Purpose:Advances in artificial intelligence have produced a few predictive models in glaucoma, including a logistic regression model predicting glaucoma progression to surgery. However, uncertainty exists regarding how to integrate the wealth of information in free-text clinical notes. The purpose of this study was to predict glaucoma progression requiring surgery using deep learning (DL) approaches on data from electronic health records (EHRs), including features from structured clinical data and from natural language processing of clinical free-text notes. Design:Development of DL predictive model in an observational cohort. Participants:Adult patients with glaucoma at a single center treated from 2008 through 2020. Methods:Ophthalmology clinical notes of patients with glaucoma were identified from EHRs. Available structured data included patient demographic information, diagnosis codes, prior surgeries, and clinical information including intraocular pressure, visual acuity, and central corneal thickness. In addition, words from patients' first 120 days of notes were mapped to ophthalmology domain-specific neural word embeddings trained on PubMed ophthalmology abstracts. Word embeddings and structured clinical data were used as inputs to DL models to predict subsequent glaucoma surgery. Main Outcome Measures:Evaluation metrics included area under the receiver operating characteristic curve (AUC) and F1 score, the harmonic mean of positive predictive value, and sensitivity on a held-out test set. Results:Seven hundred forty-eight of 4512 patients with glaucoma underwent surgery. The model that incorporated both structured clinical features as well as input features from clinical notes achieved an AUC of 73% and F1 of 40%, compared with only structured clinical features, (AUC, 66%; F1, 34%) and only clinical free-text features (AUC, 70%; F1, 42%). All models outperformed predictions from a glaucoma specialist's review of clinical notes (F1, 29.5%). Conclusions:We can successfully predict which patients with glaucoma will need surgery using DL models on EHRs unstructured text. Models incorporating free-text data outperformed those using only structured inputs. Future predictive models using EHRs should make use of information from within clinical free-text notes to improve predictive performance. Additional research is needed to investigate optimal methods of incorporating imaging data into future predictive models as well.

INTRODUCTION:Low vision rehabilitation improves quality-of-life for visually impaired patients, but referral rates fall short of national guidelines. Automatically identifying, from electronic health records (EHR), patients with poor visual prognosis could allow targeted referrals to low vision services. The purpose of this study was to build and evaluate deep learning models that integrate EHR data that is both structured and free-text to predict visual prognosis.METHODS:We identified 5547 patients with low vision (defined as best documented visual acuity (VA) less than 20/40) on ≥ 1 encounter from EHR from 2009 to 2018, with ≥ 1 year of follow-up from the earliest date of low vision, who did not improve to greater than 20/40 over 1 year. Ophthalmology notes on or prior to the index date were extracted. Structured data available from the EHR included demographics, billing and procedure codes, medications, and exam findings including VA, intraocular pressure, corneal thickness, and refraction. To predict whether low vision patients would still have low vision a year later, we developed and compared deep learning models that used structured inputs and free-text progress notes. We compared three different representations of progress notes, including 1) using previously developed ophthalmology domain-specific word embeddings, and representing medical concepts from notes as 2) named entities represented by one-hot vectors and 3) named entities represented as embeddings. Standard performance metrics including area under the receiver operating curve (AUROC) and F1 score were evaluated on a held-out test set.RESULTS:Among the 5547 low vision patients in our cohort, 40.7% (N = 2258) never improved to better than 20/40 over one year of follow-up. Our single-modality deep learning model based on structured inputs was able to predict low vision prognosis with AUROC of 80% and F1 score of 70%. Deep learning models utilizing named entity recognition achieved an AUROC of 79% and F1 score of 63%. Deep learning models further augmented with free-text inputs using domain-specific word embeddings, were able to achieve AUROC of 82% and F1 score of 69%, outperforming all single- and multiple-modality models representing text with biomedical concepts extracted through named entity recognition pipelines.DISCUSSION:Free text progress notes within the EHR provide valuable information relevant to predicting patients' visual prognosis. We observed that representing free-text using domain-specific word embeddings led to better performance than representing free-text using extracted named entities. The incorporation of domain-specific embeddings improved the performance over structured models, suggesting that domain-specific text representations may be especially important to the performance of predictive models in highly subspecialized fields such as ophthalmology.

BACKGROUND Central arterial stiffness and brain hypoperfusion are emerging risk factors of Alzheimer's disease (AD). Aerobic exercise training (AET) may improve central arterial stiffness and brain perfusion. OBJECTIVE To investigate the effects of AET on central arterial stiffness and cerebral blood flow (CBF) in patients with amnestic mild cognitive impairment (MCI), a prodromal stage of AD. METHODS This is a proof-of-concept, randomized controlled trial that assigned 70 amnestic MCI patients into a 12-month program of moderate-to-vigorous AET or stretching-and-toning (SAT) intervention. Carotid β-stiffness index and CBF were measured by color-coded duplex ultrasonography and applanation tonometry. Total CBF was measured as the sum of CBF from both the internal carotid and vertebral arteries, and divided by total brain tissue mass assessed with MRI to obtain normalized CBF (nCBF). Episodic memory and executive function were assessed using standard neuropsychological tests (CVLT-II and D-KEFS). Changes in cardiorespiratory fitness were measured by peak oxygen uptake (VO2peak). RESULTS Total 48 patients (29 in SAT and 19 in AET) were completed one-year training. AET improved VO2peak, decreased carotid β-stiffness index and CBF pulsatility, and increased nCBF. Changes in VO2peak were associated positively with changes in nCBF (r = 0.388, p = 0.034) and negatively with carotid β-stiffness index (r = -0.418, p = 0.007) and CBF pulsatility (r = -0.400, p = 0.014). Decreases in carotid β-stiffness were associated with increases in cerebral perfusion (r = -0.494, p = 0.003). AET effects on cognitive performance were minimal compared with SAT. CONCLUSION AET reduced central arterial stiffness and increased CBF which may precede its effects on neurocognitive function in patients with MCI.

OBJECTIVE:To develop and evaluate novel word embeddings (WEs) specific to ophthalmology, using text corpora from published literature and electronic health records (EHR).MATERIALS AND METHODS:We trained ophthalmology-specific WEs using 121,740 PubMed abstracts and 89,282 EHR notes using word2vec continuous bag-of-words architecture. PubMed and EHR WEs were compared to general domain GloVe WEs and general biomedical domain BioWordVec embeddings using a novel ophthalmology-domain-specific 200-question analogy test and prediction of prognosis in 5547 low vision patients using EHR notes as inputs to a deep learning model.RESULTS:We found that many words representing important ophthalmic concepts in the EHR were missing from the general domain GloVe vocabulary, but covered in the ophthalmology abstract corpus. On ophthalmology analogy testing, PubMed WEs scored 95.0 %, outperforming EHR (86.0 %) and GloVe (91.0 %) but less than BioWordVec (99.5 %). On predicting low vision prognosis, PubMed and EHR WEs resulted in similar AUROC (0.830; 0.826), outperforming GloVe (0.778) and BioWordVec (0.784).CONCLUSION:We found that using ophthalmology domain-specific WEs improved performance in ophthalmology-related clinical prediction compared to general WEs. Deep learning models using clinical notes as inputs can predict the prognosis of visually impaired patients. This work provides a framework to improve predictive models using domain-specific WEs.

Aerobic exercise (AE) has recently received increasing attention in the prevention of Alzheimer's disease (AD). There is some evidence that it can improve neurocognitive function in elderly individuals. However, the mechanism of these improvements is not completely understood. In this prospective clinical trial, thirty amnestic mild cognitive impairment participants were enrolled into two groups and underwent 12 months of intervention. One group (n = 15) performed AE training (8M/7F, age = 66.4 years), whereas the other (n = 15) performed stretch training (8M/7F, age = 66.1 years) as a control intervention. Both groups performed 25-30 minutes training, 3 times per week. Frequency and duration were gradually increased over time. Twelve-month AE training improved cardiorespiratory fitness (p = 0.04) and memory function (p = 0.004). Cerebral blood flow (CBF) was measured at pre- and post-training using pseudo-continuous-arterial-spin-labeling MRI. Relative to the stretch group, the AE group displayed a training-related increase in CBF in the anterior cingulate cortex (p = 0.016). Furthermore, across individuals, the extent of memory improvement was associated with CBF increases in anterior cingulate cortex and adjacent prefrontal cortex (voxel-wise p < 0.05). In contrast, AE resulted in a decrease in CBF of the posterior cingulate cortex, when compared to the stretch group (p = 0.01). These results suggest that salutary effects of AE in AD may be mediated by redistribution of blood flow and neural activity in AD-sensitive regions of brain.

AbstractBackgroundAlzheimer’s Disease (AD) and AD related dementia (ADRD) are under‐recognized and under‐treated in individuals with Asian cultural heritages due to the social stigma. Asians account for more than 60% of the world population. With the rapidly aging society, it is imperative to effectively detect and prevent AD & ADRD prior to its onset in order to alleviate social healthcare burden in the next decades to come.MethodWe conducted a 1‐year observational study in 42 non‐AD adults of Asian races (age=55±9, m=13, f=29) to monitor changes in gait profile using augmented reality (AR) technology via RADAR (i.e. Report for Alzheimer’s Disease Accumulated Risks), an in‐house smart device app developed by the PI. Gait profile (i.e. velocity (m/s), stride length (cm), deviation (%)) was recorded and calculated at baseline, 6 months, and 12 months with and without dual‐task conditions (i.e. delayed recall+sorting). Cognitive performance was evaluated using previously described methods. To the best of our knowledge, this was the first attempt to use a novel behavioral marker (i.e. gait deteriorations under dual‐task conditions) to predict early stages of cognitive decline in Asian adults.ResultUsing multiple linear regression modeling, we found that gait velocity decline (i.e. >10%Δ compared to baseline under dual‐task conditions or >20%Δ compared to non‐dual‐task condition) independently predicts AD risks (adjusted R2=.38, p=.01) in Asian adults.ConclusionWe have demonstrated a cost‐effective alternative instrument that is shown to be sensitive in detecting early dementia. Current consensus emphasizes the prominence in early AD diagnosis. Although existing diagnostic tools such as positron emission tomography (PET) is effective in detecting beta‐amyloid protein, the hallmark of AD, PET scan is costly and not readily accessible for most patients. Emerging literature suggests that gait deteriorations at middle age are predictive of AD. Further more, AD prevalence and care in Asian people is under‐recognized; this novel tool that can be implemented in those cultures that might be reluctant to seek professional consultation due to cultural bias.

Cerebral white matter (WM) represents the structural substrate of neuronal communications which is damaged by Alzheimer’s disease (AD). Aerobic exercise training (AET) may improve WM integrity in cognitively normal older adults, but its efficacy remains unknown in patients with amnestic mild cognitive impairment (MCI), a prodromal phase of AD dementia. Therefore, we conducted a proof-of-concept study that randomized 70 amnestic MCI patients to a 1-year program of AET or a non-aerobic stretching and toning (SAT), active control group. Thirty-six patients completed both baseline and follow-up MRI scans, and cerebral WM integrity was measured by WM lesion volume and diffusion characteristics using fluid-attenuated-inversion-recovery and diffusion tensor imaging respectively. Peak oxygen uptake (VO2peak) and neuropsychological function were also measured. At baseline and 1-year follow-up, WM lesion volume and diffusion characteristics were similar between the AET and SAT groups, although VO2peak significantly improved after AET. The AET group showed slight improvement in neuropsychological performance. When analyzing individual data, tract-based spatial statistics demonstrated that VO2peak improvements are associated with attenuated elevations in mean and axial diffusivities, particularly the anterior WM fiber tracts (e.g., genu of corpus callosum). In patients with amnestic MCI, we found that although AET intervention did not improve WM integrity at group level analysis, individual cardiorespiratory fitness gains were associated with improved WM tract integrity of the prefrontal cortex.

OBJECTIVES:To systematically summarize the evidence of gait tests as screening tools for mild cognitive impairment (MCI). DATA SOURCES:Electronic database searches were conducted in PubMed, EBSCO, Cochrane, Web of Science, Ovid, China National Knowledge Infrastructure, WanFang, and SinoMed, and studies published before November 30, 2018, were included. STUDY SELECTION:Synonyms of MCI, gait, and cognitive-motor interference (CMI) were searched. Studies that analyzed gait change of people with MCI in single- or dual-task gait tests were included. DATA EXTRACTION:The quality of the included studies was assessed with Downs and Black methodological quality appraisal tools. Study characteristics, participants' characteristics, test descriptions, and results were extracted from the included studies. DATA SYNTHESIS:Twenty-two studies involving 1928 participants were included. Meta-analysis showed that gait velocity difference in dual task (effect size [ES]=-0.89) were more obvious than in single task (ES=-0.74) between older adults with and without MCI, and the ES increased with the complexity of cognitive load (countdown by 1s, ES=-0.83; verbal fluency, ES=-0.96; serial reduction by 7s, ES=-1.26). The dual-task cost of gait velocity showed high sensitivity (ES=0.90) in detecting MCI. Meta-regression analysis demonstrated strong criterion-related validity between the CMI of gait velocity and the Montreal Cognitive Assessment score. CONCLUSIONS:In comparison with the single-task gait test, gait change under cognitive load is more pronounced in older adults with MCI. CMI of gait velocity can be a potential screening tool for MCI in elderly persons.

Introduction: Atrial fibrillation (AF) is the leading cause of fatal ischemic stroke. Although stroke risk factors can be identified using available clinical assessment tools, current standard of care primarily relies on antithrombotic/anticoagulation therapy and fails to proactively modify the underlying risk factors contributing to stroke. The purpose of this study was to determine the effect of moderate-to-high intensity aerobic training in alleviating stroke risk by reducing arterial stiffness and AF burden in AF patients. Methods: Forty-two patients with clinically diagnosed AF between the ages of 65-75 were recruited and randomly assigned to either a 3-month aerobic training with moderate to high intensity (i.e. >80%MHR, 45 minutes, 3-4 days/week) or a health education group. Vascular integrity was evaluated by carotid-radial pulse-wave-velocity (PWVcr), carotid intima-media-thickness (cIMT) and end-diastolic velocity (EDV); AF burden was quantified using a 2-week continuous cardiac event monitor (ZioXT patch, iRhythm); stroke risk was assessed using the CHA 2 DS 2 -VASc scale. All measurements were assessed before and after training. Results: Thirty AF patients participated in the aerobic training group (f=18, age=70±3) and 12 participated in the health education group (f=8, age=69±4). After 3 months, the aerobic training group exhibited significant improvement in PWVcr (12.6±3.2m/s vs. 9.6±2.1m/s, p=0.001), EDV (14.3±2.5cm/s vs. 15.9±2.1cm/s, p=0.01), AF burden (84.3±12.3% vs. 66.6±1.3%, p=0.01), and CHA 2 DS 2 -VASc score (2.2±1.3 vs. 0.9±0.9, p=0.05). In addition, the change of EDV is predictive of the stroke risk (r 2 =0.32, p=0.01). No significant change was observed in the health education group. Conclusion: We found that 3 months of supervised aerobic training at moderate-to-high intensity level appeared to improve vascular integrity, alleviate AF burden, and reduce stroke risk in patients with AF. More importantly, the AF burden and stroke risk are modulated by improvements in vascular functions. This finding warrants future large-scale investigations to examine the dose-response relationship of exercise reducing ischemic stroke risk.

BACKGROUND:The current evidence is inconclusive to support the benefits of aerobic exercise training (AET) for preventing neurocognitive decline in patients with amnestic mild cognitive impairment (aMCI).OBJECTIVE:To examine the effect of a progressive, moderate-to-high intensity AET program on memory and executive function, brain volume, and cortical amyloid-β (Aβ) plaque deposition in aMCI patients.METHODS:This is a proof-of-concept trial that randomized 70 aMCI patients to 12 months of AET or stretching and toning (SAT, active control) interventions. Primary neuropsychological outcomes were assessed by using the California Verbal Learning Test-second edition (CVLT-II) and the Delis-Kaplan Executive Function System (D-KEFS). Secondary outcomes were the global and hippocampal brain volumes and the mean cortical and precuneus Aβ deposition.RESULTS:Baseline cognitive scores were similar between the groups. Memory and executive function performance improved over time but did not differ between the AET and SAT groups. Brain volume decreased and precuneus Aβ plaque deposition increased over time but did not differ between the groups. Cardiorespiratory fitness was significantly improved in the AET compared with SAT group. In amyloid positive patients, AET was associated with reduced hippocampal atrophy when compared with the SAT group.CONCLUSION:The AET and SAT groups both showed evidence of slightly improved neuropsychological scores in previously sedentary aMCI patients. However, these interventions did not prevent brain atrophy or increases in cortical Aβ deposition over 12 months. In amyloid positive patients, AET reduced hippocampal atrophy when compared with the SAT group.

Peak oxygen consumption (VO2peak) is an independent predictor of all-cause and dementia related mortality. We aimed to determine whether individuals with mild cognitive impairment (MCI), who are at risk for dementia, are capable of eliciting a valid VO2peak during a maximal exercise test. Secondarily, we examined whether individuals with MCI had differing cardiovascular responses during graded peak exercise testing and subsequent recovery compared with individuals with normal cognition (NC). Patients with MCI (n=71, age=65.0 ± 6.3 yr) and NC adults (n=122, age=66.2 ± 6.6 yr) underwent graded peak exercise testing to assess VO2peak. Heart rate (HR) and blood pressure were measured throughout exercise testing and during 10 minutes of recovery. 1) VO2 plateau; 2) respiratory exchange ratio ≥1.08; 3) lactate ≥7.0 mmol/dL; 4) maximal HR within 5 beats/min of age-predicted max; 5) rating of perceived exertion on the Borg Scale of ≥17 were defined a priori as indicators of maximal effort. Linear mixed modeling was used to assess cardiovascular responses to graded exercise testing stages. Individuals with MCI and NC subjects were similar in age, sex, and BMI. Those with MCI (64.8%) and NC (63.1%) did not differ in their rate of satisfying ≥3 maximal physiological criteria. At VO2peak, MCI and NC subjects did not differ in VO2, cardiac output, HR, arteriovenous difference, systolic (SBP) or diastolic blood pressure, while stroke volume was elevated in individuals with MCI. When assessing physiological responses to stages of exercise, subjects with MCI demonstrated an attenuated VO2 uptake response during exercise testing compared with NC (group*stage, p=0.007). HR recovery from graded exercise testing did not differ between groups.

BACKGROUND:Mounting evidence showed the self-reported levels of physical activity are positively associated with white matter (WM) integrity and cognitive performance in normal adults and patients with mild cognitive impairment (MCI). However, the objective measure of cardiorespiratory fitness (CRF) was not used in these studies. OBJECTIVE:To determine the associations of CRF measured by maximal oxygen uptake (VO2max) with WM fiber integrity and neurocognitive performance in older adults with MCI. METHODS:Eighty-one participants (age = 65±7 years, 43 women), including 26 cognitively normal older adults and 55 amnestic MCI patients, underwent VO2max test to measure CRF, diffusion tensor imaging (DTI) to assess WM fiber integrity, and neurocognitive assessment focused on memory and executive function. DTI data were analyzed by the tract-based spatial statistics and region-of-interest approach. RESULTS:Cognitively normal older adults and MCI patients were not different in global WM fiber integrity and VO2max. VO2max was associated positively with DTI metrics of fractional anisotropy in ∼54% WM fiber tracts, and negatively with mean and radial diffusivities in ∼46% and ∼56% of the WM fiber tracts. The associations of VO2max with DTI metrics remained statistically significant after adjustment of age, sex, body mass index, WM lesion burden, and MCI status. The DTI metrics obtained from the area that correlated to VO2max were associated with executive function performance in MCI patients. CONCLUSIONS:Higher levels of CRF are associated with better WM fiber integrity, which in turn is correlated with better executive function performance in MCI patients.

Although Post-stroke fatigue (PSF) has gained attention in recent years, clinicians and caregivers are still faced with the challenge of diagnosis and management of PSF. The purpose of this review is to provide understanding of the nature of PSF and potential clinical implication for healthcare providers.

Research & Investigations in Sports Medicine Old Dog, New Tricks: Learning Novel Motor Tasks May Enhance Brain Health in Older Adults Benjamin Tseng* and Colby Craddock Department of Health and Kinesiology, The University of Texas at Tyler, USA *Corresponding author: Benjamin Tseng, PhD, Laboratory of Brain Aging and Neuromotor Behavior, Department of Health and Kinesiology, The University of Texas at Tyler, 3900 University Blvd, Tyler, TX 75799, USA Submission: February 24, 2018; Published: February 27, 2018 DOI: 10.31031/RISM.2018.02.000526 ISSN: 2577-1914 Volume2 Issue1

Amnestic mild cognitive impairment represents an early stage of Alzheimer’s disease, and characterization of physiological alterations in mild cognitive impairment is an important step toward accurate diagnosis and intervention of this condition. To investigate the extent of neurodegeneration in patients with mild cognitive impairment, whole-brain cerebral metabolic rate of oxygen in absolute units of µmol O2/min/100 g was quantified in 44 amnestic mild cognitive impairment and 28 elderly controls using a novel, non-invasive magnetic resonance imaging method. We found a 12.9% reduction (p = 0.004) in cerebral metabolic rate of oxygen in mild cognitive impairment, which was primarily attributed to a reduction in the oxygen extraction fraction, by 10% (p = 0.016). Global cerebral blood flow was not found to be different between groups. Another aspect of vascular function, cerebrovascular reactivity, was measured by CO2-inhalation magnetic resonance imaging and was found to be equivalent between groups. Therefore, there seems to be a global, diffuse diminishment in neural function in mild cognitive impairment, while their vascular function did not show a significant reduction.

Key points Cerebral autoregulation (CA) is a key mechanism to protect brain perfusion in the face of changes in arterial blood pressure, but little is known about individual variability of CA and its relationship to the presence of brain white matter hyperintensity (WMH) in older adults, a type of white matter lesion related to cerebral small vessel disease (SVD). This study demonstrated the presence of large individual variability of CA in healthy older adults during vasoactive drug‐induced changes in arterial pressure assessed at the internal carotid and vertebral arteries. We also observed, unexpectedly, that it was the ‘over‐’ rather than the ‘less‐reactive’ CA measured at the vertebral artery that was associated with WMH severity. These findings challenge the traditional concept of CA and suggest that the presence of cerebral SVD, manifested as WMH, is associated with posterior brain hypoperfusion during acute increase in arterial pressure. AbstractThis study measured the individual variability of static cerebral autoregulation (CA) and determined its associations with brain white matter hyperintensity (WMH) in older adults. Twenty‐seven healthy older adults (13 females, 66 ± 6 years) underwent assessment of CA during steady‐state changes in mean arterial pressure (MAP) induced by intravenous infusion of sodium nitroprusside (SNP) and phenylephrine. Cerebral blood flow (CBF) was measured using colour‐coded duplex ultrasonography at the internal carotid (ICA) and vertebral arteries (VA). CA was quantified by a linear regression slope (CA slope) between percentage changes in cerebrovascular resistance (CVR = MAP/CBF) and MAP relative to baseline values. Periventricular and deep WMH volumes were measured with T2‐weighted magnetic resonance imaging. MAP was reduced by −11 ± 7% during SNP, and increased by 21 ± 8% during phenylephrine infusion. CA demonstrated large individual variability with the CA slopes ranging from 0.37 to 2.20 at the ICA and from 0.17 to 3.18 at the VA; no differences in CA were found between the ICA and VA. CA slopes measured at the VA had positive correlations with the total and periventricular WMH volume (r = 0.55 and 0.59, P < 0.01). Collectively, these findings demonstrated the presence of large individual variability of CA in older adults, and that, when measured in the posterior cerebral circulation, it is the higher rather than lower CA reactivity that is associated with WMH severity.

Cerebral hypoperfusion elevates the risk of brain white matter (WM) lesions and cognitive impairment. Central artery stiffness impairs baroreflex, which controls systemic arterial perfusion, and may deteriorate neuronal fiber integrity of brain WM. The purpose of this study was to examine the associations among brain WM neuronal fiber integrity, baroreflex sensitivity (BRS), and central artery stiffness in older adults. Fifty-four adults (65 ± 6 years) with normal cognitive function or mild cognitive impairment (MCI) were tested. The neuronal fiber integrity of brain WM was assessed from diffusion metrics acquired by diffusion tensor imaging. BRS was measured in response to acute changes in blood pressure induced by bolus injections of vasoactive drugs. Central artery stiffness was measured by carotid–femoral pulse wave velocity (cfPWV). The WM diffusion metrics including fractional anisotropy (FA) and radial (RD) and axial (AD) diffusivities, BRS, and cfPWV were not different between the control and MCI groups. Thus, the data from both groups were combined for subsequent analyses. Across WM, fiber tracts with decreased FA and increased RD were associated with lower BRS and higher cfPWV, with many of the areas presenting spatial overlap. In particular, the BRS assessed during hypotension was strongly correlated with FA and RD when compared with hypertension. Executive function performance was associated with FA and RD in the areas that correlated with cfPWV and BRS. These findings suggest that baroreflex-mediated control of systemic arterial perfusion, especially during hypotension, may play a crucial role in maintaining neuronal fiber integrity of brain WM in older adults.

BACKGROUND With age, performance of motor tasks becomes more reliant on cognitive resources to compensate for the structural and functional declines in the motor control regions in the brain. We hypothesized that participants with amnestic mild cognitive impairment (aMCI) are more prone to motor dysfunctions than cognitively normal older adults under dual-task conditions where competitive demands challenge cognitive functions while performing a motor task simultaneously. METHODS Sixteen aMCI participants (females=9, age=64±5yrs, clinical dementia rating score=0.5) and 10 age- and education-matched cognitively normal adults (females=5, age=62±6yrs) participated. Using a 10-meter-walk test (10MW), gait velocity was recorded at baseline and under 4 different dual-task (DT) conditions designed to challenge working memory, executive function, and episodic memory. Specifically, DT1: verbal fluency; DT2: 5-digit backward span; DT3: serial-7 subtraction; and DT4: 3-item delayed recall. Physical function was measured by Timed Up-and-Go (TUG), simple reaction time (RT) to a free-falling yardstick, and functional reach (FR). RESULTS No difference was found in physical functions, aerobic fitness, and exercise cardiopulmonary responses between aMCI participants and controls. However, aMCI participants showed more pronounced gait slowing from baseline when compared to the controls (p<0.05; p=0.001; p<0.001; p<0.001, respectively). CONCLUSIONS Our finding supports the theory of shared resource of motor and cognitive control. Participants with aMCI manifested more gait slowing than cognitively-normal older adults under DT conditions, with the largest differences during tests of working and episodic memory. The outcome of dual-task assessment shows promise as a potential marker for detection of aMCI and early Alzheimer disease.