Evidence map›Paper›PMID 33153462›Full record

SynthesisBMC medicine2020

Use of wearable biometric monitoring devices to measure outcomes in randomized clinical trials: a methodological systematic review.

Carolina Graña Possamai, Philippe Ravaud, Lina Ghosn, Viet-Thi Tran

Open access · goldAbstract readSystematic Review
In one paragraph

Synthesis in BMC medicine, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 papers.

0numbers the graph read from it
0cells of the map it votes in
18citing papers in PubMed
4.3field-weighted citation impact, top 5% of its field
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

18 citing papers in PubMed, 40 citations in OpenAlex.

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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

4 authors at 1 institution in 2 countries.

Carolina Graña PossamaiMETHODS Team, Center for Research in Epidemiology and Statistics (CRESS), Université de Paris/INSERM (UMR 1153), 1 Place du Parvis Notre Dame, 75004, Paris, France.
Philippe RavaudMETHODS Team, Center for Research in Epidemiology and Statistics (CRESS), Université de Paris/INSERM (UMR 1153), 1 Place du Parvis Notre Dame, 75004, Paris, France.
Lina GhosnMETHODS Team, Center for Research in Epidemiology and Statistics (CRESS), Université de Paris/INSERM (UMR 1153), 1 Place du Parvis Notre Dame, 75004, Paris, France.
Viet-Thi TranMETHODS Team, Center for Research in Epidemiology and Statistics (CRESS), Université de Paris/INSERM (UMR 1153), 1 Place du Parvis Notre Dame, 75004, Paris, France. thi.tran-viet@aphp.fr.ORCID 0000-0003-1863-6739
Inserm · FR

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundWearable biometric monitoring devices (BMDs) have the potential to transform the conduct of randomized controlled trials (RCTs) by shifting the collection of outcome data from single measurements at predefined time points to dense continuous measurements.

methodsMethodological systematic review to understand how recent RCTs used BMDs to measure outcomes and to describe the reporting of these RCTs. Electronic search was performed in the Cochrane Central Register of Controlled Trials, PubMed, and EMBASE and completed a page-by-page hand search in five leading medical journals between January 1, 2018, and December 31, 2018. Three reviewers independently extracted all primary and secondary outcomes collected using BMDs, and assessed (1) the definitions used to summarize BMD outcome data; (2) whether the validity, reliability, and responsiveness of sensors was reported; (3) the discrepancy with outcomes prespecified in public clinical trial registries; and (4) the methods used to manage missing and incomplete BMD outcome data.

resultsOf the 4562 records screened, 75 RCTs were eligible. Among them, 24% tested a pharmacological intervention and 57% used an inertial measurement sensor to measure physical activity. Included trials involved 464 outcomes (average of 6 [SD = 8] outcomes per trial). In total, 35 trials used a BMD to measure a primary outcome. Several issues affected the value and transparency of trials using BMDs to measure outcomes. First, the definition of outcomes used in the trials was highly heterogeneous (e.g., 21 diabetes trials had 266 outcomes and 153 had different unique definitions to measure diabetes control), which limited the combination and comparison of results. Second, information on the validity, reliability, and responsiveness of sensors used was lacking in 74% of trials. Third, half (53%) of the outcomes measured with BMDs had not been prespecified, with a high risk of outcome reporting bias. Finally, reporting on the management of incomplete outcome data (e.g., due to suboptimal compliance with the BMD) was absent in 68% of RCTs.

conclusionsUse of BMDs to measure outcomes is becoming the norm rather than the exception in many fields. Yet, trialists need to account for several methodological issues when specifying and conducting RCTs using these novel tools.

Indexed as

Wearable Electronic DevicesFemaleHumansMaleMonitoring, PhysiologicRandomized Controlled Trials as TopicReproducibility of ResultsTreatment OutcomeClinical trialsOutcomesWearable devices

Identifiers

PMID33153462
PMCPMC7646072
OpenAlexW3094734549

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.