Evidence map›Paper›PMID 38068481›Full record

ReviewJournal of clinical medicine2023

Predicting Cardiopulmonary Arrest with Digital Biomarkers: A Systematic Review.

Gioacchino D De Sario Velasquez, Antonio J Forte, Christopher J McLeod, Charles J Bruce, Laura M Pacheco-Spann, Karla C Maita, Francisco R Avila, Ricardo A Torres-Guzman, John P Garcia, Sahar Borna and 3 more

Open access · goldAbstract readReview
In one paragraph

Review in Journal of clinical medicine, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
0.7field-weighted citation impact, top 27% 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

3 citing papers in PubMed, 2 citations in OpenAlex.

  1. Article
  2. Article
  3. 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

13 authors at 1 institution in 1 country.

Gioacchino D De Sario VelasquezDivision of Plastic Surgery, Mayo Clinic, Jacksonville, FL 32224, USA.ORCID 0009-0004-7682-2438
Antonio J ForteDivision of Plastic Surgery, Mayo Clinic, Jacksonville, FL 32224, USA.ORCID 0000-0003-2004-7538
Christopher J McLeodDepartment of Cardiovascular Medicine, Mayo Clinic, Jacksonville, FL 32224, USA.
Charles J BruceDepartment of Cardiovascular Medicine, Mayo Clinic, Jacksonville, FL 32224, USA.
Laura M Pacheco-SpannDepartment of Health Sciences Research, Mayo Clinic, Jacksonville, FL 32224, USA.ORCID 0000-0002-6531-8840
Karla C MaitaDivision of Plastic Surgery, Mayo Clinic, Jacksonville, FL 32224, USA.
Francisco R AvilaDivision of Plastic Surgery, Mayo Clinic, Jacksonville, FL 32224, USA.
Ricardo A Torres-GuzmanDivision of Plastic Surgery, Mayo Clinic, Jacksonville, FL 32224, USA.
John P GarciaDivision of Plastic Surgery, Mayo Clinic, Jacksonville, FL 32224, USA.
Sahar BornaDivision of Plastic Surgery, Mayo Clinic, Jacksonville, FL 32224, USA.
Christopher L FeltonDepartment of Physiology and Biomedical Engineering, Mayo Clinic, Rochester, MN 55902, USA.
Rickey E CarterDepartment of Health Sciences Research, Mayo Clinic, Jacksonville, FL 32224, USA.ORCID 0000-0002-0818-273X
Clifton R HaiderDepartment of Physiology and Biomedical Engineering, Mayo Clinic, Rochester, MN 55902, USA.
Mayo Clinic in Florida · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

(1) Background: Telemetry units allow the continuous monitoring of vital signs and ECG of patients. Such physiological indicators work as the digital signatures and biomarkers of disease that can aid in detecting abnormalities that appear before cardiac arrests (CAs). This review aims to identify the vital sign abnormalities measured by telemetry systems that most accurately predict CAs. (2) Methods: We conducted a systematic review using PubMed, Embase, Web of Science, and MEDLINE to search studies evaluating telemetry-detected vital signs that preceded in-hospital CAs (IHCAs). (3) Results and Discussion: Out of 45 studies, 9 met the eligibility criteria. Seven studies were case series, and 2 were case controls. Four studies evaluated ECG parameters, and 5 evaluated other physiological indicators such as blood pressure, heart rate, respiratory rate, oxygen saturation, and temperature. Vital sign changes were highly frequent among participants and reached statistical significance compared to control subjects. There was no single vital sign change pattern found in all patients. ECG alarm thresholds may be adjustable to reduce alarm fatigue. Our review was limited by the significant dissimilarities of the studies on methodology and objectives. (4) Conclusions: Evidence confirms that changes in vital signs have the potential for predicting IHCAs. There is no consensus on how to best analyze these digital biomarkers. More rigorous and larger-scale prospective studies are needed to determine the predictive value of telemetry-detected vital signs for IHCAs.

Indexed as

cardiac arrestelectrocardiogramin-hospital cardiac arrestphysiological markerphysiological monitoringtelemetryvital signs

Identifiers

PMID38068481
PMCPMC10707115
OpenAlexW4389181240

What Socratic 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 Socratic graph.