Evidence mapPaperPMID 41860332Full record

Observational studyJMIR aging2026

Leveraging Digital Health Technologies to Assess Older Adults' Frailty and Nutritional Status: Two Cross-Sectional Studies.

Nunzio Camerlingo, Madisen Wicker, Dimitrios J Psaltos, Nina Shaafi-Kabiri, Hao Zhang, Andrew Messere, Isabelle Messina, Zachary Hayden, Meredith Kelly, Gauri Kamat and 5 more

2 registry-linked trialsAbstract readObservational Study
In one paragraph

Observational study in JMIR aging, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to 2 registered trials, which are not on this map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

NCT04858932 completednot on this map

Novel Digital Endpoints in Geriatric Anorexia

TypeobservationalSponsorBoston UniversityRan2021 to 2021Enrolled51ConditionsHealthyArmsContinuous Glucose Monitor, Wrist Actigraphy Device, Food Weight Scale, Smart Body Weight Scale
NCT05211973 completednot on this map

Developing Novel Digital Endpoints in Anorexia of Aging in Elderly Populations Residing in Long Term Care (LTC), Nursing Home, or Assisted Living Facilities

TypeobservationalSponsorBoston UniversityRan2022 to 2022Enrolled44ConditionsHealthy, FrailtyArmsWrist Actigraphy Device, Smart Body Weight Scale, Chair Scale, Handheld Body Fat Percentage Device, Bioelectric Impedance Analysis Scale
3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

15 authors.

Nunzio CamerlingoPfizer (United States), Cambridge, MA, United States.ORCID https://orcid.org/0000-0003-3222-2479
Madisen WickerChobanian and Avedisian School of Medicine, Boston University, Boston, MA, United States.ORCID https://orcid.org/0000-0002-6240-0208
Dimitrios J PsaltosPfizer (United States), Cambridge, MA, United States.ORCID https://orcid.org/0000-0002-3347-307X
Nina Shaafi-KabiriChobanian and Avedisian School of Medicine, Boston University, Boston, MA, United States.ORCID https://orcid.org/0000-0001-8951-2237
Hao ZhangPfizer (United States), Cambridge, MA, United States.ORCID https://orcid.org/0000-0003-1833-7069
Andrew MesserePfizer (United States), Cambridge, MA, United States.ORCID https://orcid.org/0009-0006-3285-6075
Isabelle MessinaChobanian and Avedisian School of Medicine, Boston University, Boston, MA, United States.ORCID https://orcid.org/0009-0003-0267-6282
Zachary HaydenChobanian and Avedisian School of Medicine, Boston University, Boston, MA, United States.ORCID https://orcid.org/0009-0007-3797-5644
Meredith KellyChobanian and Avedisian School of Medicine, Boston University, Boston, MA, United States.ORCID https://orcid.org/0009-0001-9524-4926
Gauri KamatPfizer (United States), Cambridge, MA, United States.ORCID https://orcid.org/0000-0001-9338-0820
Fikret Işık KarahanoğluPfizer (United States), Cambridge, MA, United States.ORCID https://orcid.org/0000-0002-9162-8367
Charmaine DemanuelePfizer (United States), Cambridge, MA, United States.ORCID https://orcid.org/0000-0002-7715-9920
Mar SantamariaPfizer (United States), Cambridge, MA, United States.ORCID https://orcid.org/0009-0009-7770-9425
David CaouettePfizer (United States), Cambridge, MA, United States.ORCID https://orcid.org/0009-0004-1720-7558
Kevin C ThomasChobanian and Avedisian School of Medicine, Boston University, Boston, MA, United States.ORCID https://orcid.org/0000-0003-3463-5832

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundWith the rising prevalence of aging worldwide, there is a necessity for reliable and frequent assessments of older individuals' health status to manage and potentially prevent age-related complications. Digital health technologies (DHTs), such as wearable devices, provide an opportunity to gather objective, continuous, and unobtrusive measurements, enabling effective health management in everyday life.

objectiveWe aimed to evaluate the relationship between digital endpoints and frailty, nutritional status, and patient-reported outcomes (PROs) in older individuals, as well as quantified their compliance and comfort with DHTs.

methodsIn two cross-sectional studies, namely the Geriatric Anorexia Studies 1 and 2, including three in-clinic visits and 2-3 weeks of at-home monitoring, 94 participants (mean age 72.98 years, SD 6.28 years) were stratified based on their frailty status (n=39, 41%, nonfrail; n=45, 48%, prefrail; and n=10, 11%, frail) and nutritional status (n=70, 74%, with normal nutrition and n=24, 26%, at risk for malnutrition), as assessed in a clinical setting using the Fried Frailty Score and the Simplified Nutritional Appetite Questionnaire, respectively. We remotely monitored older adults using different DHTs. At home, participants were monitored with a wrist accelerometer for physical activity, continuous glucose monitoring (CGM) for glucose concentration, a digital body scale for weight and body composition, and a digital nutritional scale for meal tracking. Compliance with devices was assessed via wear time and correct at-home usage, while comfort was evaluated using questionnaires. The association between digital endpoints and frailty/nutritional status was investigated via linear regression, followed by ANOVA, and the relationship between digital endpoints collected at home and PROs was evaluated via Spearman's ρ. Weight and body composition were also assessed during in-clinic visits with a research-grade scale, used to validate the at-home digital body scale measurements, via the intraclass correlation coefficient, Pearson's R, and Bland-Altman plots with mean bias.

resultsPhysical activity digital endpoints collected at home were significantly different across frailty and nutritional groups and significantly correlated with self-reported appetite, fatigue, and physical function (eg, for mean daily activity in the maximum 60 minutes of activity, ρ=0.28, -0.23, and 0.47, respectively). More than 80% of participants reported that all devices were mostly to very acceptable to wear/use: 95% (88/93) for the body scale, 86% (43/50) for CGM, 80% (40/50) for the nutrition scale, and 91% (84/93) for the wrist accelerometer. Compliance ranged from 60% of monitoring days for the digital nutrition scale to 90% for the wrist accelerometer.

conclusionsPhysical activity digital endpoints show clear prognostic significance for frailty and malnutrition in older individuals and reflect self-reported measures. DHTs can be reliably deployed at home for older individuals to measure their physical activity, weight and body composition, glucose concentration, and meal intakes, thus enabling patient-centric, data-centric clinical trials.

trial registrationClinicalTrials.gov NCT04858932; https://clinicaltrials.gov/study/NCT04858932; ClinicalTrials.gov NCT05211973; https://clinicaltrials.gov/study/NCT05211973.

Indexed as

Frail ElderlyFrailtyGeriatric AssessmentNutritional StatusRemote Patient MonitoringAgedAged, 80 and overCross-Sectional StudiesDigital HealthFemaleHumansMalePatient Reported Outcome MeasuresWearable Electronic Devicesdigital health technologyfrailtymalnutritionolder populationwearable devices

Identifiers

PMID41860332
PMCPMC13135171

What Socratic holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.