Evidence map›Paper›PMID 34583742›Full record

SynthesisCritical care (London, England)2021

The impact of wearable continuous vital sign monitoring on deterioration detection and clinical outcomes in hospitalised patients: a systematic review and meta-analysis.

Carlos Areia, Christopher Biggs, Mauro Santos, Neal Thurley, Stephen Gerry, Lionel Tarassenko, Peter Watkinson, Sarah Vollam

Open access · goldAbstract readMeta-AnalysisSystematic Review
In one paragraph

Synthesis in Critical care (London, England), 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 36 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
36citing papers in PubMed, 1 pooled it
10.9field-weighted citation impact, top 1% 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

36 citing papers in PubMed, 1 synthesis or guideline pooled it, 83 citations in OpenAlex.

  1. Pooled it
  2. Trial
  3. Article
  4. Alert burden when monitoring patients' vital signs continuously at home.Journal of clinical monitoring and computing · 2026
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  7. Review
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  18. Ability to identify patient-ventilator asynchronies in intensive care unit professionals: A multicenter cross-sectional analytical study.Journal of critical care medicine (Universitatea de Medicina si Farmacie din Targu-Mures) · 2025
    Article
  19. Integrating enterprise risk management to address AI-related risks in healthcare: Strategies for effective risk mitigation and implementation.Journal of healthcare risk management : the journal of the American Society for Healthcare Risk Management · 2025
    Article
  20. Article
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

8 authors at 3 institutions in 1 country.

Carlos AreiaCritical Care Research Group, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, Oxfordshire, UK. carlos.morgadoareia@ndcn.ox.ac.uk.ORCID 0000-0002-4668-7069
Christopher BiggsCritical Care Research Group, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, Oxfordshire, UK.ORCID 0000-0003-0348-5480
Mauro SantosBiomedical Research Centre, National Institute for Health Research, Oxford, UK.ORCID 0000-0002-1470-6966
Neal ThurleyBodleian Health Care Libraries, University of Oxford, Oxford, Oxfordshire, UK.
Stephen GerryCentre for Statistics in Medicine, Nuffield Department of Orthopaedics, Rheumatology and Musculoskeletal Sciences, University of Oxford, Oxford, UK.
Lionel TarassenkoBiomedical Research Centre, National Institute for Health Research, Oxford, UK.ORCID 0000-0002-0118-1646
Peter WatkinsonCritical Care Research Group, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, Oxfordshire, UK.ORCID 0000-0003-1023-3927
Sarah VollamCritical Care Research Group, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, Oxfordshire, UK.ORCID 0000-0003-2835-6271
National Institute for Health Research · GBNuffield Orthopaedic Centre · GBUniversity of Oxford · GB

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundTimely recognition of the deteriorating inpatient remains challenging. Wearable monitoring systems (WMS) may augment current monitoring practices. However, there are many barriers to implementation in the hospital environment, and evidence describing the clinical impact of WMS on deterioration detection and patient outcome remains unclear.

objectiveTo assess the impact of vital-sign monitoring on detection of deterioration and related clinical outcomes in hospitalised patients using WMS, in comparison with standard care.

methodsA systematic search was conducted in August 2020 using MEDLINE, Embase, CINAHL, Cochrane Database of Systematic Reviews, CENTRAL, Health Technology Assessment databases and grey literature. Studies comparing the use of WMS against standard care for deterioration detection and related clinical outcomes in hospitalised patients were included. Deterioration related outcomes (primary) included unplanned intensive care admissions, rapid response team or cardiac arrest activation, total and major complications rate. Other clinical outcomes (secondary) included in-hospital mortality and hospital length of stay. Exploratory outcomes included alerting system parameters and clinical trial registry information.

resultsOf 8706 citations, 10 studies with different designs met the inclusion criteria, of which 7 were included in the meta-analyses. Overall study quality was moderate. The meta-analysis indicated that the WMS, when compared with standard care, was not associated with significant reductions in intensive care transfers (risk ratio, RR 0.87; 95% confidence interval, CI 0.66-1.15), rapid response or cardiac arrest team activation (RR 0.84; 95% CI 0.69-1.01), total (RR 0.77; 95% CI 0.44-1.32) and major (RR 0.55; 95% CI 0.24-1.30) complications prevalence. There was also no statistically significant association with reduced mortality (RR 0.48; 95% CI 0.18-1.29) and hospital length of stay (mean difference, MD - 0.09; 95% CI - 0.43 to 0.44).

conclusionThis systematic review indicates that there is no current evidence that implementation of WMS impacts early deterioration detection and associated clinical outcomes, as differing design/quality of available studies and diversity of outcome measures make it difficult to reach a definite conclusion. Our narrative findings suggested that alarms should be adjusted to minimise false alarms and promote rapid clinical action in response to deterioration. PROSPERO Registration number: CRD42020188633 .

Indexed as

Monitoring, PhysiologicVital SignsWearable Electronic DevicesClinical DeteriorationHospitalizationHumansOutcome Assessment, Health CareClinical outcomesDeterioration detectionHospitalICU transferVital signsWearable monitoringWearables

Identifiers

PMID34583742
PMCPMC8477465
OpenAlexW3202874627

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

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.