Changes in ImPACT Cognitive Subtest Networks Following Sport-Related Concussion

Minimal Detectable Change for the ImPACT Subtests at Baseline

OBJECTIVE

To establish the minimal detectable change (MDC) of the subtests that comprise the composite scores from remotely administered Immediate Post-Concussion Assessment and Cognitive Testing (ImPACT) baselines.

METHOD

Remote ImPACT baseline data from 172 (male = 45, female = 127) National Collegiate Athletic Association Division I student-athletes from the 2020 and 2021 athletic preseasons were used to calculate the MDC at the 95%, 90%, and 80% confidence intervals (CIs) for all subtest scores used to generate the four core composite scores and the impulse control composite.

RESULTS

The MDCs for the verbal memory subtests at the 95% CI were 10.31 for word memory percent correct, 4.68 for symbol match total correct hidden, and 18.25 for three letters percentage correct. Visual memory subtest MDCs were 19.03 for design memory total percent correct and 4.90 for XO total correct memory. Visual motor speed subtest MDCs were 18.89 for XO total correct interference and 5.40 for three letters average counted correctly. Reaction time (RT) MDCs were 0.12 for XO average correct, 0.95 for symbol match average correct RT, and 0.28 for color match average correct. Impulse control MDCs were 5.97 for XO total incorrect and 1.15 for color match total commissions. One-way repeated measures MANOVA, repeated measures ANOVAs, and Wilcoxon signed-ranks test all suggested no significant difference between any subtests across two remote ImPACT baselines.

CONCLUSIONS

The ImPACT subtest scores did not significantly change between athletic seasons. Our study suggests the subtests be evaluated in conjunction with the composite scores to provide additional metrics for clinical interpretation.

Network analysis of neuropsychiatric symptoms in Alzheimer's disease

BACKGROUND

Neuropsychiatric symptoms due to Alzheimer's disease (AD) and mild cognitive impairment (MCI) can decrease quality of life for patients and increase caregiver burden. Better characterization of neuropsychiatric symptoms and methods of analysis are needed to identify effective treatment targets. The current investigation leveraged the National Alzheimer's Coordinating Center (NACC) Uniform Data Set (UDS) to examine the network structure of neuropsychiatric symptoms among symptomatic older adults with cognitive impairment.

METHODS

The network relationships of behavioral symptoms were estimated from Neuropsychiatric Inventory Questionnaire (NPI-Q) data acquired from 12,494 older adults with MCI and AD during their initial visit. Network analysis provides insight into the relationships among sets of symptoms and allows calculation of the strengths of the relationships. Nodes represented individual NPI-Q symptoms and edges represented the pairwise dependency between symptoms. Node centrality was calculated to determine the relative importance of each symptom in the network.

RESULTS

The analysis showed patterns of connectivity among the symptoms of the NPI-Q. The network (M = .28) consisted of mostly positive edges. The strongest edges connected nodes within symptom domain. Disinhibition and agitation/aggression were the most central symptoms in the network. Depression/dysphoria was the most frequently endorsed symptom, but it was not central in the network.

CONCLUSIONS

Neuropsychiatric symptoms in MCI and AD are highly comorbid and mutually reinforcing. The presence of disinhibition and agitation/aggression yielded a higher probability of additional neuropsychiatric symptoms. Interventions targeting these symptoms may lead to greater neuropsychiatric symptom improvement overall. Future work will compare neuropsychiatric symptom networks across dementia etiologies, informant relationships, and ethnic/racial groups, and will explore the utility of network analysis as a means of interrogating treatment effects.

Network Analysis of Neuropsychiatric Symptoms in Alzheimer's Disease

Background: Neuropsychiatric symptoms due to Alzheimer's disease (AD) and mild cognitive impairment (MCI) can decrease quality of life for patients and increase caregiver burden. Better characterization of neuropsychiatric symptoms and methods of analysis are needed to identify effective treatment targets. The current investigation leveraged the National Alzheimer's Coordinating Center (NACC) Uniform Data Set (UDS) to examine the network structure of neuropsychiatric symptoms among symptomatic older adults with cognitive impairment. Methods: The network relationships of behavioral symptoms was estimated from Neuropsychiatric Inventory Questionnaire (NPI-Q) data acquired from 12,494 older adults with MCI and AD during their initial visit. Network analysis provides insight into the relationships among sets of symptoms and allows calculation of the strengths of the relationships. Nodes represented individual NPI-Q symptoms and edges represented the pairwise dependency between symptoms. Node centrality was calculated to determine the relative importance of each symptom in the network. Results: The analysis showed patterns of connectivity among the symptoms of the NPI-Q. The network ( M =.28) consisted of mostly positive edges. The strongest edges connected nodes within symptom domain. Disinhibition and agitation/aggression were the most central symptoms in the network. Depression/dysphoria was the most frequently endorsed symptom, but it was not central in the network. Conclusions: Neuropsychiatric symptoms in MCI and AD are highly comorbid and mutually reinforcing. The presence of disinhibition and agitation/aggression yielded a higher probability of additional neuropsychiatric symptoms. Interventions targeting these symptoms may lead to greater neuropsychiatric symptom improvement overall. Future work will compare neuropsychiatric symptom networks across dementia etiologies, informant relationships, and ethnic/racial groups, and will explore the utility of network analysis as a means of interrogating treatment effects.