MoCA Intraindividual Cognitive Variability in Older Adults With Type 1 Diabetes.

Older adults with type 1 diabetes (T1D) may have an elevated risk of developing Alzheimer disease and related dementia. Higher intraindividual cognitive variability (IICV) has been proposed as a novel risk factor of Alzheimer disease and related dementia. Here, we examined the association between cross-domain IICV measured using the Montreal Cognitive Assessment (MoCA) and cognitive impairment measured using traditional neuropsychological tests in older individuals with T1D. Participants with T1D (N=201) completed both the MoCA and a battery of traditional neuropsychological tests. Participants with cognitive impairment, determined using traditional tests, had significantly higher IICV scores and significantly lower total MoCA scores ( P <0.001). However, the effect of the total score was greater than that of the IICV score on the likelihood of cognitive impairment (total odds ratio=3.50, IICV odds ratio=2.03, P <0.001). The MoCA total score performed better than the MoCA IICV score in identifying T1D individuals classified with cognitive impairment.

Ecological Momentary Assessment of Cognition in Clinical and Community Samples: Reliability and Validity Study.

BACKGROUND: The current methods of evaluating cognitive functioning typically rely on a single time point to assess and characterize an individual's performance. However, cognitive functioning fluctuates within individuals over time in relation to environmental, psychological, and physiological contexts. This limits the generalizability and diagnostic utility of single time point assessments, particularly among individuals who may exhibit large variations in cognition depending on physiological or psychological context (eg, those with type 1 diabetes [T1D], who may have fluctuating glucose concentrations throughout the day). OBJECTIVE: We aimed to report the reliability and validity of cognitive ecological momentary assessment (EMA) as a method for understanding between-person differences and capturing within-person variation in cognition over time in a community sample and sample of adults with T1D. METHODS: Cognitive performance was measured 3 times a day for 15 days in the sample of adults with T1D (n=198, recruited through endocrinology clinics) and for 10 days in the community sample (n=128, recruited from TestMyBrain, a web-based citizen science platform) using ultrabrief cognitive tests developed for cognitive EMA. Our cognitive EMA platform allowed for remote, automated assessment in participants' natural environments, enabling the measurement of within-person cognitive variation without the burden of repeated laboratory or clinic visits. This allowed us to evaluate reliability and validity in samples that differed in their expected degree of cognitive variability as well as the method of recruitment. RESULTS: The results demonstrate excellent between-person reliability (ranging from 0.95 to 0.99) and construct validity of cognitive EMA in both the sample of adults with T1D and community sample. Within-person reliability in both samples (ranging from 0.20 to 0.80) was comparable with that observed in previous studies in healthy older adults. As expected, the full-length baseline and EMA versions of TestMyBrain tests correlated highly with one another and loaded together on the expected cognitive domains when using exploratory factor analysis. Interruptions had higher negative impacts on accuracy-based outcomes (ß=-.34 to -.26; all P values <.001) than on reaction time-based outcomes (ß=-.07 to -.02; P<.001 to P=.40). CONCLUSIONS: We demonstrated that ultrabrief mobile assessments are both reliable and valid across 2 very different clinic versus community samples, despite the conditions in which cognitive EMAs are administered, which are often associated with more noise and variability. The psychometric characteristics described here should be leveraged appropriately depending on the goals of the cognitive assessment (eg, diagnostic vs everyday functioning) and the population being studied.

Usefulness of the Montreal Cognitive Assessment in Older Adults With Type 1 Diabetes.

Objective: Older adults with type 1 diabetes are at high risk for cognitive impairment, yet the usefulness of common cognitive screening instruments has not been evaluated in this population. Methods: A total of 201 adults ≥60 years of age with type 1 diabetes completed a battery of neuropsychological measures and the Montreal Cognitive Assessment (MoCA). Receiver operating characteristic (ROC) curves and Youden indices were used to evaluate overall screening test performance and to select an optimal MoCA cutoff score for detecting low cognitive performance, as defined as two or more neuropsychological test performances ≥1.5 SD below demographically corrected normative data. Results: The ROC area under the curve (AUC) was 0.745 (P < 0.001). The publisher-recommended cutoff score of <26 resulted in sensitivity of 60.4% and specificity of 71.4%, whereas a cutoff score of <27 resulted in sensitivity of 75.0% and specificity of 61.0%. The Youden indices for these cutoff scores were 0.318 and 0.360, respectively. Minimally acceptable sensitivity (i.e., >0.80) was obtained when using a cutoff score of <28, whereas >0.80 specificity was obtained with a cutoff score of <25. Conclusions: The MoCA has modest overall performance (AUC 0.745) as a cognitive screening instrument in older adults with type 1 diabetes. The standard cutoff score of <26/30 may not adequately detect individuals with neuropsychological testing-defined abnormal cognition. The optimal MoCA cutoff score (based on the Youden index) was <27/30. A score of <28 resulted in acceptable sensitivity but was accompanied by low specificity (42%). Future studies with a more diverse population are needed to confirm these findings.

Effect of Continuous Glucose Monitoring on Hypoglycemia in Older Adults With Type 1 Diabetes: A Randomized Clinical Trial.

Importance: Continuous glucose monitoring (CGM) provides real-time assessment of glucose levels and may be beneficial in reducing hypoglycemia in older adults with type 1 diabetes. Objective: To determine whether CGM is effective in reducing hypoglycemia compared with standard blood glucose monitoring (BGM) in older adults with type 1 diabetes. Design, Setting, and Participants: Randomized clinical trial conducted at 22 endocrinology practices in the United States among 203 adults at least 60 years of age with type 1 diabetes. Interventions: Participants were randomly assigned in a 1:1 ratio to use CGM (n = 103) or standard BGM (n = 100). Main Outcomes and Measures: The primary outcome was CGM-measured percentage of time that sensor glucose values were less than 70 mg/dL during 6 months of follow-up. There were 31 prespecified secondary outcomes, including additional CGM metrics for hypoglycemia, hyperglycemia, and glucose control; hemoglobin A1c (HbA1c); and cognition and patient-reported outcomes, with adjustment for multiple comparisons to control for false-discovery rate. Results: Of the 203 participants (median age, 68 [interquartile range {IQR}, 65-71] years; median type 1 diabetes duration, 36 [IQR, 25-48] years; 52% female; 53% insulin pump use; mean HbA1c, 7.5% [SD, 0.9%]), 83% used CGM at least 6 days per week during month 6. Median time with glucose levels less than 70 mg/dL was 5.1% (73 minutes per day) at baseline and 2.7% (39 minutes per day) during follow-up in the CGM group vs 4.7% (68 minutes per day) and 4.9% (70 minutes per day), respectively, in the standard BGM group (adjusted treatment difference, -1.9% (-27 minutes per day); 95% CI, -2.8% to -1.1% [-40 to -16 minutes per day]; P <.001). Of the 31 prespecified secondary end points, there were statistically significant differences for all 9 CGM metrics, 6 of 7 HbA1c outcomes, and none of the 15 cognitive and patient-reported outcomes. Mean HbA1c decreased in the CGM group compared with the standard BGM group (adjusted group difference, -0.3%; 95% CI, -0.4% to -0.1%; P <.001). The most commonly reported adverse events using CGM and standard BGM, respectively, were severe hypoglycemia (1 and 10), fractures (5 and 1), falls (4 and 3), and emergency department visits (6 and 8). Conclusions and Relevance: Among adults aged 60 years or older with type 1 diabetes, continuous glucose monitoring compared with standard blood glucose monitoring resulted in a small but statistically significant improvement in hypoglycemia over 6 months. Further research is needed to understand the long-term clinical benefit. Trial Registration: ClinicalTrials.gov Identifier: NCT03240432.

The relationship between neuropsychological assessment, numeracy, and functional status in older adults with type 1 diabetes.

While data are accumulating on the association between neuropsychological performance and real-world endpoints, less is known about the association with medical self-management skills. The self-management of type 1 diabetes (T1D) is often complex, and mismanagement can result in hypoglycaemia and hyperglycaemia and associated morbidity and mortality. The T1D Exchange conducted a case-control study evaluating factors associated with severe hypoglycaemia in older adults (≥ 60 years old) with longstanding T1D (≥ 20 years). A battery of neuropsychological and functional assessments was administered, including measures of diabetes-specific self-management skill (diabetes numeracy) and instrumental activities of daily living (IADL). After adjusting for confounding variables, diabetes numeracy was related to memory and complex speeded attention; while IADL were associated with simple processing speed, executive functioning, complex speeded attention and dominant hand dexterity. The severity of overall cognitive deficit was uniquely associated with both diabetes numeracy and IADL, when controlling for age, education, frailty and depression. This study demonstrates that the cognitive deficits in older adults with T1D have functional implications for both diabetes management and IADL. Further research is needed to determine specific interventions to maximise diabetes self-management in older adults with declining cognition.

Medication Intervention for Chronic Kidney Disease Patients Transitioning from Hospital to Home: Study Design and Baseline Characteristics.

BACKGROUND: The hospital readmission rate in the population with chronic kidney disease (CKD) is high and strategies to reduce this risk are urgently needed. METHODS: The CKD-Medication Intervention Trial (CKD-MIT; www.clinicaltrials.gov; NCTO1459770) is a single-blind (investigators), randomized, clinical trial conducted at Providence Health Care in Spokane, Washington. Study participants are hospitalized patients with CKD stages 3-5 (not treated with kidney replacement therapy) and acute illness. The study intervention is a pharmacist-led, home-based, medication management intervention delivered within 7 days after hospital discharge. The primary outcome is a composite of hospital readmissions and visits to emergency departments and urgent care centers for 90 days following hospital discharge. Secondary outcomes are achievements of guideline-based targets for CKD risk factors and complications. RESULTS: Enrollment began in February 2012 and ended in May 2015. At baseline, the age of participants was 69 ± 11 years (mean ± SD), 50% (77 of 155) were women, 83% (117 of 141) had hypertension and 56% (79 of 141) had diabetes. At baseline, the estimated glomerular filtration rate was 41 ± 14 ml/min/1.73 m2 and urine albumin-to-creatinine ratio was 43 mg/g (interquartile range 8-528 mg/g). The most frequent diagnosis category for the index hospital admission was cardiovascular diseases at 34% (53 of 155), but the most common single diagnosis for admission was community-acquired acute kidney injury at 10% (16 of 155). CONCLUSION: Participants in CKD-MIT are typical of acutely ill hospitalized patients with CKD. A medication management intervention after hospital discharge is under study to reduce post-hospitalization acute care utilization and to improve CKD management.

Cognition in Adults and Older Adults With Type 1 Diabetes: Chicken or Egg?

IN BRIEF Cognitive impairment and cognitive decline are common in adults with type 1 diabetes. Although several diabetes-related variables have been associated with cognitive functioning in both cross-sectional and longitudinal studies, inconsistencies remain. This is particularly true in older adults. Cognitive impairment appears to be both a consequence of and a risk factor for poor diabetes self-management and associated glycemic outcomes. Interventions such as cognitive compensatory strategies, assistive technology, and simplified treatment regimens may limit the impact of cognitive impairment on self-management in adults and older adults with type 1 diabetes.

Mid-life sleep is associated with cognitive performance later in life in aging American Indians: data from the Strong Heart Study.

Background: Sleep-related disorders have been associated with cognitive decline and neurodegeneration. American Indians are at increased risk for dementia. Here, we aim to characterize, for the first time, the associations between sleep characteristics and subsequent cognitive performance in a sample of aging American Indians. Methods: We performed analyses on data collected in two ancillary studies from the Strong Heart Study, which occurred approximately 10 years apart with an overlapping sample of 160 American Indians (mean age at follow-up 73.1, standard deviation 5.6; 69.3% female and 80% with high school completion). Sleep measures were derived by polysomnography and self-reported questionnaires, including sleep timing and duration, sleep latency, sleep stages, indices of sleep-disordered breathing, and self-report assessments of poor sleep and daytime sleepiness. Cognitive assessment included measures of general cognition, processing speed, episodic verbal learning, short and long-delay recall, recognition, and phonemic fluency. We performed correlation analyses between sleep and cognitive measures. For correlated variables, we conducted separate linear regressions. We analyzed the degree to which cognitive impairment, defined as more than 1.5 standard deviations below the average Modified Mini Mental State Test score, is predicted by sleep characteristics. All regression analyses were adjusted for age, sex, years of education, body mass index, study site, depressive symptoms score, difference in age from baseline to follow-up, alcohol use, and presence of APOE e4 allele. Results: We found that objective sleep characteristics measured by polysomnography, but not subjective sleep characteristics, were associated with cognitive performance approximately 10 years later. Longer sleep latency was associated with worse phonemic fluency (ß = -0.069, p = 0.019) and increased likelihood of being classified in the cognitive impairment group later in life (odds ratio 1.037, p = 0.004). Longer duration with oxygen saturation < 90% was associated with better immediate verbal memory, and higher oxygen saturation with worse total learning, short and long-delay recall, and processing speed. Conclusion: In a sample of American Indians, sleep characteristics in midlife were correlated with cognitive performance a decade later. Sleep disorders may be modifiable risk factors for cognitive impairment and dementia later in life, and suitable candidates for interventions aimed at preventing neurodegenerative disease development and progression.

Risk factors associated with cognitive performance and cognitive impairment in older adults with type 1 diabetes: Data from the Wireless Innovation for Seniors with Diabetes Mellitus (WISDM) study.

BACKGROUND: Adults with type 1 diabetes (T1D) are considered at increased risk for cognitive impairment and accelerated brain aging. However, longitudinal data on cognitive impairment and dementia in this population are scarce. OBJECTIVE: To identify risk factors associated with cognitive performance and cognitive impairment in a longitudinal sample of older adults with T1D. METHODS: We analyzed data collected as part of the Wireless Innovation for Seniors with Diabetes Mellitus (WISDM) Study, in which 22 endocrinology practices participated. Randomized participants with T1D ≥60 years of age who completed at least one cognitive assessment were included in this study (n = 203). Cognitive impairment was classified using published recommendations. RESULTS: Older age, male sex, non-private health insurance, worse daily functioning, diagnosis of neuropathy, and longer duration of diabetes were associated with worse cognitive performance, but not cognitive impairment. 49 % and 39 % of the sample met criteria for cognitive impairment at baseline and 52 weeks respectively. Of the participants that had data at both time points, 10 % were normal at baseline and impaired at 52 weeks and 22 % of participants (44 % of those classified with cognitive impairment at baseline) reverted to normal over 52 weeks. CONCLUSION: This study indicated that several demographic and clinical characteristics are associated with worse cognitive performance in older adults with T1D, but there were no associations between these characteristics and cognitive impairment defined by NIH Toolbox cognitive impairment criteria. Caution is warranted when assessing cognition in older adults with T1D, as a large percentage of those identified as having cognitive impairment at baseline reverted to normal after 52 weeks. There is need for future studies on the interrelationship of cognition and aging to better understand the effects of T1D on cognitive health, to improve clinical monitoring and help mitigate the risk of dementia in this population.

Rest-Activity Rhythm Fragmentation and Weaker Circadian Strength Are Associated With Cognitive Impairment in Survivors of Acute Respiratory Failure.

Background: Survivors of acute respiratory failure (ARF) experience long-term cognitive impairment and circadian rhythm disturbance after hospital discharge. Although prior studies in aging and neurodegenerative diseases indicate actigraphy-estimated rest-activity circadian rhythm disturbances are risk factors for cognitive impairment, it is unclear if this applies to ARF survivors. This study explored the relationships of actigraphy-estimated rest-activity circadian rhythms with cognitive functioning in ARF survivors at 3 months after discharge. Methods: 13 ARF survivors (mean age 51 years and 69% males) completed actigraphy and sleep diaries for 9 days, followed by at-home neuropsychological assessment. Principal component factor analysis created global cognition and circadian rhythm variables, and these first components were used to examine the global relationships between circadian rhythm and cognitive measure scores. Results: Global circadian function was associated with global cognition function in ARF survivors (r = .70, p = .024) after adjusting for age, education, and premorbid cognition. Also, greater fragmented rest-activity circadian rhythm (estimated by intradaily variability, r = .85, p = .002), and weaker circadian strength (estimated by amplitude, r = .66, p = .039; relative strength, r = .70, p = .024; 24-h lag serial autocorrelation, r = .67, p = .035), were associated with global cognition and individual cognitive tests. Conclusions: These results suggest circadian rhythm disturbance is associated with poorer global cognition in ARF survivors. Future prospective research with larger samples is needed to confirm these results and increase understanding of the relationship between disrupted circadian rhythms and cognitive impairment among ARF survivors.

Utility of the NIH Toolbox Cognition Battery in middle to older aged adults with longstanding type 1 diabetes: The DCCT/EDIC study.

Objective: Adults with type 1 diabetes (T1D) face an increased risk for cognitive decline and dementia. Diabetes-related and vascular risk factors have been linked to cognitive decline using detailed neuropsychological testing; however, it is unclear if cognitive screening batteries can detect cognitive changes associated with aging in T1D. Method: 1,049 participants with T1D (median age 59 years; range 43-74) from the Diabetes Control and Complications Trial (DCCT), and the follow-up Epidemiology of Diabetes Interventions and Complications (EDIC) study, completed the NIH Toolbox Cognition Battery (NIHTB-C) and Montreal Cognitive Assessment (MoCA). Neuropsychological assessments, depression, glycated hemoglobin levels (HbA1c), severe hypoglycemia, T1D complications, and vascular risk factors were assessed repeatedly over 32 years to determine associations with current NIHTB-C performance. Available cognitive data was clinically adjudicated to determine cognitive impairment status. Results: NIHTB-C scores had moderate associations (r = 0.36-0.53) with concurrently administered neuropsychological tests. In multivariate models, prior severe hypoglycemic episodes, depression symptoms, nephropathy, lower BMI, and higher HbA1c and LDL cholesterol were associated with poorer NIHTB-C Fluid Cognition Composite scores. The NIHTB-C adequately detected adjudicated cognitive impairment (Area Under the Curve = 0.86; optimal cut score ≤90). The MoCA performed similarly (Area Under the Curve = 0.83; optimal cut score ≤25). Conclusions: The NIHTB-C is sensitive to the cognitive effects of diabetes-related and vascular risk factors, correlated with neuropsychological testing, and accurately detects adjudicated cognitive impairment. These data support its use as a screening test in middle to older aged adults with T1D to determine if referral for detailed neuropsychological assessment is needed.

Glycemic Variability and Fluctuations in Cognitive Status in Adults With Type 1 Diabetes (GluCog): Observational Study Using Ecological Momentary Assessment of Cognition.

BACKGROUND: Individuals with type 1 diabetes represent a population with important vulnerabilities to dynamic physiological, behavioral, and psychological interactions, as well as cognitive processes. Ecological momentary assessment (EMA), a methodological approach used to study intraindividual variation over time, has only recently been used to deliver cognitive assessments in daily life, and many methodological questions remain. The Glycemic Variability and Fluctuations in Cognitive Status in Adults with Type 1 Diabetes (GluCog) study uses EMA to deliver cognitive and self-report measures while simultaneously collecting passive interstitial glucose in adults with type 1 diabetes. OBJECTIVE: We aimed to report the results of an EMA optimization pilot and how these data were used to refine the study design of the GluCog study. An optimization pilot was designed to determine whether low-frequency EMA (3 EMAs per day) over more days or high-frequency EMA (6 EMAs per day) for fewer days would result in a better EMA completion rate and capture more hypoglycemia episodes. The secondary aim was to reduce the number of cognitive EMA tasks from 6 to 3. METHODS: Baseline cognitive tasks and psychological questionnaires were completed by all the participants (N=20), followed by EMA delivery of brief cognitive and self-report measures for 15 days while wearing a blinded continuous glucose monitor. These data were coded for the presence of hypoglycemia (<70 mg/dL) within 60 minutes of each EMA. The participants were randomized into group A (n=10 for group A and B; starting with 3 EMAs per day for 10 days and then switching to 6 EMAs per day for an additional 5 days) or group B (N=10; starting with 6 EMAs per day for 5 days and then switching to 3 EMAs per day for an additional 10 days). RESULTS: A paired samples 2-tailed t test found no significant difference in the completion rate between the 2 schedules (t17=1.16; P=.26; Cohen dz=0.27), with both schedules producing >80% EMA completion. However, more hypoglycemia episodes were captured during the schedule with the 3 EMAs per day than during the schedule with 6 EMAs per day. CONCLUSIONS: The results from this EMA optimization pilot guided key design decisions regarding the EMA frequency and study duration for the main GluCog study. The present report responds to the urgent need for systematic and detailed information on EMA study designs, particularly those using cognitive assessments coupled with physiological measures. Given the complexity of EMA studies, choosing the right instruments and assessment schedules is an important aspect of study design and subsequent data interpretation.

Memory-Aware Active Learning in Mobile Sensing Systems.

We propose a novel active learning framework for activity recognition using wearable sensors. Our work is unique in that it takes limitations of the oracle into account when selecting sensor data for annotation by the oracle. Our approach is inspired by human-beings' limited capacity to respond to prompts on their mobile device. This capacity constraint is manifested not only in the number of queries that a person can respond to in a given time-frame but also in the time lag between the query issuance and the oracle response. We introduce the notion of mindful active learning and propose a computational framework, called EMMA, to maximize the active learning performance taking informativeness of sensor data, query budget, and human memory into account. We formulate this optimization problem, propose an approach to model memory retention, discuss the complexity of the problem, and propose a greedy heuristic to solve the optimization problem. Additionally, we design an approach to perform mindful active learning in batch where multiple sensor observations are selected simultaneously for querying the oracle. We demonstrate the effectiveness of our approach using three publicly available activity datasets and by simulating oracles with various memory strengths. We show that the activity recognition accuracy ranges from 21% to 97% depending on memory strength, query budget, and difficulty of the machine learning task. Our results also indicate that EMMA achieves an accuracy level that is, on average, 13.5% higher than the case when only informativeness of the sensor data is considered for active learning. Moreover, we show that the performance of our approach is at most 20% less than the experimental upper-bound and up to 80% higher than the experimental lower-bound. To evaluate the performance of EMMA for batch active learning, we design two instantiations of EMMA to perform active learning in batch mode. We show that these algorithms improve the algorithm training time at the cost of a reduced accuracy in performance. Another finding in our work is that integrating clustering into the process of selecting sensor observations for batch active learning improves the activity learning performance by 11.1% on average, mainly due to reducing the redundancy among the selected sensor observations. We observe that mindful active learning is most beneficial when the query budget is small and/or the oracle's memory is weak. This observation emphasizes advantages of utilizing mindful active learning strategies in mobile health settings that involve interaction with older adults and other populations with cognitive impairments.

Associations between Intra-Individual Neurocognitive Variability and Prospective Memory in Veterans with Mild Traumatic Brain Injury History and Posttraumatic Stress Disorder.

OBJECTIVE: Mild traumatic brain injury (mTBI) and posttraumatic stress disorder (PTSD) frequently co-occur and are associated with neurocognitive intra-individual variability (IIV) and difficulty with prospective memory (PM). The current study aimed to examine associations between IIV and PM in this comorbid group. METHOD: Fifty veterans with a history of blast mTBI and current comorbid PTSD completed a standardized neurocognitive battery to measure IIV, and the Memory for Intentions Screening Test measuring PM. RESULTS: Adjusting for age, education, and race, higher IIV was associated with poorer time-based PM (p < .001, f2 = .34), but not event-based PM. In a subset of the sample with self-report data, higher IIV was associated with poorer self-reported retrospective memory, but not PM. CONCLUSIONS: Cognitive variability on a standardized neuropsychological battery was associated with strategically demanding PM, which is an ecologically relevant ability and highlights the possible connection between subtle cognitive difficulties in-clinic and those experienced in daily life.

Benefit of Continuous Glucose Monitoring in Reducing Hypoglycemia Is Sustained Through 12 Months of Use Among Older Adults with Type 1 Diabetes.

Objective: To evaluate glycemic outcomes in the Wireless Innovation for Seniors with Diabetes Mellitus (WISDM) randomized clinical trial (RCT) participants during an observational extension phase. Research Design and Methods: WISDM RCT was a 26-week RCT comparing continuous glucose monitoring (CGM) with blood glucose monitoring (BGM) in 203 adults aged ≥60 years with type 1 diabetes. Of the 198 participants who completed the RCT, 100 (98%) CGM group participants continued CGM (CGM-CGM cohort) and 94 (98%) BGM group participants initiated CGM (BGM-CGM cohort) for an additional 26 weeks. Results: CGM was used a median of >90% of the time at 52 weeks in both cohorts. In the CGM-CGM cohort, median time <70 mg/dL decreased from 5.0% at baseline to 2.6% at 26 weeks and remained stable with a median of 2.8% at 52 weeks (P < 0.001 baseline to 52 weeks). Participants spent more time in range 70-180 mg/dL (TIR) (mean 56% vs. 64%; P < 0.001) and had lower hemoglobin A1c (HbA1c) (mean 7.6% [59 mmol/mol] vs. 7.4% [57 mmol/mol]; P = 0.01) from baseline to 52 weeks. In BGM-CGM, from 26 to 52 weeks median time <70 mg/dL decreased from 3.9% to 1.9% (P < 0.001), TIR increased from 56% to 60% (P = 0.006) and HbA1c decreased from 7.5% (58 mmol/mol) to 7.3% (57 mmol/mol) (P = 0.025). In BGM-CGM, a severe hypoglycemic event was reported for nine participants while using BGM during the RCT and for two participants during the extension phase with CGM (P = 0.02). Conclusions: CGM use reduced hypoglycemia without increasing hyperglycemia in older adults with type 1 diabetes. These data provide further evidence for fully integrating CGM into clinical practice. Clinicaltrials.gov (NCT03240432).

Construct validity, ecological validity and acceptance of self-administered online neuropsychological assessment in adults.

Objective: The goal of this project was to explore the initial psychometric properties (construct and ecological validity) of self-administered online (SAO) neuropsychological assessment (using the www.testmybrain.org platform), compared to traditional testing, in a clinical sample, as well as to evaluate participant acceptance. SAO assessment has the potential to expand the reach of in-person neuropsychological assessment approaches.Method: Counterbalanced, within-subjects design comparing SAO performance to in-person performance in adults with diabetes with and without Chronic Kidney Disease (CKD). Forty-nine participants completed both assessment modalities (type 1 diabetes N = 14, type 2 diabetes N = 35; CKD N = 18).Results: Associations between SAO and analogous in-person tests were adequate to good (r = 0.49-0.66). Association strength between divergent cognitive tests did not differ between SAO versus in-person tests. SAO testing was more strongly associated with age than in-person testing (age R2=0.54 versus 0.23), while prediction of education, HbA1c, and estimated glomerular filtration rate (eGFR) did not differ significantly between test modalities (education R2=0.37 versus 0.30; HbA1c R2=0.20 versus 0.12; eGFR R2 = 0.41 versus 0.33). Associations with measures of everyday functioning were also similar (Functional Activities Questionnaire R2=0.08 versus 0.07; Neuro-QoL R2=0.14 versus 0.16; Diabetes Self-Management Questionnaire R2=0.19 versus 0.19).Conclusions: The selected SAO neuropsychological tests had acceptable construct validity (including divergent, convergent, and criterion-related validity), and similar ecological validity to that of traditional testing. These SAO assessments were acceptable to participants and appear appropriate for use in research applications, although further research is needed to better understand the strengths and weaknesses in other clinical populations.

Hypoglycemia and Glycemic Control in Older Adults With Type 1 Diabetes: Baseline Results From the WISDM Study.

BACKGROUND: Knowledge regarding the burden and predictors of hypoglycemia among older adults with type 1 diabetes (T1D) is limited. METHODS: We analyzed baseline data from the Wireless Innovations for Seniors with Diabetes Mellitus (WISDM) study, which enrolled participants at 22 sites in the United States. Eligibility included clinical diagnosis of T1D, age ≥60 years, no real-time continuous glucose monitoring (CGM) use in prior three months, and HbA1c <10.0%. Blinded CGM data from 203 participants with at least 240 hours were included in the analyses. RESULTS: Median age of the cohort was 68 years (52% female, 93% non-Hispanic white, and 53% used insulin pumps). Mean HbA1c was 7.5%. Median time spent in the glucose range <70 mg/dL was 5.0% (72 min/day) and <54 mg/dL was 1.6% (24 min/day). Among all factors analyzed, only reduced hypoglycemia awareness was associated with greater time spent <54 mg/dL (median time of 2.7% vs 1.3% [39 vs 19 minutes per day] for reduced awareness vs aware/uncertain, respectively, P = .03). Participants spent a mean 56% of total time in target glucose range of 70-180 mg/dL and 37% of time above 180 mg/dL. CONCLUSIONS: Over half of older T1D participants spent at least an hour a day with glucose levels <70 mg/dL. Those with reduced hypoglycemia awareness spent over twice as much time than those without in a serious hypoglycemia range (glucose levels <54 mg/dL). Interventions to reduce exposure to clinically significant hypoglycemia and increase time in range are urgently needed in this age group.

Digital neuropsychology: Challenges and opportunities at the intersection of science and software.

OBJECTIVE: Digital devices are now broadly accessible and have the capacity to measure aspects of human behavior with high precision and accuracy, in a standardized manner. The purpose of this article is to characterize opportunities and barriers for modern digital neuropsychology, particularly those that are unique to digital assessment. METHODS: We provide a critical overview of the state-of-the-art in digital neuropsychology, focusing on personal digital devices. RESULTS: We identify three major barriers associated with digital neuropsychology, which affect both the interpretation of test scores and test norms: (1) variability in the perceptual, motor and cognitive demands of the same test across digital device classes (e.g. personal computer, tablet and smartphone); (2) hardware and software variability between devices within the same class that affect stimulus presentation and measurement and (3) rapid changes over time in hardware, software and device ownership, which can lead to rapid obsolescence of particular tests and test norms. We offer specific recommendations to address these barriers and outline new opportunities to understand and measure neuropsychological functioning over time and in everyday environments. CONCLUSIONS: Digital neuropsychology provides new approaches for measuring and monitoring neuropsychological functioning, informed by an understanding of the limitations and potential of digital technology.

Clinically significant cognitive impairment in older adults with type 1 diabetes.

AIMS: Little is known about cognition in older adults with type 1 diabetes. The aim of this study was to identify correlates of clinically significant cognitive impairment. METHODS: Neuropsychological, diabetes-related and glycemic (HbA1c, Continuous Glucose Monitoring; CGM) data were collected from 201 older adults (≥60 years) with longstanding type 1 diabetes. RESULTS: Clinically significant cognitive impairment (≥2 cognitive tests ≥1.5 SD below normative data) occurred in 48% of the sample. After controlling for age, gender, education and diabetes duration, we found that hypoglycemia unawareness, recent severe hypoglycemic events, any microvascular complication, higher HbA1c and CGM average nocturnal glucose were all associated with increased odds of clinically significant cognitive impairment (ORs = 1.01-2.61), while CGM nocturnal % time below 60 mg/dL was associated with a decreased odds of cognitive impairment (OR = 0.94). Diabetes duration, diagnosis age, daytime CGM, and lifetime severe hypoglycemic events were not related to cognitive impairment status. CONCLUSIONS: Clinically significant cognitive impairment was common in older adults with type 1 diabetes. Diabetes-related correlates of cognitive impairment were identified, including hypoglycemia unawareness, recent severe hypoglycemic events, and CGM variables. Longitudinal research is needed to determine if these variables predict cognitive decline and if their modification alters outcomes.

Depressive Symptoms in Older versus Younger People with Epilepsy: Findings from an Integrated Epilepsy Self-Management Clinical Research Dataset.

AIM: There are limited data on psychological outcomes in older people with epilepsy (PWE). This analysis, from a large pooled dataset of clinical studies from the Managing Epilepsy Well (MEW) Network, examined clinical variables including depressive symptom severity, quality of life and epilepsy self-management competency among older (age 55+) vs younger (