Evidence map›Paper›PMID 38358559›Full record

SynthesisAnnals of biomedical engineering2024

Cardiorespiratory Sensors and Their Implications for Out-of-Hospital Cardiac Arrest Detection: A Systematic Review.

Saud Lingawi, Jacob Hutton, Mahsa Khalili, Babak Shadgan, Jim Christenson, Brian Grunau, Calvin Kuo

Abstract readSystematic Review
PubMed Publisher
In one paragraph

Synthesis in Annals of biomedical engineering, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
4.1field-weighted citation impact, top 7% 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

4 citing papers in PubMed, 6 citations in OpenAlex.

  1. Article
  2. Article
  3. Article
  4. Wearable devices for out-of-hospital cardiac arrest: A population survey on the willingness to adhere.Journal of the American College of Emergency Physicians open · 2024
    Article
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

7 authors at 2 institutions in 1 country.

Saud Lingawi *British Columbia Resuscitation Research Collaborative, Vancouver, BC, Canada. Saud.Lingawi@ubc.ca.ORCID http://orcid.org/0000-0001-5712-2795
Jacob Hutton *British Columbia Resuscitation Research Collaborative, Vancouver, BC, Canada.ORCID http://orcid.org/0000-0001-6387-8476
Mahsa Khalili *British Columbia Resuscitation Research Collaborative, Vancouver, BC, Canada.ORCID http://orcid.org/0000-0002-0510-2554
Babak ShadganBritish Columbia Resuscitation Research Collaborative, Vancouver, BC, Canada.
Jim ChristensonBritish Columbia Resuscitation Research Collaborative, Vancouver, BC, Canada.
Brian GrunauBritish Columbia Resuscitation Research Collaborative, Vancouver, BC, Canada.
Calvin KuoBritish Columbia Resuscitation Research Collaborative, Vancouver, BC, Canada.
University of British Columbia · CAIsland Health · CA

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Out-of-hospital cardiac arrest (OHCA) is a major health problem, with a poor survival rate of 2-11%. For the roughly 75% of OHCAs that are unwitnessed, survival is approximately 2-4.4%, as there are no bystanders present to provide life-saving interventions and alert Emergency Medical Services. Sensor technologies may reduce the number of unwitnessed OHCAs through automated detection of OHCA-associated physiological changes. However, no technologies are widely available for OHCA detection. This review identifies research and commercial technologies developed for cardiopulmonary monitoring that may be best suited for use in the context of OHCA, and provides recommendations for technology development, testing, and implementation. We conducted a systematic review of published studies along with a search of grey literature to identify technologies that were able to provide cardiopulmonary monitoring, and could be used to detect OHCA. We searched MEDLINE, EMBASE, Web of Science, and Engineering Village using MeSH keywords. Following inclusion, we summarized trends and findings from included studies. Our searches retrieved 6945 unique publications between January, 1950 and May, 2023. 90 studies met the inclusion criteria. In addition, our grey literature search identified 26 commercial technologies. Among included technologies, 52% utilized electrocardiography (ECG) and 40% utilized photoplethysmography (PPG) sensors. Most wearable devices were multi-modal (59%), utilizing more than one sensor simultaneously. Most included devices were wearable technologies (84%), with chest patches (22%), wrist-worn devices (18%), and garments (14%) being the most prevalent. ECG and PPG sensors are heavily utilized in devices for cardiopulmonary monitoring that could be adapted to OHCA detection. Developers seeking to rapidly develop methods for OHCA detection should focus on using ECG- and/or PPG-based multimodal systems as these are most prevalent in existing devices. However, novel sensor technology development could overcome limitations in existing sensors and could serve as potential additions to or replacements for ECG- and PPG-based devices.

Indexed as

Out-of-Hospital Cardiac ArrestEmergency Medical ServicesHumansMonitoring, PhysiologicPhotoplethysmographyCardiopulmonaryElectrocardiographyOut-of-hospital cardiac arrestPhotoplethysmographyPhysiological monitoringWearable sensors

Identifiers

PMID38358559
OpenAlexW4391845427

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.