study that evaluated 121 individuals above 60 years old, divided in 2 groups: 60 control subjects and 60 AD patients, both with more than 4 years of education level. All participants answered the Mini Mental State Examination (MMSE), the cognitive subscale of the ‘Alzheimer Disease Assessment Scale’ (ADAS-Cog) and the individuals had been requested to tell a story about seven pictures that we presented to them. It was analyzed: content-related complete propositions, no-content-related complete propositions, incomplete propositions, macropropositions, appropriate local coherence, appropriate global coherence, modalizations, main information units. It was used linear regression to observe the differences between the groups and after that, it was used logistic regression (SFLR) to identify the most relevant MaD items, with variables that significantly distinguished between the two groups into the anterior regression analysis. Results: Linear regression analysis has shown worst performance in AD patients in content-related complete propositions b¼-0,52 (CI¼-0,38 to -0,19, p<0,001*), incomplete propositions b¼-0,47 (CI¼0,10 to 0,23, p<0,001*), macropropositions b¼-0,53 (CI¼-2,17 to -1,17, p<0,001*), main information units b¼-0,58 (CI¼-4,86 to -2,74, p<0,001*), cohesive devices b¼0,65 (CI¼-0,16 to -0,10, p<0,001*) and cohesive ruptures b¼0,52 (CI¼0,03 to 0,06, p<0,001*). It was observed that three variables were
selected for the logistic regression model: content-related complete propositions, macropropositions and cohesives devices. Conclusions: Content-related complete propositions, macropropositions and cohesives devices were considered better to differentiate individuals with AD from controls in oral discourse MaD analysis.
P2-457
SIGNS OF EARLY COGNITIVE DECLINE WITHIN CONNECTED SPEECH: EVIDENCE FROM THE WISCONSIN REGISTRY FOR ALZHEIMER’S PREVENTION (WRAP)
Kimberly D. Mueller1, Rebecca L. Koscik1, Lyn S. Turkstra2, Kristina M. Fiscus3, Sarah K. Riedeman3, Lindsay R. Clark4, Bruce P. Hermann5, Sterling C. Johnson1,4,6, 1Wisconsin Alzheimer’s Institute, University of Wisconsin School of Medicine and Public Health, Madison, WI, USA; 2Department of Communication Sciences and Disorders, University of Wisconsin - Madison, Madison, WI, USA; 3 University of Wisconsin - Madison, Madison, WI, USA; 4Wisconsin Alzheimer’s Disease Research Center, University of Wisconsin School of Medicine and Public Health, Madison, WI, USA; 5Department of Neurology, School of Medicine and Public Health, University of Wisconsin-Madison, Madison, WI, USA; 6Geriatric Research Education and Clinical Center, William S. Middleton Memorial Veterans Hospital, Madison, WI, USA. Contact e-mail: [email protected] Background: Alzheimer’s disease (AD) is primarily characterized by early memory impairment; however, many patients show deficits in language across all stages of AD. Typical language testing is insensitive to early language problems that may manifest in discourse. We examined connected speech longitudinally in a group of late-middle-aged adults at risk for AD. We hypothesized that those with early Mild Cognitive Impairment (eMCI) would show decline in connected speech over time compared to cognitively healthy (CH) adults. Methods: First, we submitted connected speech measures from a picture description task to exploratory and confirmatory factor analyses (EFA, CFA) from a subgroup of cognitively healthy WRAP participants (n¼399; mean age¼6067, 67% female). Next, we examined resulting factor scores as outcomes in a subset of participants with speech samples obtained at 2 time points (n¼219), using a linear mixed effects model (LME), with fixed effects of time point and baseline cognitive status (CH/eMCI), and a random effect of intercept nested within subjects. Secondary analyses used logistic regression to investigate the effect of speech factors on cognitive status at latest visit. Results: The EFA/CFA factor structure (Fig 1, Table 1) met goodness-of-fit criteria. Participant characteristics for longitudinal analyses are presented in Table 2. Cognitive status at time 1 was a significant predictor of Semantic (p ¼.007) and Syntax (p <.001) factors, with a significant interaction of time and cognitive status for the Semantic factor (p ¼.04) (Table 3, Fig.2). Syntax was a significant predictor of eMCI (p <.0001), as was change in Fluency (p¼.01) (Table 4). Conclusions: This is the first study to demonstrate a confirmed factor structure of connected speech measures in a prospective AD-risk-enriched cohort. Evident are baseline differences between eMCI and CH in syntax complexity. Baseline syntax and change in Fluency were significant predictors of
0.08 0.11 0.11 0.10 0.37 0.71 0.70 0.55 0.07 0.25 0.16 0.40 -0.26 -0.21 -0.29 0.00 0.25 0.86 0.56 0.05 -1.15 0.17 -0.58 2.02 0.85 1.19 1.19 1.03 0.09 0.02 0.07 0.20 0.76 0.49 0.49 0.68 1
-0.02 -0.01 -0.05 0.26 Lexical Semantic Syntax Fluency
*p-values are compared to a Bonferroni-corrected alpha of .0125. 95% Confidence Interval, lower bound; 2 95% confidence interval, upper bound; 3 standard error of the mean; 4 Coefficient of Repeatability, 2.77*SEM.
0.62 0.33 0.32 0.52 0.77 0.50 0.49 0.69 0.95 1.01 1.02 1.03 0.07 -0.02 0.01 0.06
p-value* t ICC r a SD Mean SD Mean
1.00 1.04 1.02 1.08
SEM3 Within subject variance 95%CI LB1 SD diff Between Subject Mean Diff (Bias) Time 2 Time 1
Discourse Factor
Figure 2. Boxplots of Connected Speech Factor by Visit and Consensus Diagnosis at Speech Time 1 (unadjusted means).
Table 1 Relative and absolute reliability indices of connected speech factors in a subset of cognitively stable individuals at 2 time points
eMCI at the latest visit. Unexpectedly, participants with eMCI performed higher on the Semantic factor at baseline; however, they declined more steeply than the CH group over time. Future analyses will continue to examine longitudinal relationships among speech factors and subtypes of cognitive impairment (memory, executive function, language), which may contribute to early identification of and intervention for AD.
95%CI UB2
Figure 1. Conceptual model submitted to confirmatory factor analysis using the cross-validation subsample(N¼149). Note: CFA met the following satisfactory fit indices: c2¼35.63, CFI ¼ .99, NNFI ¼ .99, RMSEA¼.04, 90% confidence interval¼.00, .08, GFI¼.98, AGFI¼.97, SRMR ¼ .07. Definitions: SUID is Semantic Unit Idea Density (number of information units/total words). Type-token ratio: number of unique words/total words. Pronoun index: total pronouns divided by nouns + pronouns. Maze Index: total number of revisions, repetitions, and filled pauses/total words. Verb Index: total number of verbs/utterances. Grammatical complexity: The number of grammatical relations that mark syntactic embeddings divided by the total number of grammatical relations. Density: ratio of the propositions corresponding to verbs, adjectives, adverbs, prepositions and conjunctions to the total number of words (excluding repetitions and fillers).
0.23 0.32 0.32 0.28
P813 CR4
Poster Presentations: Monday, July 17, 2017
P814
Poster Presentations: Monday, July 17, 2017
Table 2 Participant Demographics and Cognitive Characteristics of Linear Mixed-effects Regression Sample Variable
Total Sample
Cognitively Healthy
Early MCI
p-value
n, % Age at Speech Sample 1 Age at Speech Sample 2 Sex (F/M, %F) APOE-ε4 allele, ε4/non-ε4(%ε4) Family History (pos/neg) WRAT-3 Reading AVLT-Total Score Speed-Flexibility y Working Memory y Verbal Learning & Memory y Immediate Memory y
219 62.7 (6.5) 63.8 (6.4) 147/72 (67%) 94/125(43%) 185/34 (85%) 106.2 (9.4) 50.4 (9.4)
184 (84) 62.3 (6.6) 63.4 (6.6) 130/17 (59%) 79/105(43%) 156/28 (84%) 106.1(9.4) 52.1 (8.6) .23 (1.1) .14(1.0) .14(1.0) .17(1.1)
35 (16) 64.6 (5.4) 65.7 (5.4) 17/18(48%) 15/20(48%) 30/5 (85%) 106.7 (9.6) 41.7 (8.4) -.95 (.93) .99 (.91) -1.21(1.1) -.78(.88)
0.05 0.05 0.01* 0.57 0.84 0.64 <.0001** <.0001** <.0001** <.0001** <.0001**
y
Speed-Flexibility, Working Memory, Verbal Learning & Memory, and Immediate Memory are z-factor scores as described in Dowling et al., 2010. *Statistically significant at p<.05; **Statistically significant at p<.001.
Table 3 Parameters resulting from linear mixed effects regression models Semantic
Syntax
Lexical
Fluency
Variable
b (SE)
95% CI
b (SE)
95% CI
b (SE)
95%CI
b (SE)
95% CI
Intercept Age (centered) Sex (female) WRAT-III standard score Speech Visit (1,2) Consensus Diagnosis (eMCI) Speech Visit (1,2) X Consensus Diagnosis
-0.251 (.52) -.001 (.01) .06 (.11) -.06 (.06) 0.081 (.09) 1.05 (.39)**
-1.3 to .75 -.02 to .02 -.15 to .27 -.17 to .04 -0.1 to .27 0.3 to 1.8
.63(.23)** -.01(.01) -.22(.11) .19(.06)*** -.08(.08) -.53(.15)***
.18 to 1.09 -.02 to .01 -.44 to .01 .08 to .31 -.24 to .06 -.81 to -.24
.19 (.23) -.005(.01) .04(.11) -.37(.05)*** -.23(.07)*** .22(.15)
-.24 to .65 -.02 to .01 -.18 to .26 .59 to -.09 -.37 to -.1 -.06 to .51
-.58(.23) -.01(.01) .41(.11)*** -.16(.06)** -.01(.07) -.05(.15)
-.10 to -.14 -.02 to .01 .19 to .63 -.27 to -.05 -.15 to .12 -.33 to .24
-.48(.24)*
-.94 to -.08
Abbreviations: SE, standard error; CI, confidence interval; ConsensusDx, consensus diagnosis of either early MCI (eMCI) or cognitively healthy(CH); WRAT-III, Wide Range Achievement Test-3, reading subtest. *Statistically significant at p<.05; **Statistically significant at p<.01; ***Statistically significant at p<.001.
Table 4 Speech factor predictors of Latest Consensus Diagnosis in logistic regression model Fluency Variables
b
Syntax SE
OR (95% CI)
b
Semantic SE
OR (95% CI)
b
SE
Lexical OR (95% CI)
b
SE
OR (95% CI)
Intercept -2.32 1.78 .10 (.002-3.1) -1.96 1.77 .14 (.004-4.4) -2.43 1.74 .09 (.002- 2.55) -2.59 1.72 .07 (.002-2.1) Gender -.79* .37 .45 (.22-.94) -1.03** .38 .35 (.17-.74) -.89* .35 .4 (.2-.82) -.93* .36 .39 (.19-.79) Age at Speech Time 1 .04 .03 1.0 (.98-1.1) .04 .03 1.04 (.73-1.7) .04 .02 1.05 (.98-1.1) .05 .03 1.05 (.99- 1.11) WRAT-III SS -.14 .20 .86 (.58-1.3) .09 .21 1.1 (.73-1.7) -.07 .19 .93 (.64-1.4) .02 .21 1.01 (.67-1.6) Factor Chg. -.48* .22 .62 (.39-.95) .25 .22 1.28 (.84-2.0) .02 .19 1.02 (.69-1.5) -.01 .20 .99 (.66-1.5) Factor Time 1 -.37 .22 .69 (.44-1.1) -.76** .26 .47 (.27-.76) .26 .25 1.3 (.99-1.1) .24 .22 1.3 (.82-1.98) Abbreviations: WRAT-III SS, Wide Range Achievement Test-3rd Edition, reading subtest, standard score; Factor Chg, Change in factor score from speech visit 1 to speech visit 2 (negative values ¼ declining performance overtime); OR, Odds Ratio; CI, Confidence Interval. *Statistically significant at p<.05; **Statistically significant at p<.01.