Evidence map›Paper›PMID 33558330›Full record

ArticleThe British journal of general practice : the journal of the Royal College of General Practitioners2021

Diagnosing community-acquired pneumonia via a smartphone-based algorithm: a prospective cohort study in primary and acute-care consultations.

Paul Porter, Joanna Brisbane, Udantha Abeyratne, Natasha Bear, Javan Wood, Vesa Peltonen, Phillip Della, Claire Smith, Scott Claxton

Open access · hybridAbstract read
In one paragraph

Article in The British journal of general practice : the journal of the Royal College of General Practitioners, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
12citing papers in PubMed, 2 pooled it
2.0field-weighted citation impact, top 12% 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

12 citing papers in PubMed, 2 syntheses or guidelines pooled it, 21 citations in OpenAlex.

  1. Cough biomarkers for diagnosis and monitoring of respiratory disease: a systematic review.European respiratory review : an official journal of the European Respiratory Society · 2026
    Pooled it
  2. Audio-based digital biomarkers in diagnosing and managing respiratory diseases: a systematic review and bibliometric analysis.European respiratory review : an official journal of the European Respiratory Society · 2025
    Pooled it
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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

9 authors at 5 institutions in 4 countries.

Paul PorterSchool of Nursing, Midwifery and Paramedicine, Curtin University, Bentley; Joondalup Health Campus, Joondalup.
Joanna BrisbaneJoondalup Health Campus, Joondalup.ORCID http://orcid.org/0000-0003-3364-5414
Udantha AbeyratneSchool of Information Technology and Electrical Engineering, University of Queensland, Brisbane, Queensland.
Natasha BearInstitute of Health Research, University of Notre Dame, Western Australia.
Javan WoodResApp Health, Brisbane, Queensland.
Vesa PeltonenResApp Health, Brisbane, Queensland.
Phillip DellaSchool of Nursing, Midwifery and Paramedicine, Curtin University, Bentley, Western Australia.
Claire SmithJoondalup Health Campus, Joondalup.
Scott ClaxtonJoondalup Health Campus, Joondalup; Genesis Care Sleep and Respiratory, Perth.
Edith Cowan University · AUQueensland Health · AUCurtin University · AUQueensland University of Technology · AUThe University of Notre Dame Australia · AU

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundCommunity-acquired pneumonia (CAP) is an essential consideration in patients presenting to primary care with respiratory symptoms; however, accurate diagnosis is difficult when clinical and radiological examinations are not possible, such as during telehealth consultations.

aimTo develop and test a smartphone-based algorithm for diagnosing CAP without need for clinical examination or radiological inputs. DESIGN AND

settingA prospective cohort study using data from participants aged >12 years presenting with acute respiratory symptoms to a hospital in Western Australia.

methodFive cough audio-segments were recorded and four patient-reported symptoms (fever, acute cough, productive cough, and age) were analysed by the smartphone-based algorithm to generate an immediate diagnostic output for CAP. Independent cohorts were recruited to train and test the accuracy of the algorithm. Diagnostic agreement was calculated against the confirmed discharge diagnosis of CAP by specialist physicians. Specialist radiologists reported medical imaging.

resultsThe smartphone-based algorithm had high percentage agreement (PA) with the clinical diagnosis of CAP in the total cohort (

conclusionThe algorithm provides rapid and accurate diagnosis of CAP. It offers improved accuracy over current protocols when clinical evaluation is difficult. It provides increased capabilities for primary and acute care, including telehealth services, required during the COVID-19 pandemic.

Indexed as

AlgorithmsAdultAgedCohort StudiesCommunity-Acquired InfectionsCoughCOVID-19FemaleFeverHumansMiddle AgedProspective StudiesRemote ConsultationSmartphonealgorithmsdiagnosispneumoniaprimary health caretelemedicine

Identifiers

PMID33558330
PMCPMC8007248
OpenAlexW3112298737

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.