Evidence map›Paper›PMID 37698697›Full record

ArticleJournal of clinical monitoring and computing2024

Video plethysmography for contactless measurement of respiratory rate in surgical patients.

Khashayar Poorzargar, Chi Pham, Darshan Panesar, Sheila Riazi, Kang Lee, Matteo Parotto, Frances Chung

Abstract read
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In one paragraph

Article in Journal of clinical monitoring and computing, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
0.5field-weighted citation impact, top 38% 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

2 citing papers in PubMed, 5 citations in OpenAlex.

  1. Article
  2. 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.

Khashayar Poorzargar *Department of Anesthesia and Pain Medicine, Toronto Western Hospital, University Health Network, University of Toronto, Toronto, ON, Canada.
Chi Pham *Department of Anesthesia and Pain Medicine, Toronto Western Hospital, University Health Network, University of Toronto, Toronto, ON, Canada.
Darshan PanesarOntario Institute for Studies in Education, University of Toronto, Toronto, ON, Canada.
Sheila RiaziDepartment of Anesthesia and Pain Medicine, Toronto Western Hospital, University Health Network, University of Toronto, Toronto, ON, Canada.
Kang LeeOntario Institute for Studies in Education, University of Toronto, Toronto, ON, Canada.
Matteo ParottoDepartment of Anesthesia and Pain Medicine, Toronto General Hospital, University Health Network, University of Toronto, Toronto, ON, Canada.
Frances ChungDepartment of Anesthesia and Pain Medicine, Toronto Western Hospital, University Health Network, University of Toronto, Toronto, ON, Canada. frances.chung@uhn.ca.ORCID 0000-0001-9576-3606
University Health Network · CAUniversity of Toronto · CA

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The accurate recording of respiratory rate (RR) without contact is important for patient care. The current methods for RR measurement such as capnography, pneumography, and plethysmography require patient contact, are cumbersome, or not accurate for widespread clinical use. Video Plethysmography (VPPG) is a novel automated technology that measures RR using a facial video without contact. The objective of our study was to determine whether VPPG can feasibly and accurately measure RR without contact in surgical patients at a clinical setting. After research ethics approval, 216 patients undergoing ambulatory surgery consented to the study. Patients had a 1.5 min video of their faces taken via an iPad preoperatively, which was analyzed using VPPG to obtain RR information. The RR prediction by VPPG was compared to 60-s manual counting of breathing by research assistants. We found that VPPG predicted RR with 88.8% accuracy and a bias of 1.40 ± 1.96 breaths per minute. A significant and high correlation (0.87) was observed between VPPG-predicted and manually recorded RR. These results did not change with the ethnicity of patients. The success rate of the VPPG technology was 99.1%. Contactless RR monitoring of surgical patients at a hospital setting using VPPG is accurate and feasible, making this technology an attractive alternative to the current approaches to RR monitoring. Future developments should focus on improving reliability of the technology.

Indexed as

PlethysmographyRespiratory RateHumansMonitoring, PhysiologicReproducibility of ResultsRespirationContactless measurement technologyRespiratory rateSurgeryVideo plethysmographyVirtual careVital sign monitoring

Identifiers

PMID37698697
OpenAlexW4386623943

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.