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

Abstract

Background: Community-acquired pneumonia (CAP) is an essential consideration in patients presenting to primary care with respiratory symptoms; however, accurate diagnosis is difficult when clinical and radiologic examinations are not possible, such as during telehealth consultations. Aim: To develop and test a smartphone-based algorithm for diagnosing CAP without need for clinical examination or radiology inputs. Design and Setting: A prospective cohort study using data from subjects aged over 12 years presenting with acute respiratory symptoms to a hospital in Western Australia. Method: Five cough audio-segments were recorded and four patient-reported symptoms (fever, acute cough, productive cough, age) were analysed by the smartphone-based algorithm to generate an immediate diagnostic output for CAP. We recruited independent cohorts 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. Results: The algorithm had high percent agreement (PA) with the clinical diagnosis of CAP in the total cohort (n=322, Positive PA=86%, Negative PA=86%, AUC=0.95); in subjects 22-65 years (n=192, PPA=86%, NPA=87%, AUC=0.94) and in subjects >65 years (n=86, PPA=86%, NPA=87.5%, AUC=0.94). Agreement was preserved across CAP severity: 85% (80/94) of subjects with CRB-65 scores 1-2, and 87% (57/65) with a score of 0, were correctly diagnosed by the algorithm. Conclusion: The 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.

Diagnostic errors are common in acute pediatric respiratory disease: a prospective, single-blinded multicenter diagnostic accuracy study in Australian Emergency Departments

“…This approach, however, relies on the quality and generalizability of the training data sets and can only be used after all information has been entered into the patient's medical record. Studies of algorithms that use point-of-care automated cough-centered analysis have reported good diagnostic accuracy for respiratory diseases, including pneumonia, correctly identifying 87% of children and 86% of adults without the need for clinical examination or investigations (49)(50)(51)(52). In settings with limited resources, such algorithms might provide a diagnostic method equal to the accuracy of well-resourced E.D.s.…”

Diagnostic Errors Are Common in Acute Pediatric Respiratory Disease: A Prospective, Single-Blinded Multicenter Diagnostic Accuracy Study in Australian Emergency Departments

“…This approach, however, relies on the quality and generalizability of the training data sets and can only be used after all information has been entered into the patient's medical record. Studies of algorithms that use point-of-care automated cough-centered analysis have reported good diagnostic accuracy for respiratory diseases, including pneumonia, correctly identifying 87% of children and 86% of adults without the need for clinical examination or investigations (49)(50)(51)(52). In settings with limited resources, such algorithms might provide a diagnostic method equal to the accuracy of wellresourced E.D.s.…”

Cough Sounds Recorded via Smart Devices as Useful Non-Invasive Digital Biomarkers of Aspiration Risk: A Case Report

“…Whereas past studies on automatic detection of cough sounds required the use of heavy equipment, recent advancements in digital devices and the rise in telehealth demand with the COVID-19 pandemic [ 4 , 6 , 7 ] have facilitated the capabilities of mobile devices to record cough sounds successfully. New techniques can extract features that can be applied to algorithms for diagnosis [ 5 ], or community-acquired pneumonia [ 1 ]. Our two cases are the first to rely on digital devices to record acoustic cough sounds in aspiration pneumonia.…”

“…Globally, pneumonia is the most common cause of infectious mortality, with more than two million adults dying from lower respiratory infections [ 1 ]. Previously collected data indicate that 60% of community-acquired pneumonia patients and 87% of hospital-acquired pneumonia patients are diagnosed with aspiration pneumonia [ 2 ].…”