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Aim: To evaluate the use of a single-lead electrocardiography (1L-ECG) device and digital cardiologist consultation platform in diagnosing arrhythmias among general practitioners (GPs)., Background: Handheld 1L-ECG offers a user-friendly alternative to conventional 12-lead ECG in primary care. While GPs can safely rule out arrhythmias on 1L-ECG recordings, expert consultation is required to confirm suspected arrhythmias. Little is known about GPs' experiences with both a 1L-ECG device and digital consultation platform for daily practice., Methods: We used two distinct methods in this study. First, in an observational study, we collected and described all cases shared by GPs within a digital cardiologist consultation platform initiated by a local GP cooperative. This GP cooperative distributed KardiaMobile 1L-ECG devices among all affiliated GPs ( n = 203) and invited them to this consultation platform. In the second part, we used an online questionnaire to evaluate the experiences of these GPs using the KardiaMobile and consultation platform., Findings: In total, 98 (48%) GPs participated in this project, of whom 48 (49%) shared 156 cases. The expert panel was able to provide a definitive rhythm interpretation in 130 (83.3%) shared cases and answered in a median of 4 min (IQR: 2-18). GPs responding to the questionnaire ( n = 43; 44%) thought the KardiaMobile was of added value for rhythm diagnostics in primary care ( n = 42; 98%) and easy to use ( n = 41; 95%). Most GPs ( n = 36; 84%) valued the feedback from the cardiologists in the consultation platform. GPs experienced this project to have a positive impact on both the quality of care and diagnostic efficiency for patients with (suspected) cardiac arrhythmias. Although we lack a comprehensive picture of experienced impediments by GPs, solving technical issues was mentioned to be helpful for further implementation. More research is needed to explore reasons of GPs not motivated using these tools and to assess real-life clinical impact.

Background: Atrial fibrillation (AF) is a common cardiac arrhythmia with a lifetime risk of one in 4. Unfortunately, AF often remains undetected, particularly when it is paroxysmal, for which single time-point evaluation is less effective. Recently, unobtrusive cardiac arrhythmia monitoring devices have become available, providing the opportunity to conduct prolonged electrocardiographic (ECG) monitoring in a patient-friendly manner. We hypothesize that applying these devices in at risk patients may improve AF detection, particularly when used during repeated episodes. We therefore aim to evaluate the diagnostic yield of yearly screening for atrial fibrillation when using a wearable device for continuous ECG monitoring for 7 days in primary care patients ≥ 65 years deemed at high-risk of AF (CHA 2 DS 2 VASc score ≥3 for men or ≥4 for women) compared with usual care over a study period of 3 years., Methods: Primary care based, cluster-randomized controlled trial with 10 general practices randomized to the intervention group and 10 general practices randomized to control group. In each group, we aim to enroll 930 patients, ≥65 years and a CHA 2 DS 2 VASc score ≥3 for men or ≥ 4 for women. The intervention consists of continuous ECG monitoring for 7 days at start of the study (t = 0), after one (t = 1) and 2 years (t = 2). The control practices will follow usual diagnostic care procedures., Results: Results are expected in 2025., Conclusions: This study differs from previous randomized controlled trials, as it involves longitudinal screening of a risk-stratified population. In case of a beneficial diagnostic yield, the PATCH-AF study will add to the evidence for AF screening., Trial Registration: The PATCH-AF study is registered at The Netherlands Trial Register (NTR number NL9656)., (Copyright © 2022 The Authors. Published by Elsevier Inc. All rights reserved.)

Background: Timely detection of atrial fibrillation (AF) is important because of its increased risk of thrombo-embolic events. Single time point screening interventions fall short in detection of paroxysmal AF, which requires prolonged electrocardiographic monitoring, usually using a Holter. However, traditional 24-48 h Holter monitoring is less appropriate for screening purposes because of its low diagnostic yield. Intermittent, ambulatory screening using a single-lead electrocardiogram (1 L-ECG) device can offer a more efficient alternative., Methods: Primary care patients of ≥65 years participated in an opportunistic screening study for AF. We invited patients with a negative 12 L-ECG to wear a Holter monitor for two weeks and to use a MyDiagnostick 1 L-ECG device thrice daily. We report the yield of paroxysmal AF found by Holter monitoring and calculate the diagnostic accuracy of the 1 L-ECG device's built-in AF detection algorithm with the Holter monitor as reference standard., Results: We included 270 patients, of whom four had AF in a median of 8.0 days of Holter monitoring, a diagnostic yield of 1.5% (95%-CI: 0.4-3.8%). In 205 patients we performed simultaneous 1 L-ECG screening. For diagnosing AF based on the 1 L-ECG device's AF detection algorithm, sensitivity was 66.7% (95%-CI: 9.4-99.2%), specificity 68.8% (95%-CI: 61.9-75.1%), positive predictive value 3.1% (95%-CI: 1.4-6.8%) and negative predictive value 99.3% (95%-CI: 96.6-99.9%)., Conclusion: We found a low diagnostic yield of paroxysmal AF using Holter monitoring in elderly primary care patients with a negative 12 L-ECG. The diagnostic accuracy of an intermittently, ambulatory used MyDiagnostick 1 L-ECG device as interpreted by its built-in AF detection algorithm is limited., (Copyright © 2021 The Author(s). Published by Elsevier B.V. All rights reserved.)

Objective: To determine the accuracy of QT measurement in a smartphone-operated, single-lead ECG (1L-ECG) device (AliveCor KardiaMobile 1L)., Design: Cross-sectional, within-patient diagnostic validation study., Setting/participants: Patients underwent a 12-lead ECG (12L-ECG) for any non-acute indication in primary care, April 2017-July 2018., Intervention: Simultaneous recording of 1L-ECGs and 12L-ECGs with blinded manual QT assessment. OUTCOMES OF INTEREST: (1) Difference in QT interval in milliseconds (ms) between the devices; (2) measurement agreement between the devices (excellent agreement <20 ms and clinically acceptable agreement <40 ms absolute difference); (3) sensitivity and specificity for detection of extreme QTc (short (≤340 ms) or long (≥480 ms)), on 1L-ECGs versus 12L-ECGs as reference standard. In case of significant discrepancy between lead I/II of 12L-ECGs and 1L-ECGs, we developed a correction tool by adding the difference between QT measurements of 12L-ECG and 1L-ECGs., Results: 250 ECGs of 125 patients were included. The mean QTc interval, using Bazett's formula (QTcB), was 393±25 ms (mean±SD) in 1L-ECGs and 392±27 ms in lead I of 12L-ECGs, a mean difference of 1±21 ms, which was not statistically different (paired t-test (p=0.51) and Bland Altman method (p=0.23)). In terms of agreement between 1L-ECGs and lead I, QTcB had excellent agreement in 66.9% and clinically acceptable agreement in 93.4% of observations. The sensitivity and specificity of detecting extreme QTc were 0% and 99.2%, respectively. The comparison of 1L-ECG QTcB with lead II of 12L-ECGs showed a significant difference (p=<0.01), but when using a correction factor (+9 ms) this difference was cancelled (paired t-test (p=0.43) or Bland Altman test (p=0.57)). Moreover, it led to improved rates of excellent (71.3%) and clinically acceptable (94.3%) agreement., Conclusion: Smartphone-operated 1L-ECGs can be used to accurately measure the QTc interval compared with simultaneously obtained 12L-ECGs in a primary care population. This may provide an opportunity for monitoring the effects of potential QTc-prolonging medications., Competing Interests: Competing interests: None declared., (© Author(s) (or their employer(s)) 2021. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ.)

Objectives: To evaluate the performance of direct-to-consumer pulse oximeters under clinical conditions, with arterial blood gas measurement (SaO 2 ) as reference standard., Design: Cross-sectional, validation study., Setting: Intensive care., Participants: Adult patients requiring SaO 2 -monitoring., Interventions: The studied oximeters are top-selling in Europe/USA (AFAC FS10D, AGPTEK FS10C, ANAPULSE ANP 100, Cocobear, Contec CMS50D1, HYLOGY MD-H37, Mommed YM101, PRCMISEMED F4PRO, PULOX PO-200 and Zacurate Pro Series 500 DL). Directly after collection of a SaO 2 blood sample, we obtained pulse oximeter readings (SpO 2 ). SpO 2 -readings were performed in rotating order, blinded for SaO 2 and completed <10 min after blood sample collection., Outcome Measures: Bias (SpO 2 -SaO 2 ) mean, root mean square difference (A RMS ), mean absolute error (MAE) and accuracy in identifying hypoxaemia (SaO 2 ≤90%). As a clinical index test, we included a hospital-grade SpO 2 -monitor (Philips)., Results: In 35 consecutive patients, we obtained 2258 SpO 2 -readings and 234 SaO 2 -samples. Mean bias ranged from -0.6 to -4.8. None of the pulse oximeters met A RMS ≤3%, the requirement set by International Organisation for Standardisation (ISO)-standards and required for Food and Drug Administration (FDA) 501(k)-clearance. The MAE ranged from 2.3 to 5.1, and five out of ten pulse oximeters met the requirement of ≤3%. For hypoxaemia, negative predictive values were 98%-99%. Positive predictive values ranged from 11% to 30%. Highest accuracy (95% CI) was found for Contec CMS50D1; 91% (86-94) and Zacurate Pro Series 500 DL; 90% (85-94). The hospital-grade SpO 2 -monitor had an A RMS of 3.0% and MAE of 1.9, and an accuracy of 95% (91%-97%)., Conclusion: Top-selling, direct-to-consumer pulse oximeters can accurately rule out hypoxaemia, but do not meet ISO-standards required for FDA-clearance., Competing Interests: Competing interests: None declared., (© Author(s) (or their employer(s)) 2021. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ.)

Single‑lead electrocardiograms (1 L-ECGs) are increasingly used in (pre)clinical settings for the detection and monitoring of a range of rhythm and conduction disorders. In this short communication paper, we aim to provide an overview of the usefulness and potential pitfalls when implementing 1 L-ECGs into everyday clinical practice. Moreover, we provide recommendations for improving signal quality, as well as a systematic approach to the interpretation of 1 L-ECGs, which is somewhat different from standard 12‑lead ECGs. Clinicians can use our illustrations and checklist as guidance when recording and interpreting 1 L-ECGs., Competing Interests: Declaration of Competing Interest None., (Copyright © 2021 The Authors. Published by Elsevier Inc. All rights reserved.)

Background: Handheld single-lead electrocardiograms (1L-ECG) present a welcome addition to the diagnostic arsenal of general practitioners (GPs). However, little is known about GPs' 1L-ECG interpretation skills, and thus its reliability in real-world practice., Objective: To determine the diagnostic accuracy of GPs in diagnosing atrial fibrillation or flutter (AF/Afl) based on 1L-ECGs, with and without the aid of automatic algorithm interpretation, as well as other relevant ECG abnormalities., Methods: We invited 2239 Dutch GPs for an online case-vignette study. GPs were asked to interpret four 1L-ECGs, randomly drawn from a pool of 80 case-vignettes. These vignettes were obtained from a primary care study that used smartphone-operated 1L-ECG recordings using the AliveCor KardiaMobile. Interpretation of all 1L-ECGs by a panel of cardiologists was used as reference standard., Results: A total of 457 (20.4%) GPs responded and interpreted a total of 1613 1L-ECGs. Sensitivity and specificity for AF/Afl (prevalence 13%) were 92.5% (95% CI: 82.5-97.0%) and 89.8% (95% CI: 85.5-92.9%), respectively. PPV and NPV for AF/Afl were 45.7% (95% CI: 22.4-70.9%) and 98.8% (95% CI: 97.1-99.5%), respectively. GP interpretation skills did not improve in case-vignettes where the outcome of automatic AF-detection algorithm was provided. In detecting any relevant ECG abnormality (prevalence 22%), sensitivity, specificity, PPV and NPV were 96.3% (95% CI: 92.8-98.2%), 68.8% (95% CI: 62.4-74.6%), 43.9% (95% CI: 27.7-61.5%) and 97.9% (95% CI: 94.9-99.1%), respectively., Conclusions: GPs can safely rule out cardiac arrhythmias with 1L-ECGs. However, whenever an abnormality is suspected, confirmation by an expert-reader is warranted., (© The Author(s) 2020. Published by Oxford University Press.)

Purpose: To validate a smartphone-operated, single-lead electrocardiography (1L-ECG) device (AliveCor KardiaMobile) with an integrated algorithm for atrial fibrillation (AF) against 12-lead ECG (12L-ECG) in a primary care population., Methods: We recruited consecutive patients who underwent 12L-ECG for any nonacute indication. Patients held a smartphone with connected 1L-ECG while local personnel simultaneously performed 12L-ECG. All 1L-ECG recordings were assessed by blinded cardiologists as well as by the smartphone-integrated algorithm. The study cardiologists also assessed all 12L-recordings in random order as the reference standard. We determined the diagnostic accuracy of the 1L-ECG in detecting AF or atrial flutter (AFL) as well as any rhythm abnormality and any conduction abnormality with the simultaneously performed 12L-ECG as the reference standard., Results: We included 214 patients from 10 Dutch general practices. Mean ± SD age was 64.1 ± 14.7 years, and 53.7% of the patients were male. The 12L-ECG diagnosed AF/AFL, any rhythm abnormality, and any conduction abnormality in 23, 44, and 28 patients, respectively. The 1L-ECG as assessed by cardiologists had a sensitivity and specificity for AF/AFL of 100% (95% CI, 85.2%-100%) and 100% (95% CI, 98.1%-100%). The AF detection algorithm had a sensitivity and specificity of 87.0% (95% CI, 66.4%-97.2%) and 97.9% (95% CI, 94.7%-99.4%). The 1L-ECG as assessed by cardiologists had a sensitivity and specificity for any rhythm abnormality of 90.9% (95% CI, 78.3%-97.5%) and 93.5% (95% CI, 88.7%-96.7%) and for any conduction abnormality of 46.4% (95% CI, 27.5%-66.1%) and 100% (95% CI, 98.0%-100%)., Conclusions: In a primary care population, a smartphone-operated, 1L-ECG device showed excellent diagnostic accuracy for AF/AFL and good diagnostic accuracy for other rhythm abnormalities. The 1L-ECG device was less sensitive for conduction abnormalities., (© 2019 Annals of Family Medicine, Inc.)