Caregiving in Older Adults; Experiences and Attitudes toward Smart Technologies.

(1) Background: The development of assistive technologies has become a key solution to reduce caregiver burden. The objective of this study was to survey caregivers on perceptions and beliefs about the future of modern technology in caregiving. (2) Methods: Demographics and clinical caregiver characteristics were collected via an online survey along with the perceptions and willingness to adopt technologies to support caregiving. Comparisons were made between those who considered themselves caregivers and those who never did. (3) Results: 398 responses (mean age 65) were analyzed. Health and caregiving status of the respondents (e.g., schedule of care) and of the care recipient were described. The perceptions and willingness to use technologies were generally positive without significant differences between those who ever considered themselves as caregivers and those who never did. The most valued features were the monitoring of falls (81%), medication use (78%), and changes in physical functioning (73%). For caregiving support, the greatest endorsements were reported for one-on-one options with similar scores for both online and in-person alternatives. Important concerns were expressed about privacy, obtrusiveness, and technological maturity. (4) Conclusions: Online surveys as a source of health information on caregiving may be an effective guide in developing care-assisting technologies receiving end users' feedback. Caregiver experience, whether positive or negative, was correlated to health habits such as alcohol use or sleep. This study provides insight on caregivers' needs and perceptions regarding caregiving according to their socio-demographic and health status.

Hospital-level variation in genetic testing in children's hospitals' neonatal intensive care units from 2016 to 2021.

PURPOSE: This study aimed to examine variation in genetic testing between neonatal intensive care units (NICUs) across hospitals over time. METHODS: We performed a multicenter large-scale retrospective cohort study using NICU discharge data from the Pediatric Hospital Information System database between 2016 and 2021. We analyzed the variation in the percentage of NICU patients who had any genetic testing across hospitals and over time. We used a multivariable multilevel logistic regression model to investigate the potential association between patient characteristics and genetic testing. RESULTS: The final analysis included 207,228 neonates from 38 hospitals. Overall, 13% of patients had at least 1 genetic test sent, although this varied from 4% to 50% across hospitals. Over the study period, the proportion of patients tested increased, with the increase disproportionately borne by hospitals already testing high proportions of patients. On average, patients who received genetic testing had higher illness severity. Controlling for severity, however, only minimally reduced the degree of hospital-level variation in genetic testing. CONCLUSION: The percentage of NICU patients who undergo genetic testing varies among hospitals and increasingly so over time. Variation is largely unexplained by differences in severity between hospitals. The degree of variation suggests that clearer guidelines for NICU genetic testing are warranted.

Emotional characteristics of socially isolated older adults with MCI using tablet administered NIH toolbox: I-CONECT study.

Introduction: Examining the emotional functioning of individuals with mild cognitive impairment (MCI) could help describe their cognitive status and inform the development of interventions. This study compared the emotional characteristics of socially isolated older adults with and without MCI. Methods: We used baseline data from the Internet-based Conversational Engagement Clinical Trial. Emotional characteristics were assessed with the National Institutes of Health Toolbox Emotion Battery (NIHTB-EB). MCI status was determined with a consensus clinical diagnosis. Results: This study included 163 participants (mean age = 81.2 years, non-Hispanic Black = 20.7%, MCI = 52.8%). MCI was associated with higher negative affect and lower psychological well-being. Non-Hispanic Black participants scored lower in sadness, higher in positive affect, and higher in meaning and purpose than non-Hispanic White participants. Conclusion: Older adults with MCI experience more negative emotions and worse psychological well-being than those with normal cognition. The NIHTB-EB appears to be a sensitive tool to detect emotional characteristics associated with cognitive decline.

Online monitoring of financial capacity in older adults: Feasibility and initial findings.

Introduction: Impairment in financial capacity places older adults at risk of fraud or abuse and can be a harbinger of loss of independence. Online automated monitoring of financial transactions offers an objective, unobtrusive, and continuous data collection strategy to minimize risk and to detect early changes in an important complex activity of daily living. Methods: Ninety-three participants used an online financial activity monitoring platform that extracted metrics related to use and potential departures from established patterns of financial behavior. Standard neuropsychological assessments and a performance-based measure of financial capacity at baseline were compared using continuous monitoring metrics. Results: Participants demonstrated a willingness to engage with an online financial activity monitoring system. Online metrics were not associated with performance in specific cognitive domains. Performance on an established test of financial capacity was negatively correlated with a ratio of alerts to transactions, that is, a higher likelihood of errors or deviations from previous activity. Discussion: To our knowledge, this is the first reported study using secure online technology to link ongoing unobtrusively collected financial activity monitoring data with other objective measures of function and cognition in a cohort of independent living older adults.

Influence of Genetic Information on Neonatologists' Decisions: A Psychological Experiment.

BACKGROUND AND OBJECTIVES: Genetic testing is expanding among ill neonates, yet the influence of genetic results on medical decision-making is not clear. With this study, we sought to determine how different types of genetic information with uncertain implications for prognosis influence clinicians' decisions to recommend intensive versus palliative care. METHODS: We conducted a national study of neonatologists using a split sample experimental design. The questionnaire contained 4 clinical vignettes. Participants were randomly assigned to see one of 2 versions that varied only regarding whether they included the following genetic findings: (1) a variant of uncertain significance; (2) a genetic diagnosis that affects neurodevelopment but not acute survival; (3) a genetic versus nongenetic etiology of equally severe pathology; (4) a pending genetic testing result. Physicians answered questions about recommendations they would make for the patient described in each vignette. RESULTS: Vignette versions that included a variant of uncertain significance, a diagnosis foreshadowing neurodevelopmental impairment, or a genetic etiology of disease were all associated with an increased likelihood of recommending palliative rather than intensive care. A pending genetic test result did not have a significant effect on care recommendations. CONCLUSIONS: Findings from this study of hypothetical cases suggest neonatologists apply uncertain genetic findings or those that herald neurodevelopmental disability in problematic ways. As genetic testing expands, understanding how it is used in decision-making and educating clinicians regarding appropriate use are paramount.

Dementia 360 ECHO: Using technology to facilitate diagnosis and treatment.

Dementia affects one in ten adults over age 65. Paradoxically, dementia (e.g., Alzheimer's disease and related dementias) is underdiagnosed, with approximately 50% of those with dementia lacking a formal diagnosis. This limits options for care, support and research engagement. To address this gap, we developed and implemented a telehealth-based ECHO (Extension for Community Healthcare Outcomes) program, "Dementia 360," to provide education and support for clinicians and allied team members. We assessed the feasibility and acceptability of this telementoring educational offering and the effect it had on clinician confidence in diagnosing and treating dementia. Clinicians from across Oregon (n = 67) attended learning sessions via videoconferencing technology. The sessions, which focused on dementia diagnosis and treatment, included didactic information provided by experts, followed by case discussions. We assessed clinician acceptability using surveys, and confidence in identifying and treating those with dementia prior to and after Dementia 360 using paired t tests. Dementia 360 was acceptable to clinicians and significantly increased their comfort levels in identifying and treating those with dementia. The technology-based program provided support and instruction that was acceptable by clinicians, even those in frontier areas of the state.

DCE-MRI of Brain Fluid Barriers: In Vivo Water Cycling at the Human Choroid Plexus.

Metabolic deficits at brain-fluid barriers are an increasingly recognized feature of cognitive decline in older adults. At the blood-cerebrospinal fluid barrier, water is transported across the choroid plexus (CP) epithelium against large osmotic gradients via processes tightly coupled to activity of the sodium/potassium pump. Here, we quantify CP homeostatic water exchange using dynamic contrast-enhanced MRI and investigate the association of the water efflux rate constant (kco) with cognitive dysfunction in older individuals. Temporal changes in the longitudinal relaxation rate constant (R1) after contrast agent bolus injection were measured in a CP region of interest in 11 participants with mild cognitive dysfunction [CI; 73 ± 6 years] and 28 healthy controls [CN; 72 ± 7 years]. kco was determined from a modified two-site pharmacokinetic exchange analysis of the R1 time-course. Ktrans, a measure of contrast agent extravasation to the interstitial space was also determined. Cognitive function was assessed by neuropsychological test performance. kco averages 5.8 ± 2.7 s-1 in CN individuals and is reduced by 2.4 s-1 [ca. 40%] in CI subjects. Significant associations of kco with global cognition and multiple cognitive domains are observed. Ktrans averages 0.13 ± 0.07 min-1 and declines with age [-0.006 ± 0.002 min-1 yr-1], but shows no difference between CI and CN individuals or association with cognitive performance. Our findings suggest that the CP water efflux rate constant is associated with cognitive dysfunction and shows an age-related decline in later life, consistent with the metabolic disturbances that characterize brain aging.

Can changes in social contact (frequency and mode) mitigate low mood before and during the COVID-19 pandemic? The I-CONECT project.

BACKGROUND/OBJECTIVES: The coronavirus disease 2019 (COVID-19) global outbreak allowed a natural experiment to observe how older adults changed social patterns and how it affected their emotional well-being. We studied the frequency and modes of social contact and their effects on older adults' mood before and during the COVID-19 pandemic. DESIGN: Phone-based surveys were administered weekly before and during the COVID-19 pandemic. SETTING: Participants were recruited from Portland, Oregon, and Detroit, Michigan. PARTICIPANTS: Older adults ≥75 years old (n = 155, age = 81.0 ± 4.5, 72.3% women) were included in a randomized controlled trial, the Internet-Based Conversational Engagement Clinical Trial (I-CONECT). MEASUREMENTS: Low mood was self-reported as feeling downhearted or blue for three or more days in the past week. Social contact was self-reported by the amount of time spent in interactions, with whom (family, friends, others), and via which modes (in-person, phone/video call, text/email/letter). RESULTS: A total of 5525 weeks of data were derived from 155 participants. Before the COVID-19 pandemic, average social interaction time spent in-person, on phone/video call, and via text/email/letter was 406, 141, and 68 min/week, respectively. During the COVID-19 pandemic, time spent in-person was reduced by 135 min/week, while time spent via phone/video call and writing increased by 33 and 26 mins/week, respectively. In-person family contact was associated with less low mood regardless of the pandemic (odds ratio = 0.92, p < 0.05). There was a COVID-19 × text/email/letter with friends interaction (odds ratio = 0.77, p = 0.03), suggesting that during the COVID-19 pandemic, an increase of 1 h of writing with friends per week was associated with a 23% decrease in the likelihood of experiencing low mood. CONCLUSION: The lost in-person time relating to COVID-19 restrictions tended to be partially compensated for with increased calls and writing time, although overall social interaction time decreased. During the COVID-19 pandemic, at least two types of social interactions (writing to friends and in-person family time) showed promise for mitigating low mood for older adults with limited social resources.

Type and frequency of social contacts associated with low mood before and during the COVID-19 pandemic in older adults: I-CONECT project.

BACKGROUND: Social isolation is a risk factor for dementia, but the underlying mechanism is not well understood. It is possible that lack of social contacts negatively affects emotional well-being, which leads to cognitive decline. To shed light on this potential mediation mechanism, we examined changes in type and frequency of social contacts and their effects on mood using data collected before and during the COVID-19 pandemic among socially isolated older adults aged 75 and older. METHOD: The data come from an ongoing randomized controlled trial, the Internet-Based Conversational Engagement Clinical Trial (I-CONECT, ClinicalTirals.gov: NCT02871921). One hundred forty-six participants (age=81.0±4.5, 71.9% women) who were in the trial both before and during the pandemic and whose data were available as of November of 2020 were included in the current analysis. Weekly health questionnaires administered on all participants regardless of treatment assignments were collected before and during the COVID-19 pandemic. Low mood ("Blueness") was self-reported as feeling downhearted or blue for three or more days in the past week (YES/NO). Social contacts were self-reported by amount of time they had interacted, with whom (family; friends; others), and via which modalities (in-person; phone/video call; text/email). RESULT: A total of 4,774 weeks of survey data were analyzed (3,047 before COVID 19). The weekly average time spent in-person, on phone/video call, and via text/email were 282, 113, and 44 minutes, respectively. During the COVID-19 pandemic, participants on average spent 82 minutes less in total social contact per week (in-person: reduced 123 minutes, video/call: increased 28 minutes, text/email: increased 13 minutes per week). Generalized estimating equation model revealed that in-person family contact was associated with less blueness regardless of the pandemic (OR=0.91, p=0.04). There was a COVID*text/email time with friends interaction (OR=0.68, p=0.03), suggesting that during the COVID-19 pandemic, an increase of 1 hour of texting/emailing with friends per week was associated with 32% decrease in experiencing blueness three or more days per week. CONCLUSION: In-person family time is beneficial for mental health. While in-person contacts become less frequent during the COVID-19 pandemic, increased text/email time with friends becomes an alternative to maintain mental health for socially isolated older adults.

The Internet-Based Conversational Engagement Clinical Trial (I-CONECT) in Socially Isolated Adults 75+ Years Old: Randomized Controlled Trial Protocol and COVID-19 Related Study Modifications.

Background: Increasing social interactions through communication technologies could offer a cost-effective prevention approach that slows cognitive decline and delays the onset of Alzheimer's disease. This paper describes the protocol of an active project named "Internet-based conversational engagement clinical trial (I-CONECT)" (ClinicalTrials.gov: NCT02871921). The COVID-19 pandemic related protocol modifications are also addressed in the current paper. Methods: I-CONECT is a multi-site, assessor-blind, randomized controlled behavioral intervention trial (RCT). We aim to randomize 320 socially isolated adults 75+ years old [160 Caucasian and 160 African American participants, 50:50 split between those with normal cognition and mild cognitive impairment (MCI)] recruited from the community to either the video chat intervention group or the control group (1:1 allocation). Those in the video chat group receive a computer and Internet service for the duration of the study, which they use to video chat with study staff for 30 min/day 4×/week for 6 months (high dose), and then 2×/week for an additional 6 months (maintenance dose). Both video chat and control groups have a brief (about 10 min) telephone check-in with study staff once per week. The primary outcome is the change in global cognitive function measured by Montreal Cognitive Assessment (MoCA) from baseline to 6 months. Secondary outcomes include changes in cognition in memory and executive function domains, emotional well-being measured by NIH Toolbox emotional battery, and daily functional abilities assessed with the Revised Observed Tasks of Daily Living (OTDL-R). Eligible participants have MRIs at baseline and 6 months. Participants contribute saliva for genetic testing (optional consent), and all video chats, weekly check-in calls and neuropsychological assessment sessions are recorded for speech and language analysis. The pandemic halted research activities and resulted in protocol modifications, including replacing in-person assessment with remote assessment, remote deployment of study equipment, and revised targeted sample size. Discussion: This trial provides user-friendly hardware for the conversational-based intervention that can be easily provided at participants' homes. The trial aspires to use age and culture-specific conversational materials and a related platform developed in this trial for enhancing cognitive reserve and improving cognitive function.

Application of In-Home Monitoring Data to Transition Decisions in Continuing Care Retirement Communities: Usability Study.

BACKGROUND: Continuous in-home monitoring of older adults can provide rich and sensitive data capturing subtle behavioral and cognitive changes. Our previous work has identified multiple metrics that describe meaningful trends in daily activities over time. The continuous, multidomain nature of this technology may also serve to inform caregivers of the need for higher levels of care to maintain the health and safety of at-risk older adults. Accordingly, care decisions can be based on objective, systematically assessed real-time data. OBJECTIVE: This study deployed a suite of in-home monitoring technologies to detect changing levels of care needs in residents of independent living units in 7 retirement communities and to assess the efficacy of computer-based tools in informing decisions regarding care transitions. METHODS: Continuous activity data were presented via an interactive, web-based tool to the staff identified in each facility who were involved in decisions regarding transitions in care among residents. Comparisons were planned between outcomes for residents whose data were shared and those whose data were not made available to the staff. Staff use of the data dashboard was monitored throughout the study, and exit interviews with the staff were conducted to explicate staff interaction with the data platform. Residents were sent weekly self-report questionnaires to document any health- or care-related changes. RESULTS: During the study period, 30 of the 95 residents (32%) reported at least one incidence of new or increased provision of care; 6 residents made a permanent move to a higher level of care within their communities. Despite initial enthusiasm and an iterative process of refinement of measures and modes of data presentation based on staff input, actual inspection and therefore the use of resident data were well below expectation. In total, 11 of the 25 staff participants (44%) logged in to the activity dashboard throughout the study. Survey data and in-depth interviews provided insight into the mismatch between intended and actual use. CONCLUSIONS: Most continuous in-home monitoring technology acceptance models focus on perceived usefulness and ease of use and equate the intent to use technology with actual use. Our experience suggests otherwise. We found that multiple intervening variables exist between perceived usefulness, intent to use, and actual use. Ethical, institutional, and social factors are considered in their roles as determinants of use.

Differentiating among stages of cognitive impairment in aging: Version 3 of the Uniform Data Set (UDS) neuropsychological test battery and MoCA index scores.

INTRODUCTION: Federally funded Alzheimer's Disease Centers in the United States have been using a standardized neuropsychological test battery as part of the National Alzheimer's Coordinating Center Uniform Data Set (UDS) since 2005. Version 3 (V3) of the UDS replaced the previous version (V2) in 2015. We compared V2 and V3 neuropsychological tests with respect to their ability to distinguish among the Clinical Dementia Rating (CDR) global scores of 0, 0.5, and 1. METHODS: First, we matched participants receiving V2 tests (V2 cohort) and V3 tests (V3 cohort) in their cognitive functions using tests common to both versions. Then, we compared receiver-operating characteristic (ROC) area under the curve in differentiating CDRs for the remaining tests. RESULTS: Some V3 tests performed better than V2 tests in differentiating between CDR 0.5 and 0, but the improvement was limited to Caucasian participants. DISCUSSION: Further efforts to improve the ability for early identification of cognitive decline among diverse racial groups are required.

Automatic Assessment of Cognitive Tests for Differentiating Mild Cognitive Impairment: A Proof of Concept Study of the Digit Span Task.

BACKGROUND: Current conventional cognitive assessments are limited in their efficiency and sensitivity, often relying on a single score such as the total correct items. Typically, multiple features of response go uncaptured. OBJECTIVES: We aim to explore a new set of automatically derived features from the Digit Span (DS) task that address some of the drawbacks in the conventional scoring and are also useful for distinguishing subjects with Mild Cognitive Impairment (MCI) from those with intact cognition. METHODS: Audio-recordings of the DS tests administered to 85 subjects (22 MCI and 63 healthy controls, mean age 90.2 years) were transcribed using an Automatic Speech Recognition (ASR) system. Next, five correctness measures were generated from Levenshtein distance analysis of responses: number correct, incorrect, deleted, inserted, and substituted words compared to the test item. These per-item features were aggregated across all test items for both Forward Digit Span (FDS) and Backward Digit Span (BDS) tasks using summary statistical functions, constructing a global feature vector representing the detailed assessment of each subject's response. A support vector machine classifier distinguished MCI from cognitively intact participants. RESULTS: Conventional DS scores did not differentiate MCI participants from controls. The automated multi-feature DS-derived metric achieved 73% on AUC-ROC of the SVM classifier, independent of additional clinical features (77% when combined with demographic features of subjects); well above chance, 50%. CONCLUSION: Our analysis verifies the effectiveness of introduced measures, solely derived from the DS task, in the context of differentiating subjects with MCI from those with intact cognition.

An Ecologically Valid, Longitudinal, and Unbiased Assessment of Treatment Efficacy in Alzheimer Disease (the EVALUATE-AD Trial): Proof-of-Concept Study.

BACKGROUND: The current clinical trial assessment methodology relies on a combination of self-report measures, cognitive and physical function tests, and biomarkers. This methodology is limited by recall bias and recency effects in self-reporting and by assessments that are brief, episodic, and clinic based. Continuous monitoring of ecologically valid measures of cognition and daily functioning in the community may provide a more sensitive method to detect subtle, progressive changes in patients with cognitive impairment and dementia. OBJECTIVE: This study aimed to present an alternative trial approach using a home-based sensing and computing system to detect changes related to common treatments employed in Alzheimer disease (AD). This paper introduces an ongoing study that aims to determine the feasibility of capturing sensor-based data at home and to compare the sensor-based outcomes with conventional outcomes. We describe the methodology used in the assessment protocol and present preliminary results of feasibility measures and examples of data related to medication-taking behavior, activity levels, and sleep. METHODS: The EVALUATE-AD (Ecologically Valid, Ambient, Longitudinal and Unbiased Assessment of Treatment Efficacy in Alzheimer's Disease) trial is a longitudinal naturalistic observational cohort study recruiting 30 patients and 30 spouse coresident care partners. Participants are monitored continuously using a home-based sensing and computing system for up to 24 months. Outcome measures of the automated system are compared with conventional clinical outcome measures in AD. Acceptance of the home system and protocol are assessed by rates of dropout and protocol adherence. After completion of the study monitoring period, a composite model using multiple functional outcome measures will be created that represents a behavioral-activity signature of initiating or discontinuing AD-related medications, such as cholinesterase inhibitors, memantine, or antidepressants. RESULTS: The home-based sensing and computing system has been well accepted by individuals with cognitive impairment and their care partners. Participants showed good adherence to the completion of a weekly web-based health survey. Daily activity, medication adherence, and total time in bed could be derived from algorithms using data from the sensing and computing system. The mean monitoring time for current participants was 14.6 months. Medication adherence, as measured with an electronic pillbox, was 77% for participants taking AD-related medications. CONCLUSIONS: Continuous, home-based assessment provides a novel approach to test the impact of new or existing dementia treatments generating objective, clinically meaningful measures related to cognition and everyday functioning. Combining this approach with the current clinical trial methodology may ultimately reduce trial durations, sample size needs, and reliance on a clinic-based assessment. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/17603.

Improving the Assessment of Mild Cognitive Impairment in Advanced Age With a Novel Multi-Feature Automated Speech and Language Analysis of Verbal Fluency.

Introduction: Clinically relevant information can go uncaptured in the conventional scoring of a verbal fluency test. We hypothesize that characterizing the temporal aspects of the response through a set of time related measures will be useful in distinguishing those with MCI from cognitively intact controls. Methods: Audio recordings of an animal fluency test administered to 70 demographically matched older adults (mean age 90.4 years), 28 with mild cognitive impairment (MCI) and 42 cognitively intact (CI) were professionally transcribed and fed into an automatic speech recognition (ASR) system to estimate the start time of each recalled word in the response. Next, we semantically cluster participant generated animal names and through a novel set of time-based measures, we characterize the semantic search strategy of subjects in retrieving words from animal name clusters. This set of time-based features along with standard count-based features (e.g., number of correctly retrieved animal names) were then used in a machine learning algorithm trained for distinguishing those with MCI from CI controls. Results: The combination of both count-based and time-based features, automatically derived from the test response, achieved 77% on AUC-ROC of the support vector machine (SVM) classifier, outperforming the model trained only on the raw test score (AUC, 65%), and well above the chance model (AUC, 50%). Conclusion: This approach supports the value of introducing time-based measures to the assessment of verbal fluency in the context of this generative task differentiating subjects with MCI from those with intact cognition.

The Collaborative Aging Research Using Technology Initiative: An Open, Sharable, Technology-Agnostic Platform for the Research Community.

INTRODUCTION: Future digital health research hinges on methodologies to conduct remote clinical assessments and in-home monitoring. The Collaborative Aging Research Using Technology (CART) initiative was introduced to establish a digital technology research platform that could widely assess activity in the homes of diverse cohorts of older adults and detect meaningful change longitudinally. This paper reports on the built end-to-end design of the CART platform, its functionality, and the resulting research capabilities. METHODS: CART platform development followed a principled design process aiming for scalability, use case flexibility, longevity, and data privacy protection while allowing sharability. The platform, comprising ambient technology, wearables, and other sensors, was deployed in participants' homes to provide continuous, long-term (months to years), and ecologically valid data. Data gathered from CART homes were sent securely to a research server for analysis and future data sharing. RESULTS: The CART system was created, iteratively tested, and deployed to 232 homes representing four diverse cohorts (African American, Latinx, low-income, and predominantly rural-residing veterans) of older adults (n = 301) across the USA. Multiple measurements of wellness such as cognition (e.g., mean daily computer use time = 160-169 min), physical mobility (e.g., mean daily transitions between rooms = 96-155), sleep (e.g., mean nightly sleep duration = 6.3-7.4 h), and level of social engagement (e.g., reports of overnight visitors = 15-45%) were collected across cohorts. CONCLUSION: The CART initiative resulted in a minimally obtrusive digital health-enabled system that met the design principles while allowing for data capture over extended periods and can be widely used by the research community. The ability to monitor and manage health digitally within the homes of older adults is an important alternative to in-person assessments in many research contexts. Further advances will come with wider, shared use of the CART system in additional settings, within different disease contexts, and by diverse research teams.

Current State of Digital Biomarker Technologies for Real-Life, Home-Based Monitoring of Cognitive Function for Mild Cognitive Impairment to Mild Alzheimer Disease and Implications for Clinical Care: Systematic Review.

BACKGROUND: Among areas that have challenged the progress of dementia care has been the assessment of change in symptoms over time. Digital biomarkers are defined as objective, quantifiable, physiological, and behavioral data that are collected and measured by means of digital devices, such as embedded environmental sensors or wearables. Digital biomarkers provide an alternative assessment approach, as they allow objective, ecologically valid, and long-term follow-up with continuous assessment. Despite the promise of a multitude of sensors and devices that can be applied, there are no agreed-upon standards for digital biomarkers, nor are there comprehensive evidence-based results for which digital biomarkers may be demonstrated to be most effective. OBJECTIVE: In this review, we seek to answer the following questions: (1) What is the evidence for real-life, home-based use of technologies for early detection and follow-up of mild cognitive impairment (MCI) or dementia? And (2) What transformation might clinicians expect in their everyday practices? METHODS: A systematic search was conducted in PubMed, Cochrane, and Scopus databases for papers published from inception to July 2018. We searched for studies examining the implementation of digital biomarker technologies for mild cognitive impairment or mild Alzheimer disease follow-up and detection in nonclinic, home-based settings. All studies that included the following were examined: community-dwelling older adults (aged 65 years or older); cognitively healthy participants or those presenting with cognitive decline, from subjective cognitive complaints to early Alzheimer disease; a focus on home-based evaluation for noninterventional follow-up; and remote diagnosis of cognitive deterioration. RESULTS: An initial sample of 4811 English-language papers were retrieved. After screening and review, 26 studies were eligible for inclusion in the review. These studies ranged from 12 to 279 participants and lasted between 3 days to 3.6 years. Most common reasons for exclusion were as follows: inappropriate setting (eg, hospital setting), intervention (eg, drugs and rehabilitation), or population (eg, psychiatry and Parkinson disease). We summarized these studies into four groups, accounting for overlap and based on the proposed technological solutions, to extract relevant data: (1) data from dedicated embedded or passive sensors, (2) data from dedicated wearable sensors, (3) data from dedicated or purposive technological solutions (eg, games or surveys), and (4) data derived from use of nondedicated technological solutions (eg, computer mouse movements). CONCLUSIONS: Few publications dealt with home-based, real-life evaluations. Most technologies were far removed from everyday life experiences and were not mature enough for use under nonoptimal or uncontrolled conditions. Evidence available from embedded passive sensors represents the most relatively mature research area, suggesting that some of these solutions could be proposed to larger populations in the coming decade. The clinical and research communities would benefit from increasing attention to these technologies going forward.

Lactation Experience of Mothers and Feeding Outcomes of Infants with Congenital Diaphragmatic Hernia.

Objective: This study explores the congenital diaphragmatic hernia (CDH) infant-mother dyad with regard to maternal lactation outcomes and infant exposure to a human milk diet. Study Design: This was a retrospective descriptive cohort study conducted at Children's Hospital of Philadelphia. A total of 149 infants born with CDH and admitted to the Newborn/Infant Intensive Care Unit (N/IICU) were included in the study. Results: Of 149 mothers, 141 (95%) initiated pumping for their CDH infants. At discharge from the N/IICU, 79% (n = 118) of infants were being fed human milk. Among those discharged on human milk, 55% (n = 65) were discharged being fed unfortified human milk with 9% (n = 11) being fed unfortified maternal hind milk. Conclusion: This research demonstrates that mothers of CDH infants can effectively establish and maintain a complete milk supply and that the majority of infants with CDH can receive a human milk diet for the entire hospital stay.