Evidence map›Paper›PMID 34878613›Full record

ArticleJournal of clinical monitoring and computing2022

Continuous vital sign monitoring using a wearable patch sensor in obese patients: a validation study in a clinical setting.

Niels Kant, Guido M Peters, Brenda J Voorthuis, Catharina G M Groothuis-Oudshoorn, Mark V Koning, Bart P L Witteman, Myra Rinia-Feenstra, Carine J M Doggen

Open access · hybridAbstract read
PubMed Publisher
In one paragraph

Article in Journal of clinical monitoring and computing, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.

0numbers the graph read from it
0cells of the map it votes in
11citing papers in PubMed
1.3field-weighted citation impact, top 22% 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

11 citing papers in PubMed, 19 citations in OpenAlex.

  1. Trial
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  11. The Related Metabolic Diseases and Treatments of Obesity.Healthcare (Basel, Switzerland) · 2022
    Review
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

8 authors at 2 institutions in 1 country.

Niels Kant *Department of Anesthesiology and Pain Management, Rijnstate Hospital, Arnhem, The Netherlands.
Guido M Peters *Scientific Bureau, Rijnstate Hospital, Rijnstate Research Center, Wagnerlaan 55, PO Box 9555, 6800 TA, Arnhem, The Netherlands.
Brenda J VoorthuisTechnical Medical Centre, Department of Health Technology and Services Research, University of Twente, Enschede, The Netherlands.
Catharina G M Groothuis-OudshoornTechnical Medical Centre, Department of Health Technology and Services Research, University of Twente, Enschede, The Netherlands.
Mark V KoningDepartment of Anesthesiology and Pain Management, Rijnstate Hospital, Arnhem, The Netherlands.
Bart P L WittemanRijnstate Hospital, Vitalys Obesity Centre, Arnhem, The Netherlands.
Myra Rinia-FeenstraDepartment of Anesthesiology and Pain Management, Rijnstate Hospital, Arnhem, The Netherlands.
Carine J M DoggenScientific Bureau, Rijnstate Hospital, Rijnstate Research Center, Wagnerlaan 55, PO Box 9555, 6800 TA, Arnhem, The Netherlands. cdoggen@rijnstate.nl.ORCID 0000-0003-4766-4333
Rijnstate Hospital · NLUniversity of Twente · NL

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Our aim was to determine the agreement of heart rate (HR) and respiratory rate (RR) measurements by the Philips Biosensor with a reference monitor (General Electric Carescape B650) in severely obese patients during and after bariatric surgery. Additionally, sensor reliability was assessed. Ninety-four severely obese patients were monitored with both the Biosensor and reference monitor during and after bariatric surgery. Agreement was defined as the mean absolute difference between both monitoring devices. Bland Altman plots and Clarke Error Grid analysis (CEG) were used to visualise differences. Sensor reliability was reflected by the amount, duration and causes of data loss. The mean absolute difference for HR was 1.26 beats per minute (bpm) (SD 0.84) during surgery and 1.84 bpm (SD 1.22) during recovery, and never exceeded the 8 bpm limit of agreement. The mean absolute difference for RR was 1.78 breaths per minute (brpm) (SD 1.90) during surgery and 4.24 brpm (SD 2.75) during recovery. The Biosensor's RR measurements exceeded the 2 brpm limit of agreement in 58% of the compared measurements. Averaging 15 min of measurements for both devices improved agreement. CEG showed that 99% of averaged RR measurements resulted in adequate treatment. Data loss was limited to 4.5% of the total duration of measurements for RR. No clear causes for data loss were found. The Biosensor is suitable for remote monitoring of HR, but not RR in morbidly obese patients. Future research should focus on improving RR measurements, the interpretation of continuous data, and development of smart alarm systems.

Indexed as

Obesity, MorbidWearable Electronic DevicesHeart RateHumansMonitoring, PhysiologicReproducibility of ResultsRespiratory RateContinuous monitoringMonitoringPhysiologic/instrumentationVital signsWearable electronic devicesWireless technology

Identifiers

PMID34878613
OpenAlexW4200575034

What OpenQuestion holds

Textmetadata
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.