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HSCT is increasingly used for curative therapy for patients with high risk hematologic diseases. Existing research regarding the neurocognitive impact of HSCT on pediatric patients is notably variable. One area of identified risk is attention/working memory (WM) [Perkins et al., 2007]. The current study examines the degree to which difficulties in attention/WM are present prior to HSCT, as assessed using parent-report of working memory and cognitive tests of attention span and working memory.
Participants and Methods:
Participants were 19 children and adolescents ages 6-17 years (M= 9.63, SD= 3.22) who were enrolled in a prospective longitudinal study monitoring neurocognitive outcomes in children undergoing HSCT. Participants were eligible for this study if they were 2-18 years old at the time of transplant and had a diagnosis that qualified for an allogenic HSCT. Participants were ineligible if they had a pre-HSCT developmental delay, were non-English speaking, and had a prior HSCT or prior CAR T-cell therapy. Participants were 53% female and 95% Caucasian. Diagnoses in the current study sample included acute lymphoblastic leukemia (n=10), acute myeloid leukemia (n=8), and myelodysplastic syndrome (n=1).
Measures included were the Working Memory Index score from the Behavior Rating Inventory of Executive Function (BRIEF; Gioia et al., 2000) and the Digit Span subtest from the Wechsler Intelligence Scale for Children, Fourth Edition (WISC-IV; Wechsler, 2003) and the Wechsler Adult Intelligence Scale, Fourth Edition (WAIS-IV; Wechsler, 2008).
Results:
Mean scores on parent-reported WM scores and cognitive measures of attention/WM fell within normal limits, including the Digit Span Total score (M = 48.42, SD= 6.33), Digit Span Forward score (M = 47.28, SD = 9.9.83), and Digit Span Backward score (M = 48.94, SD = 6.31). However, further analyses suggested that between 11-32% of patients had scores falling at least one standard deviation below the mean on these measures, with more than half of the sample (52.6%) identified with at least one measured weakness in attention and WM. The most commonly identified weakness (33.3% of patients) was Digit Span Forward. Correlations between parent-reported WM issues and cognitive measures of attention and WM were generally strong, with parent report of WM significantly correlated with the Digit Span Total score (r(18)= -0.52, p=.02) and the Digit Span Forward score (r(18) = -0.51, p=.03). No correlations were found between Digit Span Backward and other measures of attention and WM.
There were no significant differences in WM scores between patients with ALL and AML. Additional analyses will examine potential contribution of medical factors (e.g., pre-HSCT treatment) to pre-HSCT performance on measures of attention and WM.
Conclusions:
These results suggest that, prior to undergoing HSCT, pediatric patients present with attention and WM issues. This finding has implications for research related to neurocognitive outcomes in HSCT, indicating the need to obtain pre-HSCT cognitive data in this area in order to fully understand potential change after HSCT. In addition, providers may need to consider adapting communication methods with patients during their transplant stay, given potential attention and WM issues within this population.
Evidence suggests that the most consistent cognitive impairment found in individuals experiencing posttraumatic stress disorder symptomology is verbal memory impairment (Johnsen & Asbjornsen, 2008). More specifically, research has shown that patients with PTSD perform poorer on verbal memory tasks relating to logical (story) memory than on word memory tasks, such as CVLT-III (Barrera-Valencia et al., 2017). While recent literature accounts for memory impairments related to PTSD, less is known about this relationship for individuals with mere trauma exposure compared to individuals without trauma exposure. The present research aims to determine if there is a significant impact on WMS-LM when compared to CVLT-III for individuals in a community sample that have been exposed to a traumatic event in their lifetime.
Participants and Methods:
One hundred nineteen patients presented to a community-based practice for neuropsychological evaluation. Patients were screened for trauma exposure during a clinical interview. Immediate and long delay trials of Wechsler Memory Scale IV Logical Memory (WMS-LM) were used to examine structured learning and memory and the California Verbal Learning Test (CVLT-II) immediate and long delay recalls were used to examine unstructured learning and memory. Out of the 119 patients, 36 patients reported trauma exposure. Twenty-five were diagnosed as “normal,” 62 were diagnosed with mild cognitive impairment, and 32 were diagnosed with dementia. A one-way MANOVA was conducted to examine the relationship across the multiple dependent variables.
Results:
There was a statistically significant difference in immediate recall in memory based on exposure to trauma, F (2, 116) = 3.28, p < .05; Wilk’s A = 0.947, partial n2 = .53, such that individuals with trauma exposure performed better. For long delay recall performance, there was a similar trend though it did not reach statistical significance F (2, 114) = 3.03, p = .052; Wilk’s A = 0.949, partial n2 = .51.
Conclusions:
Data showed that patients who reported trauma exposure scored significantly higher on immediate recall performance on CVLT and WMS-LM than those who did not report trauma exposure. Although research suggests that patients who were exposed to trauma often experience cognitive deficits on verbal memory tasks, evidence also shows that trauma exposure can lead to higher immediate recall performance in memory related to attentional allocation modeling (Hayes et al., 2012).
Pediatric traumatic brain injury (TBI) is the leading cause of disability in children under the age of 15, often resulting in executive function deficits and poor behavioral outcomes. Damage to white matter tracts may be a driving force behind these difficulties. We examined if whether 1) greater TBI severity was associated with worse neurobehavioral outcome, 2) greater TBI severity was associated with tract-based white matter microstructure, and 3) worse neurobehavioral outcome was associated with white matter microstructure.
Participants and Methods:
Twelve children with complicated-mild TBI (cmTBI; Mage=12.59, nmale=9), 17 with moderate-to-severe TBI (msTBI; Mage =11.50, nmale=11), and 21 with orthopedic injury (OI; Mage =11.60, nmale=16), 3.94 years post injury on average, were recruited from a large midwestern children’s hospital with a Level 1 Trauma Center. Parents completed the Behavior Rating Inventory of Executive Function (BRIEF) and Child Behavior Checklist (CBCL) while children completed 64-direction diffusion tensor imaging in a Siemens 3T scanner. White matter microstructure was quantified with FMRIB’s Diffusion Toolbox (FSLv6.0.4). Tract-Based Spatial Statistics computed fractional anisotropy (FA) and mean diffusivity (MD) for the cingulum bundle (CB), inferior fronto-occipital fasciculus (IFOF), superior longitudinal fasciculus (SLF), and uncinate fasciculus (UF), bilaterally.
Results:
Group differences were assessed using one-way ANOVA. Children with msTBI were rated as having worse Sluggish Cognitive Tempo on the CBCL than children with cmTBI and OI (p=.02, eta2=.143); no other parent-rated differences reached significance. Group differences were found in left SLF FA (p=.031; msTBI<cmTBI=OI) and approached significance in left UF FA (p=.062, eta2=.114; msTBI<OI). Group differences were also found in right IFOF MD (p=.048; msTBI>OI) and left SLF MD (p=.013; msTBI>cmTBI=OI). Bivariate correlations assessed cross-domain associations. Higher left IFOF FA was associated with better BRIEF Metacognitive Skills (r=-.301, p=.030) and CBCL School Competence (r=.280; p=.049). Higher left SLF FA was associated with better BRIEF Behavioral Regulation and Metacognitive Skills (r=-.331, p=.017 and r=-.291, p=.036, respectively), and CBCL School Competence and Attention Problems (r=.398, p=.004 and r=-.435, p=.001, respectively). Similarly, higher right UF FA was broadly associated with better neurobehavioral outcomes, including Behavioral Regulation and Metacognitive Skills (r=-.324, p=.019 and r=-.359, p=.009, respectively), and School Competence, Attention Problems, and Sluggish Cognitive Tempo (r=.328, p=.020, r=-.398, p=.003, and r=-.356, p=.010, respectively). Higher right CB MD was associated with worse Behavioral Regulation (r=.327, p=.018) and more Attention Problems (r=.278, p=.046); higher left and right SLF MD was associated with Sluggish Cognitive Tempo (r=.363, p=.008, r=.408, p=.003, respectively).
Conclusions:
Children with TBI, particularly msTBI, were rated as having cognitive slowing; while other anticipated group differences in neurobehavioral outcomes were not found, this appears driven by milder difficulties in cmTBI and OI groups. In fact, across CBCL and BRIEF subscales, children with msTBI were rated as approaching or exceeding a full standard deviation deficit based on normative data. TBI severity was also associated with white matter microstructure and cross-domain associations linked microstructure with observable neurobehavioral morbidities, suggesting a possible mechanism post-injury. Future longitudinal studies would be useful to examine the temporal evolution of deficits.
Psychosocial factors show a significant relationship between child behavior problems, family functioning, and cognitive performance in children with Sickle Cell Disease, marking those as important targets for intervention among this population. The purpose of this research is to address the effects of psychosocial factors impact on specific cognitive domains.
Participants and Methods:
Archival data from the National Institutes of Health’s Cooperative Study of Sickle Cell Disease was used. Data was restricted to individuals aged 14 or younger (N= 2,408), with 47.8% (n = 1,152) identified as female and 52.2% (n = 1,256) as male. Black or African American (96.9%, n = 2,334) children made up the majority of the sample, with the remainder coded as “other” (2.8%, n = 68). The measures utilized included the Wechsler Intelligence Scale for Children-Revised (WISC-R), Wechsler Intelligence Scale for Children-Third Edition (WISC-III), Peabody Picture Vocabulary Test (PPVT), Achenbach Child Behavior Checklist, and Family Environment Scale (FES).
Results:
Bivariate correlations were completed with significant correlations found between FES and performance on the WISC-R/III and PPVT. Supportiveness subscale on the FES demonstrated several statistically significant correlations with WAIS FSIQ (r = .21, p = .000) as well as the Information (r = .22, p = .000), Similarities (r = .17, p = .001), Arithmetic (r = .13, p = .021), Block Design (r = .11, p = .036), Vocabulary (r = .22, p = .000), Object Assembly (r = .12, p = .033), Comprehension (r = .19, p = .000), and Digit Span (r = .13, p = .014) subscales. A statistically significant correlation was observed between the PPVT and the Supportiveness subscale (r = .34, p = .000).
Conclusions:
Various areas of cognitive functioning are affected by family dynamics. Improvement in family functioning would benefit the cognitive functioning of children with SCD. To increase aspects of family functioning including supportiveness, early identification of children with SCD, targeted interventions, and family and/or individual therapy for caregivers are suggested.
Multiple sclerosis (MS), an inflammatory autoimmune disease of the central nervous system, is characterized by damage to white matter via myelin degeneration with resulting sclerotic plaques and lesions. Upwards of 70% of people with MS show cognitive changes in multiple domains including verbal memory. Advances in disease-modifying therapies have increased the expected lifespan of people with MS, making aging with MS a critical emerging area of study. Memory declines during normal aging, yet the specific impact of MS on verbal memory in aging is inconclusive and understudied. To address this gap in knowledge, we examined whether MS was associated with verbal learning slope, total learning, delayed recall, and recognition performance in older adults. We further explored whether MS disease severity influenced these memory operations.
Participants and Methods:
Participants included two cohorts: older adults with MS recruited from MS centers and patient registries, and healthy controls recruited from the community. A total of 164 adults age 60 and older without dementia were included in the current study, 79 in the MS group (mean age = 65.05 + 4.72; %female = 62) and 85 in the control group (mean age = 69.53 + 6.65; %female = 65.9). All participants were administered a neuropsychological battery including the Hopkins Verbal Learning Test-Revised (HVLT-R). The Patient Determined Disease Steps (PDDS), a patient-rated score of disability severity in MS comprised of eight steps related to walking ability, was used to operationalize MS severity. Using a median split, the PDDS was dichotomized into low (PDDS = 0-2) versus high (PDDS = 3-5) MS severity groups. Linear regression models were run to examine the effect of group (MS vs. control) and disease severity (PDDS) on four operations from the HVLT-R: learning slope, total learning, delayed recall, and recognition. Statistical analyses adjusted for age, years of education, and sex.
Results:
Linear regression models revealed that older adults with MS showed lower total learning compared to healthy controls (β = -.18, p = .03). Learning slope, delayed recall, and recognition did not differ by group (p > .05). Compared to healthy controls, older adults with high MS severity performed worse on total learning (β = -.21; p = .01) and delayed recall (β = -.18; p = .03). Group differences on learning slope and recognition were not significant (p > .05).
Conclusions:
The presence of MS was associated with worse total learning. Moreover, high severity of MS was associated with worse total learning and delayed recall in older adults. These results delineate the influence of MS on specific memory operations and emphasize the potential utility of disease severity on cognitive performance in aging.
Health disparities among African Americans (AAs) in the United States are evident, especially among older adults and people living with HIV (PLWH). These health disparities include worse cognitive functioning among AAs than White counterparts. Though disparities in health literacy among AAs impact health outcomes across clinical populations, less is known on the mechanistic role health literacy may play in explaining racial differences in cognitive functioning among older PLWH. The current study investigated the association between health literacy and global cognitive functioning among middle-aged and older AA and White adults with and without HIV in the Deep South.
Participants and Methods:
Two hundred and seventy-three people (170 PLWH: 146 AA, 24 White; 103 HIV-negative: 67 AA, 36 White) were enrolled in an observational study and completed measures of sociodemographic characteristics, as well as the reading subtest of the Wide Range Achievement Test-3rd Edition to assess verbal IQ. A composite score of socioeconomic status (SES) was created using total years of education and annual household income. Neurocognitive functioning was assessed using a comprehensive cognitive battery (i.e., verbal, attention/working memory, executive function, learning, recall, speed of processing, and motor), from which a sample-based global Z-score composite was created. Health literacy was measured using a sample-based composite Z-score derived from the Rapid Estimate of Adult Literacy in Medicine, Test of Functional Health Literacy in Adults Reading Comprehension, Newest Vital Sign, and Expanded Numeracy Scale. First, multivariable linear regression analyses were performed within both PLWH and HIV-negative samples examining the association between race, SES, verbal IQ, and health literacy with cognitive functioning. These results informed two bootstrap confidence interval mediation analyses to determine whether health literacy mediated the association between race and global cognitive functioning.
Results:
In both PLWH and HIV-negative individuals, linear regressions showed that Whites had better global cognitive functioning, health literacy, and verbal IQ than AAs. Linear regressions showed that health literacy had an independent association with cognitive function when accounting for verbal IQ and SES. Mediations showed that health literacy significantly mediated the association between race and global cognitive functioning in both samples, independent of verbal IQ (PLWH: b = .07, 95% CI [0.0096, 0.2149]; HIV-negative: b = .15, 95% CI [0.0518, 0.2877]), indicating that Whites were expected to obtain higher global cognitive Z-scores than AAs in both PLWH and HIV-negative samples, through the mediating effect of better health literacy.
Conclusions:
Health literacy significantly mediated the association between race and global cognitive functioning among middle-aged and older adults with and without HIV, underscoring the importance of health literacy in explaining racial disparities in cognitive outcomes among AAs in the Deep South. Findings have implications for guiding clinicians and healthcare providers in developing interventions that promote health literacy in these underserved populations, which may have downstream impacts on cognitive functioning. Future work is needed to examine mechanisms whereby health literacy impacts neurocognition among AA PLWH.
Community reintegration and participation have been shown to be significantly correlated to improved Quality of Life (QoL) following moderate to severe traumatic brain injury (msTBI), yet these models often come with significant levels of unaccounted variability (Pierce and Hanks, 2006). Measures for community participation frequently employ objective measures of participation, such as number of outings in a week or current employment status (Migliorini et al., 2016), which may not adequately account for lifestyle differences, especially in aging populations. Less often integrated are subjective measures of an individual’s own belongingness and autonomy within the community (Heineman et al., 2011), also referred to as their participation enfranchisement (PE). The present study examines three questions pertinent to the potential clinical value of PE. First, do measures of objective participation significantly predict an individual’s PE ratings? Second, are both types of measures equally successful predictors of QoL for aging individuals with chronic-stage msTBI. Finally, would controlling for either objective or subjective integration ratings enable neurocognitive assessments to better predict QoL post injury?
Participants and Methods:
41 older-adults (M= 65.32; SD= 7.51) with a history of msTBI were included (M= 12.59 years post-injury;SD= 8.29) for analysis. Subjective community integration was measured through the Participation Enfranchisement Survey. The Participation Assessment with Recombined Tools-Objective (PART-O) provided the objective measurement of participation. Quality of life was assessed through the Quality of Life after Brain Injury (QOLIBRI). An estimate of neurocognitive performance was created through the Brief Test of Adult Cognition by Telephone (BTACT), which includes six domains including: verbal-learning and memory (immediate and delayed recall), working memory (digit-span backwards), reasoning (number sequencing), semantic fluency (category fluency), and processing speed (backwards counting). Performance on the BTACT, PE ratings, and PART-O scores were included as the dependent variables in stepwise, linear regression models predicting QoL ratings to assess the differential contribution of the dependent variables and potential interaction effects.
Results:
While both the PART-O (f(1,39)=5.52;p=.024,n2=.124) and the PE survey (f(1,39)=14.31 ;p<.001,n2=.268) significantly predicted QoL, the addition of PE in the PART-O model resulted in significant (20.9%) reduction in unaccounted variance. Further in the model controlling for PE, PART-O no longer provides a significant (p=.15) contribution to the model estimating QoL (f(2,38)=8.41; p=.001). Performance on the BTACT correlated with PART-O (p<.0001), but not PE (p=.13) ratings. Finally, across two models controlling for BTACT performance, PE (p=.002,partial n2=.23), but not PART-O (p=.28,partial n2=.031) contributed significantly to QoL predictions. No significant interactions between PART-O, PE, and/or BTACT were observed when added to any model.
Conclusions:
MsTBI impacts nearly every facet of an individual’s life, and as such, improving QoL post-injury requires a broad, yet well-considered approach. The objective ratings of participation, subjective PE, BTACT performance, all independently predicted quality of life in this sample. However, after controlling for neurocognitive assessment performance, PE was shown to independently contribute to quality of life, while the PART-O ratings no longer provided significant contribution. While community integration is a vital factor to consider for long-term rehabilitation, tailoring what “integration” means to the patient may hold significant potential to improve long-term quality of life.
To examine the relationships between baseline gray matter volumes, diagnostic status, and executive function performance at 24-month follow-up, and the relative importance of predictors of executive function in a cohort of non-demented older adults.
Participants and Methods:
The study sample included 147 participants from the Alzheimer’s Disease Neuroimaging Initiative (mean age = 70.6, SD = 6.4; mean education = 17 years, SD = 2.4). At baseline, 49 participants were diagnosed as cognitively normal (CN), 60 as early mild cognitive impairment (EMCI), and 38 as late mild cognitive impairment (LMCI). Magnetic resonance imaging (MRI) data were collected at baseline. A composite score of executive function and FreeSurfer-derived gray matter regions-of-interest (ROI; whole brain, superior frontal gyrus, middle frontal gyrus, inferior frontal gyrus, orbitofrontal cortex, anterior cingulate cortex, superior parietal lobule, inferior parietal lobule, hippocampus) were examined. Hierarchical linear regression models were employed to assess whether brain volume predicted executive function at 24-month follow-up and interaction effects between baseline ROI volume and diagnostic status. Age, gender, education, Mini-Mental State Examination scores, and APOE-e4 allele status were included as control variables in each model. Relative importance metrics, which quantifies an individual regressor’s contribution to a multiple regression model, were computed using the Lindemen, Merenda, and Gold (lmg) method to assess the relative contribution of each variable in predicting executive function performance.
Results:
Across all participants, baseline gray matter ROI volume accounted for a significant amount of variance in executive function at 24-months after accounting for control variables. Specifically, anterior cingulate cortex and superior parietal lobule accounted for an additional 7% and 6% of variance in executive function at 24-months. Significant brain region X diagnostic status interaction effects were observed in executive function performance at 24-months. Relative importance metrics within each group indicated that age is the most important predictor of executive function at 24-months for CN, anterior cingulate cortex is most important for EMCI, and Mini-Mental Examination score is most important for LMCI.
Conclusions:
Our findings implicate frontoparietal gray matter regions as significant predictors of executive function performance at 24-months, and that this relationship is moderated by diagnostic status. Our results indicate that the value of specific variables to predict executive function performance varies based on diagnostic status. Specifically, anterior cingulate cortex was a significant predictor of executive function performance across all participants and was the most important variable in predicting performance in the earliest stage of mild cognitive impairment. These results support previous studies examining gray matter correlates of executive function and extend the literature by exploring predictors of executive function in early and late stages of mild cognitive impairment.
Attention of the research community on childhood cancer has grown exponentially over the last 5 decades (Robinson & Hudson, 2014). With research attention growing rapidly, cure rates have increased just as dramatically, with survivorship well over 80% (Ward, et al., 2014). With survivorship on the rise, research has turned to the examination of late effects in survivors of childhood cancer, especially neuropsychological late effects (Krull, et al., 2018). Late effects, functional impairment, and the awareness of one’s own impairment can create several lasting issues in a survivor’s life (Oeffinger, et al., 2010). The objective of this study is to explore the feasibility and functionality of a group intervention for this population.
Participants and Methods:
Participants were recruited from a pediatric cancer institute in southern California. To be considered for inclusion, participants must have completed curative treatment for childhood cancer, not be currently undergoing treatment for childhood cancer, be free of any severe and persistent mental illnesses, and have access to a stable internet connection (for Zoom sessions). This study examined the impact of an Acceptance and Commitment Therapy (ACT)-based group intervention protocol on survivors of childhood cancer. Specifically, this study explored a strategy to identify early neuropsychological late effects and a strategy to improve these impacts. The group intervention was conducted via Zoom (www.zoom.us) which provided an opportunity to continue to provide this service in the wake of COVID-19. Data was collected at baseline and at the completion of the group intervention. This data focused on the functional and perceived impacts of neuropsychological sequelae in these participants, as well as the changes as related to the group intervention.
Results:
Data did not show any significant changes from baseline to follow-up in this population. The lack of significance was likely due to a severely truncated sample size. Despite the lack of significant findings, data appears to trend negatively. Although these findings do not provide conclusive evidence for this ACT-based group as an intervention for neuropsychological late effects in survivors of childhood cancer, the data suggested some interesting trends which will be explored further in this presentation.
Conclusions:
The results of this study help to further explore the importance of attention to neuropsychological symptoms and issues in survivors of childhood cancer, especially within the first few years following the completion of treatment. As survivorship continues to increase, it will be of utmost importance to continue to examine the impact of neuropsychological late effects and how the field of neuropsychology can best serve this population. This study was severely limited by a small sample size, a single clinician providing the protocol, and a truncated timeline. Further research will examine the impact of this study protocol in a larger sample size, which will likely increase the ability to reject the null hypothesis. In addition, future research must also be conducted to better explore strategies of early and consistent neuropsychological intervention in this population.
Survivors of childhood ALL treated with CNS-directed chemotherapy are at risk for neurocognitive deficits that emerge during treatment and impact functional and quality of life outcomes throughout survivorship. Neurocognitive monitoring is the recommended standard of care for this population; however, information on assessment timing and recommendations for assessment measures are limited. We examined the role of serial neurocognitive monitoring completed during protocol-directed therapy in predicting parent-reported neurocognitive late effects during survivorship.
Participants and Methods:
Parents of 61 survivors of childhood ALL completed a semi-structured survey focused on parent perspective of neurocognitive late effects as part of a quality improvement project. Survivors completed protocol-directed treatment for newly diagnosed ALL on two consecutive clinical trials (St. Jude Total Therapy Study 15, 47.5%; Total Therapy 16, 52.5%). The majority of survivors were White (86.9%), 52.5% were male, and 49% were treated for low risk disease. Mean age at diagnosis was 7.77 years (standard deviation [SD] = 5.31). Mean age at survey completion was 15.25 years (SD = 6.29). Survivors completed neurocognitive monitoring at two prospectively determined time points during and at the end of protocol-directed therapy for childhood ALL.
Results:
During survivorship, parents reported that 73.8% of survivors experienced neurocognitive late effects, with no difference in frequency of endorsement by protocol (p = .349), age at diagnosis (p = .939), patient sex (p = .417), or treatment risk arm (p = .095). In survivors with late effects, 44.3% sought intervention in the form of educational programming (i.e., 504 or Individualized Education Program). Among the group with late effects, compared to those without educational programming, those with educational programming had worse verbal learning (CVLT Trials 1-5 Total, Mean[SD]; T = 56.36 [11.19], 47.00 [10.12], p = .047) and verbal memory (CVLT Short Delay Free Recall, Z = 0.86 [0.67], -0.21 [1.01], p = .007); Long Delay Free Recall, Z = 0.91 [0.92], -0.25 [1.25], p = .020) during therapy. Compared to those without educational programming, survivors with educational programming had lower estimated IQ (SS = 109.25 [13.48], 98.07 [15.74], p = .045) and greater inattention [CPT Beta T = 56.80 [13.95], 75.70 [22.93], p = .017) at the end of therapy.
Conclusions:
Parents report that nearly three quarters of children treated for ALL with chemotherapy only experience neurocognitive late effects during early survivorship, with no difference in frequency by established risk factors. Of those with late effects, nearly half required educational programming implemented after diagnosis, suggesting a significant impact on school performance. Results from neurocognitive monitoring beginning during therapy has utility for predicting educational need in survivors experiencing late effects. Our findings provide direction on the timing and content of neurocognitive monitoring, which is the recommended standard of care for childhood cancer patients treated with CNS-directed therapy.
The global prevalence of persons living with dementia will soon exceed 50 million. Most of these individuals reside in low- and middle-income countries (LMICs). In South Africa, one such LMIC, the physician-to-patient ratio of 9:10 000 severely limits the capacity of clinicians to screen, assess, diagnose, and treat dementias. One way to address this limitation is by using mobile health (mHealth) platforms to scale-up neurocognitive testing. In this paper, we describe one such platform, a brief tablet-based cognitive assessment tool (NeuroScreen) that can be administered by lay health-providers. It may help identify patients with cognitive impairment (related, for instance, to dementia) and thereby improve clinical care and outcomes. However, there is a lack of data regarding (a) the acceptability of this novel technology for delivery of neurocognitive assessments in LMIC-resident older adults, and (b) the influence of technology-use experience on NeuroScreen performance of LMIC-resident older adults. This study aimed to fill that knowledge gap, using a sample of cognitively impaired South African older adults.
Participants and Methods:
Participants were 60 older adults (63.33% female; 91.67% right-handed; age M = 68.90 years, SD = 9.42, range = 50-83), all recruited from geriatric and memory clinics in Cape Town, South Africa. In a single 1-hour session, they completed the entire NeuroScreen battery (Trail Making, Number Speed, Finger Tapping, Visual Discrimination, Number Span Forward, Number Span Backward, List Learning, List Recall) as well as a study-specific questionnaire assessing acceptability of NeuroScreen use and overall experience and comfort with computer-based technology. We summed across 11 questionnaire items to derive a single variable capturing technology-use experience, with higher scores indicating more experience.
Results:
Almost all participants (93.33%) indicated that NeuroScreen was easy to use. A similar number (90.00%) indicated they would be comfortable completing NeuroScreen at routine doctor's visits. Only 6.67% reported feeling uncomfortable using a tablet, despite about three-quarters (76.67%) reporting never having used a tablet with a touchscreen before. Almost one in five participants (18.33%) reported owning a computer, 10.00% a tablet, and 70.00% a smartphone. Correlations between test performance and technology-use experience were statistically significant (or strongly tended toward significance) for most NeuroScreen subtests that assessed higherorder cognitive functioning and that required the participant to manipulate the tablet themselves: Trail Making 2 (a measure of cognitive switching ability), r = .24, p = .05; Visual Discrimination A (complex processing speed [number-symbol matching]), r = .38, p = .002; Visual Discrimination B (pattern recognition), r = .37, p = .004; Number Speed (simple information processing speed), r = .36, p = .004. For the most part, there were no such significant associations when the NeuroScreen subtest required only verbal input from the participant (i.e., on the list learning and number span tasks).
Conclusions:
NeuroScreen, a tablet-based neurocognitive screening tool, appears feasible for use among older South Africans, even if they are cognitively impaired and have limited technological familiarity. However, test performance might be influenced by amount of technology-use experience; clinicians using the battery must consider this in their interpretations.
To present the Mobile Toolbox (MTB), comprised of an expandable library of cognitive and other tests, including adapted versions of NIH Toolbox® measures. The MTB provides a complete research platform for app creation, study management, data collection, and data management. We will describe the MTB project and MTB research platform and demonstrate examples of assessments.
Participants and Methods:
MTB is the product of an NIH-funded, multi-institutional effort involving Northwestern University, Sage Bionetworks, Penn State, University of California San Francisco, University of California San Diego, Emory University, and Washington University. The MTB assessment library is a dynamic repository built upon Sage Bionetworks mobile health platform. All MTB measures are created or adapted for a mobile interface using iOS and Android smartphones. Guided by the principles of open science, many components are open source to allow researchers and developers to integrate externally developed tests, including supplemental scales (e.g., passively collected contextual factors) assessing variables such as mood and fatigue that might influence cognitive test performance.
Results:
The current MTB library includes eight core cognitive tests based on well-established neuropsychological measures: two language tasks (Spelling and Word Meaning), two executive functioning tasks (Arrow Matching and Shape-Color Sorting), an associative memory task (Faces and Names), an episodic memory task (Arranging Pictures), a working memory task (Sequences) and a processing speed task (Numbers and Symbols). Additional cognitive assessments from other popular test libraries including the International Cognitive Ability Resource (ICAR), Cognitive Neuroscience Test Reliability and Clinical Applications for Schizophrenia (CNTRACS) and Test My Brain are currently being implemented, as are non-cognitive measures from the NIH Toolbox Emotion Battery and the Patient-Reported Outcomes Measurement Information System (PROMIS). The MTB library includes measures suitable for use in research studies incorporating point-in-time and burst designs as well as ecological momentary assessment (EMA).
Conclusions:
The MTB was created to address many of the scientific, practical, and technical challenges to cognitive assessment by capitalizing on advances in technology measurement and cognitive research. Initial psychometric evaluation of measures has been performed, and additional clinical validation is underway in studies with persons at risk for cognitive impairment or Alzheimer’s disease (AD), diagnosed with mild cognitive impairment (MCI) or AD, Parkinson’s disease, and HIV-associated Neurocognitive Disorders. Calculation of norms and reliable change indicators is in progress. The MTB is currently available to beta testers with public release planned for Summer, 2023. Clinical researchers will be able to use the MTB system to design smartphone-based test batteries, deploy and manage mobile data collection in their research studies, and aggregate and analyze results in the context of large-scale norming data.
Although the cognitive profiles of people experiencing homelessness have been described in the literature, the neuropsychological profile of people experiencing complex homelessness has not been delineated. Complex homelessness is homelessness that continues despite the provision of bricks and mortar solutions. People experiencing complex homelessness often have an array of physical health, mental health, substance use, neurodevelopmental and neurocognitive disorders. The present study aimed to delineate the neuropsychological profile of people experiencing complex homelessness and explore the utility of neuropsychological assessment in supporting this population.
Participants and Methods:
19 people experiencing complex homelessness in Sydney, Australia, were consecutively referred by specialist homelessness services for neuropsychological assessment. They underwent comprehensive assessment of intelligence, memory and executive functioning and completed questionnaires to screen for the presence of ADHD, PTSD, depression, anxiety and stress. A range of performance validity measures were included. Referrers were asked to complete questionnaires on history of childhood trauma, psychological functioning, drug and alcohol use, functional cognitive abilities, homelessness factors, personality, risk of cognitive impairment and adaptive functioning and to note existing or suspected mental health, neurodevelopmental and neurocognitive disorders. Referrers also completed a post-assessment pathways questionnaires to identify whether the neuropsychological assessment facilitated referral pathways (e.g., for government housing or financial assistance). Clinicians completed a post-assessment diagnosis survey, which was compared to the pre-assessment known or suspected diagnoses. Finally, referrers were asked to complete a satisfaction questionnaire regarding the neuropsychological assessment.
Results:
Mean (SD) WAIS-IV indexes were VCI = 81.1 (14.5), PRI = 86.1 (10.9), WMI = 80.5 (13.0), PSI = 81.6 (10.2). Mean WMS-IV Flexible (LMVR) indexes were AMI = 68.3 (19.6), VMI = 77.1 (19.3), IMI = 72.7 (17.2), and DMI = 70.5 (17.6). The majority of participants showed unusual differences between WAIS-IV and TOPF-predicted WAIS-IV scores and between WAIS-IV General Ability and WMS-IV Flexible (LMVR) scores. Demographically corrected scores on tests of executive functioning were mostly one or more standard deviations below the mean. The majority of participants screened positive on screening measures of executive dysfunction, PTSD and ADHD and had elevated self-reported psychological distress scores. At least one new diagnosis was made for nine (47%) participants, established diagnoses were confirmed for two (11%) participants, diagnoses were supported for 15 (79%) participants, tentative diagnoses were made for 16 (84%) participants, and five (26%) participants had at least one diagnosis disconfirmed/unsupported. Referrers indicated that the majority of post-assessment pathways were more accessible following the neuropsychological assessment and that they were very satisfied with the neuropsychological assessments overall.
Conclusions:
This is one of the first studies to delineate the neuropsychological profile of people experiencing complex homelessness using robust psychometric approaches, including performance validity tests. This population experiences a high burden of cognitive impairment and associated substance use, neurodevelopmental and mental health comorbidities. Neuropsychological assessment makes referral pathways more accessible and is valued by referrers of people experiencing complex homelessness.
There is increasing recognition of cognitive and pathological heterogeneity in early-stage Alzheimer’s disease and other dementias. Data-driven approaches have demonstrated cognitive heterogeneity in those with mild cognitive impairment (MCI), but few studies have examined this heterogeneity and its association with progression to MCI/dementia in cognitively unimpaired (CU) older adults. We identified cluster-derived subgroups of CU participants based on comprehensive neuropsychological data and compared baseline characteristics and rates of progression to MCI/dementia or a Dementia Rating Scale (DRS) of <129 across subgroups.
Participants and Methods:
A hierarchical cluster analysis was conducted using 11 baseline neuropsychological test scores from 365 CU participants in the UCSD Shiley-Marcos Alzheimer’s Disease Research Center (age M=71.93 years, SD=7.51; 55.9% women; 15.6% Hispanic/Latino/a/x/e). A discriminate function analysis was then conducted to test whether the individual neuropsychological scores predicted cluster-group membership. Cox regressions examined the risk of progression to consensus diagnosis of MCI or dementia, or to DRS score <129, by cluster group.
Results:
Cluster analysis identified 5 groups: All-Average (n=139), Low-Visuospatial (n=46), Low-Executive (n=51), Low-Memory/Language (n=83), and Low-All Domains (n=46). The discriminant function analysis using the neuropsychological measures to predict group membership into these 5 clusters correctly classified 85.2% of the participants. Subgroups had unique demographic and clinical characteristics. Relative to the All-Average group, the Low-Visuospatial (hazard ratio [HR] 2.39, 95% CI [1.03, 5.56], p=.044), Low-Memory/Language (HR 4.37, 95% CI [2.24, 8.51], p<.001), and Low-All Domains (HR 7.21, 95% CI [3.59, 14.48], p<.001) groups had greater risk of progression to MCI/dementia. The Low-Executive group was also twice as likely to progress to MCI/dementia compared to the AllAverage group, but did not statistically differ (HR 2.03, 95% CI [0.88,4.70], p=.096). A similar pattern of results was found for progression to DRS score <129, with the Low-Executive (HR 2.82, 95% CI [1.26, 6.29], p=.012), Low-Memory/Language (HR 3.70, 95% CI [1.80, 7.56], p<.001) and Low-All Domains (HR 5.79, 95% CI [2.74, 12.27], p<.001) groups at greater risk of progression to a DRS score <129 than the All-Average group. The Low-Visuospatial group was also twice as likely to progress to DRS <129 compared to the All-Average group, but did not statistically differ (HR 2.02, 95% CI [0.80, 5.06], p=.135).
Conclusions:
Our results add to a growing literature documenting heterogeneity in the earliest cognitive and pathological presentations associated with Alzheimer’s disease and related disorders. Participants with subtle memory/language, executive, and visuospatial weaknesses all declined at faster rates than the All-Average group, suggesting that there are multiple pathways and/or unique subtle cognitive decline profiles that ultimately lead to a diagnosis of MCI/dementia. These results have important implications for early identification of individuals at risk for MCI/dementia. Given that the same classification approach may not be optimal for everyone, determining profiles of subtle cognitive difficulties in CU individuals and implementing neuropsychological test batteries that assess multiple cognitive domains may be a key step towards an individualized approach to early detection and fewer missed opportunities for early intervention.
History of traumatic brain injury (TBI) is associated with increased risk of dementia, but few studies have evaluated whether TBI history alters the course of neurocognitive decline, and existing literature on this topic is limited to short follow-up and smaller samples. The primary aim of this study was to evaluate whether a history of TBI (TBI+) influences neurocognitive decline later-in-life among older adults with or without cognitive impairment [i.e., normally aging, Mild Cognitive Impairment (MCI), or dementia].
Participants and Methods:
Participants included individuals from the National Alzheimer’s Coordinating Center (NACC) who were at least 50 years old and with 3 to 6 visits (M number of visits = 4.43). Participants with any self-reported history of TBI (n = 1,467) were matched 1:1 to individuals with no reported history of TBI (TBI-) from a sample of approximately 45,000 participants using case-control matching based on age (+/- 2 years), sex, education, race, ethnicity, cognitive diagnosis [cognitively normal (CN), MCI, or all-cause dementia], etiology of cognitive impairment, functional decline (Clinical Dementia Rating Scale, CDR), number of Apolipoprotein E4 (APOE ε4) alleles, and number of annual visits (3 to 6). Mixed linear models were used to assess longitudinal neuropsychological test composites (using NACC normative data) of executive functioning/attention/speed (EFAS), language, and memory in TBI+ and TBI- participants. Interactions between TBI and demographics, APOE ε4 status, and cognitive diagnosis were also examined.
Results:
Following matching procedures, TBI+ (n=1467) and TBI- (n=1467) groups were nearly identical in age (TBI+ M = 71.59, SD = 8.49; TBI- M = 71.63, SD = 8.44), education (TBI+ M = 16.12, SD = 2.59; TBI- M = 16.10, SD = 2.52), sex (both 55% male), race (both 90% White), ethnicity (both 98% non-Hispanic), APOE ε4 alleles (both 0 = 62%, 1 = 33%, 2 = 5%), baseline cognitive diagnoses (both CN = 60%, MCI = 18%, dementia = 12%), and global CDR (TBI+ M = 0.30, SD = 0.38, TBI- M = 0.30, SD = 0.38). At baseline, groups had similar Z-scores of in EFAS (TBI+ Mefas = -0.02, SD = 1.21; TBI- Mefas = -0.04, SD = 1.27), language (TBI+ MLanguage = -0.48, SD = 0.98; TBI- MLanguage = -0.55, SD = 1.05), and memory (TBI+ MMemory = -0.45, SD = 1.28; TBI- MMemory = -0.45, SD =1.28). The course of change in neuropsychological functioning worsened longitudinally, but did not differ between TBI groups (p’s > .110). There were no significant interactions between TBI history and age, sex, education, race/ethnicity, number of APOE ε4 status, or cognitive diagnosis (all p’s > .027).
Conclusions:
In this matched case-control design, our findings suggest that a history of TBI, regardless of demographic factors, APOE ε4 status, and cognitive diagnosis, does not significantly alter the course of neurocognitive functioning later-in-life in older adults with and without cognitive impairment. Future clinicopathological longitudinal studies with well characterized TBI histories and the associated clinical course are needed to help clarify the mechanism by which TBI may increase dementia risk for some individuals, without affecting course of decline.
Sexual dimorphism in human brain structure and behavior is influenced by exposure to sex hormones during critical developmental periods. In children, cancer and cancer treatments may alter hormone activity and brain development, impacting neurocognitive functions.
Participants and Methods:
Five-year survivors of childhood cancer (N=15,560) diagnosed at <21 years from 1970 to 1999, and 3,206 siblings from the Childhood Cancer Survivor Study completed the Neurocognitive Questionnaire (NCQ), a measure of self-reported task efficiency (TE), emotion regulation (ER), Organization, and working memory (WM). We compared rates of cognitive impairment (i.e., NCQ scores >90th percentile) in survivors and same-sex siblings, and sex differences in risk factors for cognitive impairment (i.e., treatment exposures, chronic health conditions (CHCs), cancer diagnosis, age at diagnosis) using modified Poisson regressions.
Results:
Survivors were more likely to report cognitive impairment than same-sex siblings (Males: TE OR=2.3, p<.001; ER OR=1.7, p=.008; Organization OR=1.5, p=.04; WM OR=2.3, p<.001. Females: TE OR=2.6, p<.001; ER OR=1.9, p<.001; Organization OR=1.5, p=.02; WM OR=2.6, p<.001). Within survivors, females were more likely than males to report impairment in TE (OR=1.2, p=.001), ER (OR=1.5, p<.001), and WM (OR=1.2, p<.001). There were no sex differences in symptom severity in siblings (all ps>.05). Risk factors for cognitive impairment in survivors included cranial radiation dose (TE <20Gy OR=1.5, p=.008, ≥20Gy OR=2.5, p<.001; ER OR=1.5, p<.001; Organization <20 Gy OR=1.4, p<.001; < WM 20 Gy OR=1.8, p<.001, ≥20Gy OR=2.7, p<.001), presence of moderate to severe CHCs (TE 1 CHC OR=1.9, p<.001, >1 CHC OR=3.6, p<.001; ER 1 CHC OR=1.7, p<.001, >1 CHC OR=2.2, p<.001; Organization 1 CHC OR=1.5, p=.001, >1 CHC OR=2.5, p<.001; WM 1 CHC OR=1.8, p<.001, >1 CHC OR=4.1, p<.001). There were sex differences in cognitive impairment risk factors in survivors. In females, cranial radiation dose (<20 Gy TE OR=1.6, p=.02; ≥20Gy TE OR=1.4, p=.01), leukemia diagnosis (TE OR=1.4, p=.02), or diagnosis age between 3-5 years (WM OR=1.4, p=.02) conferred higher risk for cognitive impairment compared to males with the same history. Females diagnosed with Hodgkin’s lymphoma (Organization OR=0.61, p=.05) or non-Hodgkin’s lymphoma (Organization OR=0.55, p=.03) were at lower risk for cognitive impairment compared to males.
Conclusions:
We found sex-specific differences in rates of, and risk factors for, neurocognitive impairment, suggesting a sex vulnerability. Future studies examining interactions between sex hormones and treatment exposures during brain development will enable tailoring treatments follow-up interventions to ensure that quality of life is maximized.
Blood-based biomarkers represent a scalable and accessible approach for the detection and monitoring of Alzheimer’s disease (AD). Plasma phosphorylated tau (p-tau) and neurofilament light (NfL) are validated biomarkers for the detection of tau and neurodegenerative brain changes in AD, respectively. There is now emphasis to expand beyond these markers to detect and provide insight into the pathophysiological processes of AD. To this end, a reactive astrocytic marker, namely plasma glial fibrillary acidic protein (GFAP), has been of interest. Yet, little is known about the relationship between plasma GFAP and AD. Here, we examined the association between plasma GFAP, diagnostic status, and neuropsychological test performance. Diagnostic accuracy of plasma GFAP was compared with plasma measures of p-tau181 and NfL.
Participants and Methods:
This sample included 567 participants from the Boston University (BU) Alzheimer’s Disease Research Center (ADRC) Longitudinal Clinical Core Registry, including individuals with normal cognition (n=234), mild cognitive impairment (MCI) (n=180), and AD dementia (n=153). The sample included all participants who had a blood draw. Participants completed a comprehensive neuropsychological battery (sample sizes across tests varied due to missingness). Diagnoses were adjudicated during multidisciplinary diagnostic consensus conferences. Plasma samples were analyzed using the Simoa platform. Binary logistic regression analyses tested the association between GFAP levels and diagnostic status (i.e., cognitively impaired due to AD versus unimpaired), controlling for age, sex, race, education, and APOE e4 status. Area under the curve (AUC) statistics from receiver operating characteristics (ROC) using predicted probabilities from binary logistic regression examined the ability of plasma GFAP to discriminate diagnostic groups compared with plasma p-tau181 and NfL. Linear regression models tested the association between plasma GFAP and neuropsychological test performance, accounting for the above covariates.
Results:
The mean (SD) age of the sample was 74.34 (7.54), 319 (56.3%) were female, 75 (13.2%) were Black, and 223 (39.3%) were APOE e4 carriers. Higher GFAP concentrations were associated with increased odds for having cognitive impairment (GFAP z-score transformed: OR=2.233, 95% CI [1.609, 3.099], p<0.001; non-z-transformed: OR=1.004, 95% CI [1.002, 1.006], p<0.001). ROC analyses, comprising of GFAP and the above covariates, showed plasma GFAP discriminated the cognitively impaired from unimpaired (AUC=0.75) and was similar, but slightly superior, to plasma p-tau181 (AUC=0.74) and plasma NfL (AUC=0.74). A joint panel of the plasma markers had greatest discrimination accuracy (AUC=0.76). Linear regression analyses showed that higher GFAP levels were associated with worse performance on neuropsychological tests assessing global cognition, attention, executive functioning, episodic memory, and language abilities (ps<0.001) as well as higher CDR Sum of Boxes (p<0.001).
Conclusions:
Higher plasma GFAP levels differentiated participants with cognitive impairment from those with normal cognition and were associated with worse performance on all neuropsychological tests assessed. GFAP had similar accuracy in detecting those with cognitive impairment compared with p-tau181 and NfL, however, a panel of all three biomarkers was optimal. These results support the utility of plasma GFAP in AD detection and suggest the pathological processes it represents might play an integral role in the pathogenesis of AD.
Religion's neural underpinnings have long been a topic of speculation and debate, but an emerging neuroscience of religion is beginning to clarify which regions of the brain integrate moral, ritual, and supernatural religious beliefs with functionally adaptive responses. In my presentation, I will review evidence indicating that religious cognition involves a complex interplay among the brain regions underpinning cognitive control, social reasoning, social motivations, emotion, reinforcement, and ideological beliefs. I will then conclude my presentation by summarizing current and future research efforts and why searching for God in the brain is critical to our understanding of human behavior.
Upon conclusion of this course, learners will be able to:
1. Summarize the methods used to study the neural basis of religious belief.
An acquired brain injury (ABI) is a neurological pathology that generates a physical injury in the brain. These include cerebrovascular accidents (CVA) and traumatic brain injuries (TBI). Brain injuries can cause cognitive, emotional, and social problems, which have the potential to severely alter a person’s independence and quality of life. Loneliness, thesubjective experience of social isolation, has been shown to be the best predictor of mental health problems and poorquality of life in patients with ABI. This study aimed to explore the relationship between cognitive, emotional, and social determinants and loneliness in Puerto Ricans with ABI in the chronic phase.
Participants and Methods:
Cross-sectional, exploratory, and correlational methods were implemented. Assessments included the Frontal Systems Behavioral Scale - Spanish version (FrSBe-SP), Perth Emotional Reactivity Scale -Spanish version (PERS), Anticipated Stigma and Concealment (ASC), and the University of California Los Angeles - Loneliness Scale (UCLA-LS).
Results:
A total of seventeen participated (n=17). Twenty-nine percent of participants were female. Forty-seven percent had history of previous CVA and fifty-two percent had history of TBI. Correlational analyses suggest a positive and significant relationship between executive dysfunction (FrSBe-SP) and feelings of loneliness (UCLA-LS) (p=.601), as well as a positive and significant relationship between neuroticism-negative emotional reactivity (PERS) and feelings of loneliness (UCLA-LS) (p=.736). Correlational analysis suggests there is no significant relationship between anticipated stigma (ASC) and feelings of loneliness (UCLA-LS) (p=.282).
Conclusions:
Our findings suggest that there is a significant relationship between cognitive determinants (executive functions) and emotional determinants (neuroticism) with feelings of loneliness in people with a history of ABI. These results support the connection between executive dysfunction, the tendency to experience negative emotions, and the subjective experience of loneliness, consistent with previous studies. However, our study did not find any significant relationship between interactional determinants, such as stigma and concealment, and loneliness. Understanding the role of cognition, emotions, and social variables in reported feelings of loneliness is important for clinical neuropsychological assessment and rehabilitation interventions.
Executive function (EF) is a self-regulatory construct well-established as a predictor of long-term academic achievement and socioemotional functioning in children (Best et al., 2009; Diamond, 2013; Zelazo & Carlson, 2020). Traumatic brain injury (TBI) in childhood frequently results in EF deficits (Beauchamp & Anderson, 2013; Levin & Hanten, 2005). In comparison to adults (Okonkwo et al., 2013), there is an absence of viable blood biomarkers for pediatric TBI to assist in diagnosis and prognosis. Osteopontin (OPN), an inflammatory cytokine, has recently been identified as a putative pediatric TBI blood biomarker (Gao et al., 2020). However, more work is needed to establish OPN’s utility in predicting functional outcomes. Thus, the present study aimed to test relations between OPN measured during the first 72 hours of hospitalization and EF 6-12 months post injury among a sample of pediatric TBI patients.
Participants and Methods:
Sample consisted of 38 children (age at injury = 4.60-16.67 years, M age = 10.61 years, 65.8% male, lowest Glasgow Coma Scale [GCS] score = 3-15, M gcs= 9.97) with TBI whose parents completed the Behavior Rating Inventory of Executive Function, Second Edition (BRIEF-2; Gioia et al., 2015) 6-12 months post injury. Plasma OPN was measured at hospital admission, 24 hours after admission, 48 hours after admission, and 72 hours after admission. 7-scores for each BRIEF-2 clinical scale (Inhibit, Self-Monitor, Shift, Emotional Control, Initiate, Working Memory, Plan/Organize, Task-Monitor, Organization of Materials) and composite index (Behavior Regulation Index, Emotion Regulation Index, Cognitive Regulation Index, Global Executive Composite) were used in analyses.
Results:
Correlation analyses revealed large positive associations (rs = .50-.73, ps = <.001.039) between 48-hour OPN and all BRIEF-2 scales/indices except Initiate. OPN at 24 hours positively correlated with Task-Monitor (r = .40, p = .037). Bivariate logistic regression analyses testing whether OPN predicted at least mildly elevated BRIEF-2 t-scores (>60) did not yield significant associations. Additional supplementary analyses testing whether alternative injury markers - glial fibrillary acidic protein (GFAP), ubiquitin C-terminal Hydrolase-L1 (UCH-L1), S100 calcium binding protein B (S100B) - measured at all time points as well as lowest GCS score correlated with EF revealed the following: admission S100B positively correlated with Inhibit (r = .34, p = .045), 48-hour UCH-L1 negatively correlated with Initiate (r = -.49, p = .041) and Cognitive Regulation Index (r = -.48, p = .044), and 72-hour UCH-L1 negatively correlated with Initiate (r = -.47, p = .048).
Conclusions:
Findings showed higher OPN at 48 hours post admission was broadly related to worse parent-reported EF 6-12 months later, with 24-hour OPN also showing limited associations. Higher levels of alternative injury markers likewise showed limited associations with EF outcomes. Null logistic regression findings may be due to few participants having elevated BRIEF-2 scores. Disrupted EF development may be more noticeable after longer time periods as children age and self-regulatory demands increase. Overall, OPN was found to more consistently predict EF outcomes than GCS score and other injury markers. This could be because OPN is a marker of inflammation, which may be particularly predictive of TBI cognitive outcomes.