Abstract
Background:
Sickle cell disease (SCD) is a genetic disorder that causes physical and cognitive impairment due to hemolysis, painful vaso-occlusion episodes, joint avascular necrosis, and strokes. As individuals with SCD age and develop conditions impacting their physical and cognitive function, their ability to multitask successfully and safely may decline. Cognitive-motor dual-task interference occurs when there is deterioration in one or both tasks while dual-tasking relative to single-tasking. Dual-task assessment (DTA) is a valuable measure of physical and cognitive function; however, there is limited data on DTA in adults with SCD.
Research Question:
Is DTA a feasible and safe method of measuring physical and cognitive function in adults with SCD? What patterns of cognitive-motor interference occur in adults with SCD?
Methods:
We enrolled 40 adults with SCD (mean age 44 years, range 20–71) in a single-center prospective cohort study. We used usual gait speed as the measure of motor performance and verbal fluency (F, A, and S) as the measure of cognitive performance. We measured feasibility as the proportion of consented participants able to complete the DTA. We calculated the relative dual-task effect (DTE %) for each task and identified patterns of dual-task interference.
Results:
Most consented participants completed the DTA (91%, 40/44) and there were no adverse events. There were 3 main dual-task interference patterns for the first trial using letter ‘A’: Motor Interference (53%, n=21), Mutual Interference (23%, n=9), and Cognitive-Priority Tradeoff (15%, n=6). For the second trial using letter ‘S’, there were two main dual-task interference patterns: Cognitive-Priority Tradeoff (53%, n=21) and Motor Interference (25%, n=10).
Statement of Significance:
DTA was feasible and safe in adults with SCD. We identified specific patterns of cognitive-motor interference. This study supports further evaluation of DTA as a potentially useful tool to measure physical and cognitive function in ambulatory adults with SCD.
Keywords: Cognitive motor interference, Dual-task, gait speed, sickle cell disease, sickle cell anemia, functional assessment, geriatrics
INTRODUCTION
Sickle cell disease (SCD) is an inherited disorder characterized by sickling and polymerization of deoxygenated hemoglobin (HbS), which leads to vaso-occlusive episodes[1]. Individuals with SCD experience frequent and severe pain, avascular necrosis (AVN) of the joints, strokes, retinopathy, and cardiopulmonary disease[2]. These complications contribute to functional impairment and disability and have resulted in a shorter life expectancy compared to the general population[3]. However, over the last 50 years the median survival for people with SCD has increased to 50–60 years[4, 5]. As the population of older adults with SCD grows, there is a need for better functional assessments to detect complications earlier and manage vulnerabilities to preserve independence, maintain mobility, and improve quality of life.
We previously reported differences between younger (18–49) and older adults (age ≥ 50 years) with SCD in a multi-institutional study. We showed that older adults had more chronic complications including avascular necrosis of the bone leading to hip replacement, pulmonary hypertension, transient ischemic attacks, and retinopathy[6]. In a pilot study of a geriatric assessment involving 40 adults with SCD, both younger and older adults experienced functional impairment with performance on usual gait speed similar to people aged 80 years in the general population[7].
Approximately 11% of individuals with SCD have a stroke prior to age 20 and 24% by age 45[8]. Furthermore, by age 14, 37% have silent cerebral infarcts, defined as abnormal MRI findings without a clinically diagnosed stroke[3, 8–10]. Silent cerebral infarcts are associated with impaired cognitive function and poor academic performance[11]. Compared to healthy adults, individuals with cognitive and/or motor impairment have increased difficulty performing two distinct tasks simultaneously (dual-tasking), such as walking (motor task) while dedicating attentional resources to a conversation, texting, or navigating traffic (cognitive task)[12]. Dual-tasking can result in decreased performance in one or both of the tasks (dual-task interference) relative to when each task is performed alone[13, 14]. In people with stroke, impaired dual task performance is linked to an increased risk of falls[15]. Stroke survivors are susceptible to dual-task interference, likely due to a decrease in attentional resources resulting in a need for reallocation of attention to walking to control motor performance[16]. The ability to change the attention allocation strategy during different dual-task situations is critical for safety in-home and community mobility.
The standardized administration of a dual-task paradigm involves the participant performing two distinct tasks individually (single-task) and then simultaneously (dual-task). Comparing performance in both conditions permits classification using the following cognitive-motor interference patterns: cognitive interference, cognitive facilitation, motor interference, motor facilitation, cognitive priority tradeoff, motor priority tradeoff, and no interference (Table 1)[17].
Table 1.
Classification of patterns of cognitive-motor dual-task interference.
| Dual Task Interference Classification | Definition |
|---|---|
|
| |
| Cognitive Interference | Cognitive performance remains stable and motor performance deteriorates while performing both tasks simultaneously |
| Cognitive Facilitation | Motor performance remains stable and cognitive performance improves while performing both tasks simultaneously |
| Motor Interference | Motor performance remains stable and cognitive performance deteriorates while performing both tasks simultaneously |
| Motor Facilitation | Cognitive performance remains stable and motor performance improves while performing both tasks simultaneously. |
| Cognitive Priority Tradeoff | Cognitive performance improves and motor performance deteriorates while performing both tasks simultaneously. |
| Motor Priority Tradeoff | Motor performance improves and cognitive performance deteriorates while performing both tasks simultaneously. |
| No Interference | Performance of both tasks simultaneously does not change relative to the single-task performance |
DTE indicates dual task effect.
Adapted from Plummer et al. 2013
Dual-task assessment (DTA) may prove useful in early identification of cognitive and/or functional decline in adults with SCD[18]. DTA can also be used as a tool for prescribing personalized rehabilitation for deficits related to overt strokes[19, 20]. Therefore, we sought to assess the feasibility and acceptability of DTA and describe the patterns of cognitive-motor dual-task interference in adults with SCD.
METHODS
Study Design and Participants
This study was approved by the Duke Institutional Review Board. All participants provided written informed consent. We enrolled 40 adults with SCD (20 age 18–49 years and 20 age ≥ 50 years) in a single-center prospective cohort study from October 2018 to July 2020[21, 22]. We included adults with a diagnosis of SCD confirmed by hemoglobin electrophoresis and that could speak fluent English. We excluded patients who were previously diagnosed with moderate to severe cognitive impairment by their usual outpatient provider(s), unable to self-consent, and/or were non-ambulatory.
The primary endpoint was feasibility of completing the DTA, measured as the proportion of participants who completed the DTA to those consented. We defined feasible as ≥ 80% completion. Secondary endpoints included adverse events and participant acceptability based on a satisfaction survey administered at the end of the study visit. We defined the secondary endpoints as: 1) no moderate or severe adverse events within 48 hours after completing the Sickle Cell Disease Functional Assessment (SCD-FA) and 2) acceptability as < 20% reporting difficulties in performance or understanding instructions. We performed an exploratory analysis to identify patterns of interference in this population.
Single and Dual-Task Assessment Procedures
The DTA consisted of the following: (1) cognitive task performance (single-task verbal fluency), (2) motor task performance (single-task comfortable walking), and (3) simultaneous motor and cognitive task performance (dual task). For the cognitive task, we asked participants to sit in a chair and say as many words as possible in one minute that started with the letter F. We audio-recorded and timed the verbal fluency task and then used the recording to count the number of correct words stated. For the motor task, we asked participants to walk at their normal speed for one minute along an oval-shaped path around 2 cones placed 20 meters apart in a quiet hallway in the clinic. We measured the distance walked using the AdirPro digital measuring wheel (AdirPro, Irvington, New Jersey). Next, we asked participants to walk at their usual speed and simultaneously perform the letter fluency task using the letter A for the first trial and letter S for the second trial. The dual-task performance trial with A was always conducted before the trial with S to standardize the assessment procedures for each participant. We chose F, A, and S because they are the most commonly used letters for verbal fluency assessment, are all classified as “easy” letters, and have good internal consistency with Cronbach’s alpha, α = .83 during this type of task[23]. We instructed participants according to published standards for the assessment of verbal fluency[23].
Calculating Dual-Task Effect and Determining Pattern of Dual-Task Interference
We collected data using REDCap (Research Electronic Data Capture) and used Microsoft Excel for data quality assurance. We conducted analyses in R Statistical Software version 3.6.1 (Foundation for Statistical Computing, Vienna, Austria) and used the conventional equation to calculate the relative dual-task effect (DTE)[20]. We calculated the relative DTE % on motor performance by subtracting the single task gait speed (in meters/second) from the dual task gait speed, dividing by the single task gait speed, and multiplying by 100. We used a similar process to calculate the relative DTE % on cognitive function by subtracting the number of correct words on the single task letter fluency test from the number of correct words on the dual-task letter fluency test, dividing by the correct words on the single task letter fluency test, and multiplying by 100. A positive DTE indicates an improvement in the dual-task relative to single-task performance. A negative DTE indicates deterioration in performance of the dual-task relative to single-task. We then plotted the DTE on gait against DTE on cognition and determined the pattern of dual-task interference for each participant using the framework developed by Plummer et. al. (Figure 1)[17, 20].
Figure 1.
Relative dual-task effects (DTE%) for correct words per minute for the verbal fluency task (1a. Letter A and 1b. Letter S) and gait speed for individual participants by age group. DTE values represent percent change in the dual-task relative to the single-task condition, where a negative DTE indicates that performance was worse in the dual-task than the single-task condition. Open circles represent participants whose age is greater than or equal to 50 years old and open triangles represent participants whose age is less than 50 years old. Dark grey bands represent cutoff points for each dual-task interference pattern as described previously by using 0.5 × standard deviation (SD) of the mean DTE.
We established cutoff points for each dual-task interference pattern as described previously by using 0.5 × standard deviation (SD) of the mean DTE[24, 25]. For example, to determine the cutoff point for motor interference, participants with a negative DTE for gait speed greater than 0.5 × SD of the mean gait speed for all participants were considered to have “gait interference.” We used the same method for determining cutoff points for cognitive interference. A change of 0.5 × SD is the minimal clinically important difference for health related-quality of life instruments and is the standard method used for classifying patterns of dual-task interference.
Statistical Analysis
We used descriptive statistics to summarize participant characteristics and feasibility and acceptability endpoints. We first applied a Shapiro-Wilk test to assess normality. We compared differences in DTE between groups with Wilcoxon signed rank tests for non-normally distributed data. Furthermore, a 3×2 repeated measures ANOVA was performed to compare the effect of task (single, dual Letter A, and dual Letter S) and age group (young and old) on performance in gait speed and number of correct words, both of which were normally distributed. We also assessed the relationship between age and single and dual task performance (usual gait speed and number of correct words on verbal fluency) using linear regression models.
RESULTS
Participant demographics and clinical data for all participants and by age group are provided in Table 2. The mean age of participants was 30 years (range, 20–47) for younger adults and 57 years (range, 50–71) for older adults. Approximately 48% were female, 48% were employed, 25% on disability, 10% either students or unemployed, and 5% retired. Most participants had achieved some level of college education or higher, with 25% having attained a bachelor’s degree and 18% having attained an advanced degree. The majority (58%) had a HbSS genotype, followed by 28% in the HbSC genotype, 13% in the HbSβ+ (thalassemia) genotype and one participant in the HbSβ0 genotype. Sixty percent had a severe SCD genotype (HbSS or Sβ0) and 60% were using hydroxyurea therapy. Thirteen percent had a prior stroke, 40% had sickle cell retinopathy, and 60% had a history of avascular necrosis of any joint respectively.
Table 2.
Participant demographics and clinical data.
| Demographics | All (n=40) | Age 18–49 (n=20) | Age ≥ 50 (n=20) |
|---|---|---|---|
|
| |||
| Mean age in years ± SD (range) | 44 ± 15.8 (20–71) | 30 ± 8.5 (20–47) | 57 ± 6.1 (50–71) |
|
| |||
| Female, % (n) | 48 (19) | 45 (9) | 50 (10) |
|
| |||
| Employment status, % (n): | |||
| Working | 48 (19) | 45 (9) | 50 (10) |
| Unemployed | 10 (4) | 15 (3) | 5 (1) |
| Disabled | 25 (10) | 20 (4) | 30 (6) |
| Retired | 5 (2) | 0 (0) | 10 (2) |
| Student | 10 (4) | 20 (4) | 0 (0) |
| Other | 3 (1) | 0 (0) | 5 (1) |
|
| |||
| Education level, % (n): | |||
| High school graduate or less | 20 (8) | 20 (4) | 20 (4) |
| Some college/associates/technical school | 38 (15) | 40 (8) | 35 (7) |
| Bachelor’s degree | 25 (10) | 25 (5) | 25 (5) |
| Advanced degree | 18 (7) | 15 (3) | 20 (4) |
|
| |||
| Lives alone, % (n) | 23 (9) | 25 (5) | 20 (4) |
|
| |||
| SCD genotype, % (n): | |||
| Hb SS | 58 (23) | 60 (12) | 55 (11) |
| Hb Sβ0 | 3 (1) | 5 (1) | 0 (0) |
| Hb Sβ+ | 13 (5) | 15 (3) | 10 (2) |
| Hb SC | 28 (11) | 20 (4) | 35 (7) |
|
| |||
| Range | 5.6–13.9 | 6.6 – 13.9 | 5.6 – 13.5 |
|
| |||
| Hemoglobin (g/dL), mean ± SD | 9.3 ± 2.2 | 9.8 ± 1.9 | 8.9 ± 2.4 |
|
| |||
| Hydroxyurea use, % (n) | 60 (24) | 65 (13) | 55 (11) |
|
| |||
| Chronic transfusion therapy, % (n) | 18 (7) | 20 (4) | 15 (3) |
|
| |||
| Strokes, % (n) | 13 (5) | 10 (2) | 15 (3) |
|
| |||
| Sickle cell retinopathy, % (n) | 40 (16) | 25 (5) | 55 (11) |
|
| |||
| Avascular necrosis of any joint, % (n) | 60 (24) | 40 (8) | 80 (16) |
|
| |||
| Joint Surgery, % (n) | 30 (12) | 30 (6) | 30 (6) |
|
| |||
| Hospitalized for pain in last year, % (n) | 53 (21) | 60 (12) | 45 (9) |
For the feasibility outcomes, 44 (80%) of the 55 patients approached for the study consented, 4 participants were removed by investigators due to multiple missed study visits, and 40 (91%) of consented participants completed the DTA. There were no adverse events, and no participants reported the DTA as difficult to perform or understand.
The mean (SD) single-task gait speed for all participants was 1.20 (0.17) m/s and dual-task gait speeds for Letter A and S were 1.05 (0.21) m/s and 1.06 (0.22) m/s, respectively. The average number (IQR) of correct words during the single task was 11.1 (7.1, 16.1) and during dual task was 10.9 (6.6, 15.1) and 14.5 (8, 21) for the Letter A and S trials, respectively. When we analyzed age as a continuous variable, on linear regression analysis we found that there was no significant relationship between age and single task gait speed (β = 0.0007; p= 0.737). There was no significant relationship between age and dual task performance except for relative DTE on verbal fluency for Letter S (β = −1.13; p= 0.044) (Supplemental Figure 1).
The classification patterns of dual-task interference are summarized in Table 3. Most participants (53%, n=21) on the DTA for Letter A had “Motor Interference” (Figure 1). Twenty-three percent (n=9) had “Mutual Interference”, 15% (n=6) had “Cognitive Priority Tradeoff”, 5% (n=2) had “Cognitive Facilitation”, 10% (n=4) had “No Interference”, and 1 participant (3%) had “Cognitive Interference”. For the DTA conducted with Letter S, 65% (n=26) of participants demonstrated a change in dual-task effect categorization (Figure 2). Most participants (53%, n=21) had “Cognitive-Priority-Trade-Off”. Twenty-five percent (n=10) had “Motor Interference”, 8% (n=3) had “Cognitive Facilitation”, 8% (n=3) had “No Interference”, 2 participants (5%) had “Cognitive Interference” and 1 participant (3%) had “Mutual Interference”.
Table 3.
Classification of cognitive-motor Interference patterns for Letter A and S.
| Classification | Letter A (n=40) | Letter S (n=40) |
|---|---|---|
|
| ||
| Cognitive* Interference, % (n) | 2.5 (1) | 5.0 (2) |
| Motor† Interference, % (n) | 52.5 (21) | 25.0 (10) |
| Mutual Interference, % (n) | 17.5 (7) | 2.5 (1) |
| Cognitive* Facilitation, % (n) | 5.0 (2) | 7.5 (3) |
| Motor† Facilitation, % (n) | 0 (0) | 0 (0) |
| Mutual Facilitation, % (n) | 0 (0) | 0 (0) |
| Cognitive* Priority Tradeoff, % (n) | 12.5 (5) | 52.5 (21) |
| No Interference, % (n) | 10.0 (4) | 7.5 (3) |
Cognitive Task is Verbal Fluency for 1 minute using letter F (single cognitive task), A (1st trial of dual-task), and S (2nd trial of dual-task)
Motor Task is Usual Gait Speed for 1 minute
Figure 2.
Relative dual-task effects (DTE%) for correct words per minute for the letter fluency task (2a. Letter A and 2b. Letter S) and gait speed for individual participants categorized by sickle-cell disease genotype. DTE values represent percent change in the dual-task relative to the single-task condition, where a negative DTE indicates that performance was worse in the dual-task than the single-task condition. Open circles represent participants whose sickle-cell disease category was Hb SC or HB Sβ+ and open triangles represent participants whose sickle-cell disease category was Hb SS or Hb Sβ0. Dark grey bands represent cutoff points for each dual-task interference pattern as described previously by using 0.5 × standard deviation (SD) of the mean DTE.
A Wilcoxon signed-rank test showed that both age groups demonstrated a significant increase in relative DTE on cognitive performance during the Letter S trial compared to the Letter A trial (age 18–49: p=0.005; age ≥ 50: p=0.008; Table 4); however, this change was largely driven by the young participants (single-tasking p=0.005) (Figures 1a and 1b). Furthermore, no significant difference was observed in a 3 × 2 ANOVA comparing the interaction of age group and task on gait speed (F[2, 114]=0.056, p=0.950) or number of correct words (F[2, 113]=1.09, p=0.340, Table 4). Simple main effects analysis demonstrated no significant effect of age group on either gait speed (p=0.390) or number of correct words (p=0.900); however, there was a significant effect of task on both outcomes (gait speed: p=0.004; correct words: p<0.001). Tukey’s Honest Significance Difference (HSD) post hoc analysis demonstrated a significant difference in gait speed between the single task and dual task for Letter A (p=0.007) as well as single task and dual task for Letter S (p=0.010). Additionally, Tukey’s HSD showed a significant difference in the number of correct words between the single task and dual task for Letter S (p=0.001) and between both dual tasks (p<0.001).
Table 4.
Mean values (SD/IQR) for single and dual-task gait speeds and correct number of words as a function of Age Group (Young: 18 – 49 years old, Older: ≥ 50 years old) and Task, with p-value and effect size (ηp2) for the interaction effect between Age and Task.
| Parameter | Group | n | Single Task | Dual Task Letter Letter | Age X Task | DTE (%) Letter Letter | p-value** | |||
|---|---|---|---|---|---|---|---|---|---|---|
| A | S | p * | ηp2 | A | S | |||||
|
| ||||||||||
| Gait Speed (m/s) + | Young | 20 | 1.18 ± 0.15 | 1.07 ± 0.23 | 1.08 ± 0.24 | 0.95 | 0.001 | −11.5 ± 9.1 | −10.3 ± 9.1 | 0.14 |
| Older | 20 | 1.20 ± 0.20 | 1.04 ± 0.19 | 1.04 ± 0.19 | −12.6 ± 9.5 | −12.4 ± 9.5 | 0.97 | |||
|
| ||||||||||
| Correct Number of Words ++ | Young | 20 | 10.3 (5.8, 14.8) | 11.2 (5.9, 17.1) | 15.1 (9.1, 21.1) | 0.34 | 0.02 | 24.2 (−16.1, 64.3) | 60.3 (23.3, 97.3) | 0.005 |
| Older | 20 | 11.9 (9.1, 14.7) | 10.5 (7.0, 14.0) | 14.0 (7.5, 20.5) | −9.2 (−50.8, 32.4) | 18.9 (−25.7, 63.5) | 0.008 | |||
Abbreviations: DTE = dual-task effect; SD = Standard deviation; ηp2, partial eta squared
3×2 ANOVA
Wilcoxon signed-rank test for non-normally distributed data. P-values indicate letter comparison
Variability reported as standard deviation
Variability reported as interquartile range
Finally, a Wilcoxon signed-rank test showed no significant differences based on genotype in relative DTE during the Letter A (gait speed: p=0.610; correct words: p=0.420) or Letter S trials (gait speed: p=0.210; correct words: p=0.610, Figure 2).
Discussion
This is the first publication examining dual-task assessment (DTA) and cognitive-motor interference in adults with SCD. In various populations, the cognitive load of the DTA has been shown to decrease physical performance of the assessment[26, 27]. Most of our participants experienced Cognitive-Priority-Trade-Off (number of correct responses on the verbal fluency test improved under dual-task conditions relative to single-task conditions at the expense of gait speed), Gait Interference (gait speed slowed under dual-task conditions with no deterioration in the cognitive task), and Mutual Interference (deterioration in both cognitive and motor tasks while dual-tasking relative to single tasking). These patterns are consistent with those identified in non-SCD patients who have had strokes or other cognitive impairments[17, 25, 28].
As individuals age and/or experience adverse neurologic events, their ability to successfully perform multiple tasks simultaneously without deterioration in one or more of the tasks declines[20, 29]. Individuals with SCD experience silent and overt strokes and have been shown to have poorer cognitive performance compared to healthy controls[30]. This may explain why our participants had similar patterns of dual-task interference as seen in stroke patients without SCD[20, 25, 28].
Most participants (65%) had a change in dual-task interference pattern between the first dual-task trial (Letter A) and the second dual-task trial (Letter S). A larger proportion of participants experienced Motor Interference (53%) for Letter A and Cognitive Priority Tradeoff (53%) for Letter S. This shift in DTE from reduced gait speed (e.g., posture first strategy) with dual-tasking in the first trial to prioritized cognition during the second trial may be due to several factors: 1) a sequential effect, defined as differences in scores due to the arrangement of tasks performed, which may be present as the Letter S trial was always conducted immediately after Letter A; 2) participants may have been more motivated to improve performance on the cognitive task, or shifted their prioritization towards the cognitive portion during the second dual-task attempt; 3) practice effects, defined as improvements in performance due to repeated exposure and increasing familiarity with the test; 4) the nature of the instructions. Studies on repetitive neurocognitive testing show that practice effects are more likely to occur the shorter the interval is between repeated tests. Although practice effects are a potential source of error, they may also have prognostic value. A study comparing repeat cognitive testing during a single session between individuals with mild cognitive impairment and healthy controls showed that those with mild cognitive impairment were less likely to demonstrate a practice effect[31]. Similar findings were shown in a systematic review indicating that lower practice effects are associated with neurodegenerative biomarkers and future cognitive decline[32].
Letter selection for the verbal fluency task may have also affected performance. Participants may have had an easier time with performing verbal fluency with letter ‘S’ compared to letter ‘A’. Prior studies on verbal fluency using letters F, A, and S classify these letters as “easy” with Letter S being the easiest and Letter A being the most difficult of the 3. In 1300 healthy volunteers aged 16 to 95 years, verbal fluency with F, A, and S demonstrated good internal consistency (Cronbach’s alpha, α=0.83). There were still significant differences between letters F, A, and S with the mean (SD) total number of words generated in 1 minute for F: 14.4 (4.5), A: 11.9 (4.4); and S: 15.0 (4.7)[23]. In addition, performance on letter fluency has been shown to improve with increasing education and decrease with increasing age[23].
Age had a minor impact on the DTA performance, as slightly more participants ages ≥ 50 years showed cognitive or mutual interference in comparison to those age 18–49. However, while both age groups had an improvement in cognitive performance for Letter S, the overall increase was largely driven by younger adults. Our results did not indicate a significant relationship between SCD genotype and DTA performance. HbSC and Hbβ+ on average have a milder phenotype and greater life expectancy compared to HbSS, but a range of disease complications can occur between individuals[4, 33]. Further research is needed to understand the relationship between age, SCD genotype, and DTA in adults with SCD.
Strengths and Limitations
Limitations of this study primarily surrounded procedures for performing the DTA. We instructed participants to “walk at your normal gait speed, and say as many words in one minute” which may have resulted in the participant prioritizing the number of words stated rather than allocating equal attention to both gait and verbal fluency. Also, the letter fluency test was conducted with 3 different letters in the same sequential order for all participants. As mentioned earlier, this may have introduced a sequence effect between the two DTA trials, making comparisons between letters A and S challenging. Future studies should randomize the order of the letters for each participant to avoid this potential source of error.
In terms of analyzing gait speed and stride during the DTA, there were two turns in the physical course that may have been a major area of decreased speed and reduction in cognitive performance. We did not specifically monitor the turning sections to see if there were differences in performance in those areas. Specific analysis of details related to walking, such as changes in stride and cadence throughout the course, may provide a more nuanced understanding of cognitive and functional effects[25].
Despite these limitations, our study has several strengths that support further research. We included a diverse group of adults with SCD with a wide variety of ages and SCD genotypes. The experiences of individuals with SCD can vary greatly based on the genotype and age; therefore, by including a variety of individuals and analyzing performance based on genotype and age we begin to gain an understanding of how the ability to multi-task may change throughout someone’s lifespan.
Implications for Clinical Practice
DTA has been shown in multiple studies to be a useful tool for the evaluation and rehabilitation of individuals impacted by neurological disorders[15, 20, 29]. In future studies it will be important to assess DTA across age group and as early as adolescence due to the early onset of silent strokes in SCD. DTA can serve as a tool for early detection of cognitive and motor impairment in order to guide interventions to improve function.
This assessment may be useful in patients with SCD, and our study has demonstrated the DTA to be safe and feasible in this population. Future research in larger samples is needed to determine if dual-task interference is predictive of patient-important outcomes.
Supplementary Material
Highlights -.
The main types of interference were motor interference, mutual interference, and cognitive-priority tradeoff (first trial) and cognitive priority tradeoff and motor interference (second trial). The change in interference patterns was mainly in participants 18–49 years old.
Age had a minor impact on performance; slightly more participants 50 or older showed cognitive or mutual interference than those 49 and younger.
The dual-task assessment is a feasible method of evaluating physical and cognitive function in ambulatory adults with SCD.
Acknowledgements
Our team would like to acknowledge the contribution of patients who participated in the study. In addition, we would also like to acknowledge Dr. Miriam Morey, director of Duke Pepper Center, and Heather Whitson, director of the Duke Center for Aging, for providing guidance on performing functional assessments in older adults.
Funding: Support for this study was provided by the Duke Claude D. Pepper Older Americans Independence Center (NIA P30AG028716) to C.I.O. and J.J.S., the National Institute of Aging Grants for Early Medical/Surgical Specialists’ Transition to Aging Research (GEMSSTAR) R03 under award number 5R03AG074054-02 held by C.I.O., and the Duke Center for Research to Advance Healthcare Equity (REACH Equity), which is supported by the National Institute on Minority Health and Health Disparities under award number U54MD012530 held by C.I.O.
Footnotes
Conflict of Interest Statement
A.P.S., C.I.O., J.S.P, and J.F. declare no competing financial interests. J.J. S. serves as site PI for a clinical trial of ADAMTS13 for the treatment of SCD (Takeda).
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