Dataset Information

Diagnostic Performance of a Smartphone-Based Photoplethysmographic Application for Atrial Fibrillation Screening in a Primary Care Setting.

ABSTRACT:

Background

Diagnosing atrial fibrillation (AF) before ischemic stroke occurs is a priority for stroke prevention in AF. Smartphone camera-based photoplethysmographic (PPG) pulse waveform measurement discriminates between different heart rhythms, but its ability to diagnose AF in real-world situations has not been adequately investigated. We sought to assess the diagnostic performance of a standalone smartphone PPG application, Cardiio Rhythm, for AF screening in primary care setting.

Methods and results

Patients with hypertension, with diabetes mellitus, and/or aged ?65 years were recruited. A single-lead ECG was recorded by using the AliveCor heart monitor with tracings reviewed subsequently by 2 cardiologists to provide the reference standard. PPG measurements were performed by using the Cardiio Rhythm smartphone application. AF was diagnosed in 28 (2.76%) of 1013 participants. The diagnostic sensitivity of the Cardiio Rhythm for AF detection was 92.9% (95% CI] 77-99%) and was higher than that of the AliveCor automated algorithm (71.4% [95% CI 51-87%]). The specificities of Cardiio Rhythm and the AliveCor automated algorithm were comparable (97.7% [95% CI: 97-99%] versus 99.4% [95% CI 99-100%]). The positive predictive value of the Cardiio Rhythm was lower than that of the AliveCor automated algorithm (53.1% [95% CI 38-67%] versus 76.9% [95% CI 56-91%]); both had a very high negative predictive value (99.8% [95% CI 99-100%] versus 99.2% [95% CI 98-100%]).

Conclusions

The Cardiio Rhythm smartphone PPG application provides an accurate and reliable means to detect AF in patients at risk of developing AF and has the potential to enable population-based screening for AF.

SUBMITTER: Chan PH

PROVIDER: S-EPMC5015379 | biostudies-literature | 2016 Jul

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Diagnostic Performance of a Smartphone-Based Photoplethysmographic Application for Atrial Fibrillation Screening in a Primary Care Setting.

Chan Pak-Hei PH Wong Chun-Ka CK Poh Yukkee C YC Pun Louise L Leung Wangie Wan-Chiu WW Wong Yu-Fai YF Wong Michelle Man-Ying MM Poh Ming-Zher MZ Chu Daniel Wai-Sing DW Siu Chung-Wah CW

Journal of the American Heart Association 20160721 7

<h4>Background</h4>Diagnosing atrial fibrillation (AF) before ischemic stroke occurs is a priority for stroke prevention in AF. Smartphone camera-based photoplethysmographic (PPG) pulse waveform measurement discriminates between different heart rhythms, but its ability to diagnose AF in real-world situations has not been adequately investigated. We sought to assess the diagnostic performance of a standalone smartphone PPG application, Cardiio Rhythm, for AF screening in primary care setting.<h4> ...[more]

PMID: 27444506

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Project description:BackgroundWe aimed to evaluate a novel method of atrial fibrillation (AF) screening using an iPhone camera to detect and analyze photoplethysmographic signals from the face without physical contact by extracting subtle beat-to-beat variations of skin color that reflect the cardiac pulsatile signal.Methods and resultsPatients admitted to the cardiology ward of the hospital for clinical reasons were recruited. Simultaneous facial and fingertip photoplethysmographic measurements were obtained from 217 hospital inpatients (mean age, 70.3±13.9 years; 71.4% men) facing the front camera and with an index finger covering the back camera of 2 independent iPhones before a 12-lead ECG was recorded. Backdrop and background light intensity was monitored during signal acquisition. Three successive 20-second (total, 60 seconds) recordings were acquired per patient and analyzed for heart rate regularity by Cardiio Rhythm (Cardiio Inc, Cambridge, MA) smartphone application. Pulse irregularity in ?1 photoplethysmographic readings or 3 uninterpretable photoplethysmographic readings were considered a positive AF screening result. AF was present on 12-lead ECG in 34.6% (n=75/217) patients. The Cardiio Rhythm facial photoplethysmographic application demonstrated high sensitivity (95%; 95% confidence interval, 87%-98%) and specificity (96%; 95% confidence interval, 91%-98%) in discriminating AF from sinus rhythm compared with 12-lead ECG. The positive and negative predictive values were 92% (95% confidence interval, 84%-96%) and 97% (95% confidence interval, 93%-99%), respectively.ConclusionsDetection of a facial photoplethysmographic signal to determine pulse irregularity attributable to AF is feasible. The Cardiio Rhythm smartphone application showed high sensitivity and specificity, with low negative likelihood ratio for AF from facial photoplethysmographic signals. The convenience of a contact-free approach is attractive for community screening and has the potential to be useful for distant AF screening.

Project description:OBJECTIVE:To evaluate the diagnostic performance of a UK National Institute for Health and Care Excellence-recommended automatic oscillometric blood pressure (BP) measurement device incorporated with an atrial fibrillation (AF) detection algorithm (Microlife WatchBP Home A) for real-world AF screening in a primary healthcare setting. SETTING:Primary healthcare setting in Hong Kong. INTERVENTIONS:This was a prospective AF screening study carried out between 1 September 2014 and 14 January 2015. The Microlife device was evaluated for AF detection and compared with a reference standard of lead-I ECG. PRIMARY OUTCOME MEASURES:Diagnostic performance of Microlife for AF detection. RESULTS:5969 patients (mean age: 67.2±11.0 years; 53.9% female) were recruited. The mean CHA2DS2-VASc ( C : congestive heart failure [1 point]; H : hypertension [1 point]; A2 : age 65-74 years [1 point] and age ?75 years [2 points]; D : diabetes mellitus [1 point]; S : prior stroke or transient ischemic attack [2 points]; VA : vascular disease [1 point]; and Sc : sex category [female] [1 point])score was 2.8±1.3. AF was diagnosed in 72 patients (1.21%) and confirmed by a 12-lead ECG. The Microlife device correctly identified AF in 58 patients and produced 79 false-positives. The corresponding sensitivity and specificity for AF detection were 80.6% (95% CI 69.5 to 88.9) and 98.7% (95% CI 98.3 to 98.9), respectively. Among patients with a false-positive by the Microlife device, 30.4% had sinus rhythm, 35.4% had sinus arrhythmia and 29.1% exhibited premature atrial complexes. With the low prevalence of AF in this population, the positive and negative predictive values of Microlife device for AF detection were 42.4% (95% CI 34.0 to 51.2) and 99.8% (95% CI 99.6 to 99.9), respectively. The overall diagnostic performance of Microlife device to detect AF as determined by area under the curves was 0.90 (95% CI 0.89 to 0.90). CONCLUSIONS:In the primary care setting, Microlife WatchBP Home was an effective means to screen for AF, with a reasonable sensitivity of 80.6% and a high negative predictive value of 99.8%, in addition to its routine function of BP measurement. In a younger patient population aged <65 years with a lower prevalence of AF, Microlife WatchBP Home A demonstrated a similar diagnostic accuracy.

Project description:BackgroundDetection of undiagnosed or undertreated ("actionable") atrial fibrillation could increase the use of appropriate oral anticoagulant therapy and reduce the risk of stroke. We sought to compare newer screening technologies with a pulse-check for the detection of atrial fibrillation and to determine whether the detection of actionable atrial fibrillation increases the use of oral anticoagulant agents.MethodsThis prospective multicentre cohort study involved 22 primary care clinics. We recruited participants aged 65 years and older who were attending routine appointments. Each participant underwent 3 methods of screening: a 30-second radial pulse-check; single-lead electrocardiogram; and screening by blood pressure machine with atrial fibrillation detection algorithms. Participants who received a positive result on 1 or more test underwent 12-lead electrocardiogram with or withour 24-hour Holter. Screening tests were compared using the McNemar test. Participants with confirmed atrial fibrillation received follow-up at 90 days.ResultsThe mean age of participants was 73.7 (± 6.9) years, and 53.4% of participants were female. Of 2171 patients, we had data from all 3 screening tests for 2054 patients. Both single-lead electrocardiogram and the blood pressure device showed superior specificity compared with pulse-check (p < 0.001 for each). Fifty-six patients (2.7%) had confirmed atrial fibrillation: 12 patients had newly detected atrial fibrillation (none of the patients were using anticoagulation agents), and 44 patients had previously diagnosed atrial fibrillation (42 patients were receiving anticoagulant therapy, 2 were not). Thus, 14 patients had actionable atrial fibrillation (0.7%). By 90 days, 77% of patients with actionable atrial fibrillation had started anticoagulant therapy.InterpretationNewer screening technologies showed superior specificity compared with a pulse-check. Screening detected undiagnosed or undertreated atrial fibrillation in 0.7% of participants, and 77% started appropriate anticoagulant therapy.Trial registrationClinicalTrials.gov, no. NCT02262351.

Project description:BackgroundMicroscopic examination is commonly used for malaria diagnosis in the field. However, the lack of well-trained microscopists in malaria-endemic areas impacted the most by the disease is a severe problem. Besides, the examination process is time-consuming and prone to human error. Automated diagnostic systems based on machine learning offer great potential to overcome these problems. This study aims to evaluate Malaria Screener, a smartphone-based application for malaria diagnosis.MethodsA total of 190 patients were recruited at two sites in rural areas near Khartoum, Sudan. The Malaria Screener mobile application was deployed to screen Giemsa-stained blood smears. Both expert microscopy and nested PCR were performed to use as reference standards. First, Malaria Screener was evaluated using the two reference standards. Then, during post-study experiments, the evaluation was repeated for a newly developed algorithm, PlasmodiumVF-Net.ResultsMalaria Screener reached 74.1% (95% CI 63.5-83.0) accuracy in detecting Plasmodium falciparum malaria using expert microscopy as the reference after a threshold calibration. It reached 71.8% (95% CI 61.0-81.0) accuracy when compared with PCR. The achieved accuracies meet the WHO Level 3 requirement for parasite detection. The processing time for each smear varies from 5 to 15 min, depending on the concentration of white blood cells (WBCs). In the post-study experiment, Malaria Screener reached 91.8% (95% CI 83.8-96.6) accuracy when patient-level results were calculated with a different method. This accuracy meets the WHO Level 1 requirement for parasite detection. In addition, PlasmodiumVF-Net, a newly developed algorithm, reached 83.1% (95% CI 77.0-88.1) accuracy when compared with expert microscopy and 81.0% (95% CI 74.6-86.3) accuracy when compared with PCR, reaching the WHO Level 2 requirement for detecting both Plasmodium falciparum and Plasmodium vivax malaria, without using the testing sites data for training or calibration. Results reported for both Malaria Screener and PlasmodiumVF-Net used thick smears for diagnosis. In this paper, both systems were not assessed in species identification and parasite counting, which are still under development.ConclusionMalaria Screener showed the potential to be deployed in resource-limited areas to facilitate routine malaria screening. It is the first smartphone-based system for malaria diagnosis evaluated on the patient-level in a natural field environment. Thus, the results in the field reported here can serve as a reference for future studies.

Project description:BackgroundAtrial fibrillation (AF) and other arrhythmias are prevalent and often encountered by general practitioners (GPs). In response to the growing prevalence and to assist practitioners in the diagnosis and management of AF, the Cardiac Society of Australia & New Zealand and Heart Foundation of Australia published the first Australian AF Guidelines in 2018. We aimed to examine (a) the proportion of GPs who performed any form of AF screening and identify the methods they applied, (b) GPs' awareness of the AF Guidelines and approaches to arrhythmia screening, (c) the roles of conventional 12-lead ECG and mobile health devices, and (d) GPs' confidence in ECG interpretation and need for training.MethodsA cross-sectional online survey titled "GPs Screen their patients for Atrial Fibrillation and othEr aRrhythmia (GPSAFER)" was conducted from October 2018 to March 2019. The participants were recruited via various GP networks across Australia. Ethics approval was granted by The University of Sydney.ResultsA total of 463 surveys were completed. Many GPs (394/463, 85.1%, 95% CI 81.5-88.2%) performed some forms of AF screening and applied at least one AF screening method, most frequently pulse palpation (389/463, 84.0%). Some (299/463, 64.6%) GPs considered assessing their patients for other arrhythmias (237/299, 79.3% for complete heart block and 236/299, 78.9% for long-QT). Most GPs (424/463, 91.6%) were not using mobile ECG devices in their practice but some (147/463, 31.7%) were contemplating it. One third (175/463, 37.8%) of GPs were aware of the Australian AF Guidelines; those aware were more likely to perform AF screening (98.9% vs 76.7%, p < 0.001). Factors significantly and positively associated with AF screening were "awareness of the AF Guidelines" (p < 0.001), "number of years working in general practice" (p < 0.001), and "confidence in ECG interpretation of AF" (p = 0.003). Most GPs reported that they were very or extremely confident in interpreting AF (381/463, 82.3%) and complete heart block (266/463, 57.5%). Many GPs (349/463, 75.4%) would like to receive online ECG interpretation training.ConclusionsAssessment of arrhythmias is common in general practice and GPs are open to further training in ECG interpretation and using mobile ECG devices to aid their clinical practice. Increasing awareness of AF Guidelines and improving confidence in ECG interpretation may increase AF screening.

Dataset Information

Diagnostic Performance of a Smartphone-Based Photoplethysmographic Application for Atrial Fibrillation Screening in a Primary Care Setting.

Background

Methods and results

Conclusions

Publications

Diagnostic Performance of a Smartphone-Based Photoplethysmographic Application for Atrial Fibrillation Screening in a Primary Care Setting.

Similar Datasets

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