Evidence map›Paper›PMID 31471076›Full record

ArticleThe American journal of emergency medicine2020

The utility of iPhone oximetry apps: A comparison with standard pulse oximetry measurement in the emergency department.

Taylor B Jordan, Cody L Meyers, Walter A Schrading, John P Donnelly

Open access · greenAbstract readComparative Study
In one paragraph

Article in The American journal of emergency medicine, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 papers.

0numbers the graph read from it
0cells of the map it votes in
18citing papers in PubMed
1.9field-weighted citation impact, top 15% 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

18 citing papers in PubMed, 27 citations in OpenAlex.

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  13. Digital health & low-value care.Healthcare (Amsterdam, Netherlands) · 2021
    Article
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  15. Review
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  17. Wearables for the Next Pandemic.IEEE access : practical innovations, open solutions · 2020
    Article
  18. 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

4 authors at 3 institutions in 1 country.

Taylor B JordanUniversity of Alabama at Birmingham School of Medicine, United States of America.
Cody L MeyersGreenville Health System, United States of America.
Walter A SchradingUniversity of Alabama at Birmingham, Department of Emergency Medicine, Office of Wilderness Medicine, United States of America. Electronic address: wschrading@uabmc.edu.
John P DonnellyUniversity of Michigan School of Medicine, Department of Learning and Health Sciences, United States of America.
University of Alabama at Birmingham · USPrisma Health · USUniversity of Michigan · US

Funding

UAB Short-Term Research Training in Health Professional Schools (SHRT)T35HL007473 · NHLBI · UNIVERSITY OF ALABAMA AT BIRMINGHAM · PI WILLIAM M GEISLER · 1985 to 2026
$4.0M
Training to Advance Care Through Implementation Science in Cardiac And Lung Illnesses (TACTICAL)K12HL138039 · NHLBI · UNIVERSITY OF MICHIGAN AT ANN ARBOR · PI BARNES, GEOFFREY DOUGLAS, PRESCOTT, HALLIE CHRISTINE · 2017 to 2021
$3.1M
Immunosuppression and Risk Prediction of Sepsis after Solid Organ TransplantationF31GM122180 · NIGMS · UNIVERSITY OF ALABAMA AT BIRMINGHAM · PI DONNELLY, JOHN P · 2017 to 2018
$52k
NHLBI NIH HHS K12 HL138039NHLBI NIH HHS T35 HL007473NIGMS NIH HHS F31 GM122180
6 · The paper itself

Abstract

objectivesTo determine if a correlation exists between 3 iphone pulse ox applications' measurements and the standard pulse oximetry (SpO2) and whether these applications can accurately determine hypoxia.

methodsThree applications reportedly measuring SpO2 were downloaded onto an iPhone 5s. Two of these applications used the onboard light and camera lens "Pulse Oximeter" (Pox) and "Heart Rate and Pulse Oximeter" (Ox) and one used an external device that plugged into the iphone (iOx). Patients in the ED were enrolled with chief complaints of cardiac/pulmonary origin or a SpO2 ≤ 94%. All measurements were compared to controls. Concordance correlation coefficients, sensitivity, and specificity were calculated.

resultsA total of 191 patients were enrolled. The concordance correlation of iOx with control was 0.55 (CI 0.46, 0.63), POx was 0.01 (CI -0.09, 0.11), and Ox was 0.07 (CI -0.02, 0.15). 68/191 patients (35%) were found to have hypoxemia. Sensitivities for detecting hypoxia were 69%, 0%, and 7% for iOx, POx, and Ox, respectively. Specificities were 89%, 100%, and 89%. Even iOx (the most accurate) 21 (11%) were incorrectly classified nonhypoxic, and 22 (12%) were incorrectly classified hypoxic.

conclusionsWhile iOx has modest concordance with control, Ox and POx showed almost none. The iOx device was best in correctly identifying hypoxia patients, but almost 1/4 of patients were incorrectly classified. The three apps provided inaccurate SpO2 measurements and had limited to no ability to accurately detect hypoxia. These apps should not be relied upon to provide accurate SpO2 measurements in emergent, even austere conditions.

Indexed as

Cell PhoneMobile ApplicationsOximetryAdultAgedCorrelation of DataEmergency Service, HospitalFemaleHumansHypoxiaMaleMiddle AgedSensitivity and SpecificityApplicationsiPhone appsOximetryPulse oxSmart phone

Identifiers

PMID31471076
PMCPMC6960362
OpenAlexW2960544909

What OpenQuestion holds

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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.