Evidence map›Paper›PMID 36279171›Full record

ArticleJMIR mHealth and uHealth2022

Digital Biomarker-Based Studies: Scoping Review of Systematic Reviews.

Hossein Motahari-Nezhad, Meriem Fgaier, Mohamed Mahdi Abid, Márta Péntek, László Gulácsi, Zsombor Zrubka

Abstract readScoping Review
In one paragraph

Article in JMIR mHealth and uHealth, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 31 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
31citing papers in PubMed, 1 pooled it
–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.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

31 citing papers in PubMed, 1 synthesis or guideline pooled it.

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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

6 authors.

Hossein Motahari-Nezhad *Doctoral School of Business and Management, Corvinus University of Budapest, Budapest, Hungary.ORCID 0000-0002-1028-4460
Meriem FgaierDoctoral School of Applied Informatics and Applied Mathematics, Óbuda University, Budapest, Hungary.ORCID 0000-0002-6658-8164
Mohamed Mahdi AbidResearch Center of Epidemiology and Statistics Sorbonne Paris Cité, Paris University, Paris, France.ORCID 0000-0002-5737-7752
Márta PéntekHealth Economics Research Center, University Research and Innovation Center, Óbuda University, Budapest, Hungary.ORCID 0000-0001-9636-6012
László GulácsiHealth Economics Research Center, University Research and Innovation Center, Óbuda University, Budapest, Hungary.ORCID 0000-0002-9285-8746
Zsombor ZrubkaHealth Economics Research Center, University Research and Innovation Center, Óbuda University, Budapest, Hungary.ORCID 0000-0002-1992-6087

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundSensors and digital devices have revolutionized the measurement, collection, and storage of behavioral and physiological data, leading to the new term digital biomarkers.

objectiveThis study aimed to investigate the scope of clinical evidence covered by systematic reviews (SRs) of randomized controlled trials involving digital biomarkers.

methodsThis scoping review was organized using the PRISMA-ScR (Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews) guidelines. With the search limited to English publications, full-text SRs of digital biomarkers included randomized controlled trials that involved a human population and reported changes in participants' health status. PubMed and the Cochrane Library were searched with time frames limited to 2019 and 2020. The World Health Organization's classification systems for diseases (International Classification of Diseases, Eleventh Revision), health interventions (International Classification of Health Interventions), and bodily functions (International Classification of Functioning, Disability, and Health [ICF]) were used to classify populations, interventions, and outcomes, respectively.

resultsA total of 31 SRs met the inclusion criteria. The majority of SRs studied patients with circulatory system diseases (19/31, 61%) and respiratory system diseases (9/31, 29%). Most of the prevalent interventions focused on physical activity behavior (16/31, 52%) and conversion of cardiac rhythm (4/31, 13%). Looking after one's health (physical activity; 15/31, 48%), walking (12/31, 39%), heart rhythm functions (8/31, 26%), and mortality (7/31, 23%) were the most commonly reported outcomes. In total, 16 physiological and behavioral data groups were identified using the ICF tool, such as looking after one's health (physical activity; 14/31, 45%), walking (11/31, 36%), heart rhythm (7/31, 23%), and weight maintenance functions (7/31, 23%). Various digital devices were also studied to collect these data in the included reviews, such as smart glasses, smartwatches, smart bracelets, smart shoes, and smart socks for measuring heart functions, gait pattern functions, and temperature. A substantial number (24/31, 77%) of digital biomarkers were used as interventions. Moreover, wearables (22/31, 71%) were the most common types of digital devices. Position sensors (21/31, 68%) and heart rate sensors and pulse rate sensors (12/31, 39%) were the most prevalent types of sensors used to acquire behavioral and physiological data in the SRs.

conclusionsIn recent years, the clinical evidence concerning digital biomarkers has been systematically reviewed in a wide range of study populations, interventions, digital devices, and sensor technologies, with the dominance of physical activity and cardiac monitors. We used the World Health Organization's ICF tool for classifying behavioral and physiological data, which seemed to be an applicable tool to categorize the broad scope of digital biomarkers identified in this review. To understand the clinical value of digital biomarkers, the strength and quality of the evidence on their health consequences need to be systematically evaluated.

Indexed as

BiomarkersExerciseHumansRandomized Controlled Trials as TopicSystematic Reviews as TopicTechnologyBiomarkersbehavioral datadigestibledigital biomarkersdigital healthhealthimplantablemobile phonephysiological dataportableremote monitoringscoping reviewsensorwearable

Identifiers

PMID36279171
PMCPMC9641516

What OpenQuestion holds

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LicenceCC BY
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Registered trials

None linked

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 OpenQuestion graph.