Efficacy of telemedicine for the management of cardiovascular disease: a systematic review and meta-analysis

Kuan, Pei Xuan; Chan, Weng Ken; Ying, Denisa Khoo Fern; Aizuddin, Abdul Rahman, Mohd; Peariasamy, Kalaiarasu M; Lai, Nai Ming; Mills, Nicholas L.; Anand, Atul

doi:10.1016/s2589-7500(22)00124-8

Cited by 78 publications

(35 citation statements)

References 61 publications

(38 reference statements)

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“…This study discovered that ICT interventions were better than those that did not allow for such adjustments in terms of improved blood glucose control, especially HbA1c levels. Various ICT interventions were examined, ranging from simple messages offering general patient care recommendations using telemedicine, mobile apps, and video conferences with nurse case managers, to more comprehensive interventions remotely monitoring blood pressure and glucose with electronic data 19 …”

Section: Discussionmentioning

confidence: 99%

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Efficacy of information and communication technology interventions for the management of diabetes mellitus: An umbrella review and evidence map

Park,

Lee,

Cho

et al. 2024

Obesity Reviews

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SummaryIntroductionWe validated the quality of evidence and potential benefits of information and communication technology interventions on diabetes‐related health outcomes.MethodsWe systematically searched PubMed/MEDLINE, Embase, Google Scholar, and CINAHL and manually searched the reference lists of the retrieved review articles from each database's inception to October 2022. Randomized controlled trials were included to determine the benefits of information and communication technology interventions on diabetes outcomes.ResultsTen meta‐analyses of randomized controlled trials were included, with 37 unique outcomes encompassing 379 studies and >70,000 participants across 47 countries and six continents. Information and communication technology intervention was associated with reduced HbA1c levels in patients with type 1 (moderate certainty), type 2 (moderate certainty), and gestational diabetes (low certainty) and showed potential benefits for type 2 diabetes, demonstrating a reduction in systolic blood pressure (high certainty), low‐density lipoprotein cholesterol (low certainty), and body weight (low certainty), whereas those for gestational diabetes demonstrated a reduction in fasting (low certainty) and 2‐h postprandial blood glucose levels (low certainty).ConclusionThis umbrella review and evidence map revealed varying evidence on the potential benefits of information and communication technology interventions for diabetes‐related outcomes. Our results demonstrate these interventions to be novel treatment options for policymakers and physicians to establish personalized health strategies.

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Section: Discussionmentioning

confidence: 99%

“…were examined, ranging from simple messages offering general patient care recommendations using telemedicine, mobile apps, and video conferences with nurse case managers, to more comprehensive interventions remotely monitoring blood pressure and glucose with electronic data. 19…”

Section: Plausible Mechanismmentioning

confidence: 99%

Efficacy of information and communication technology interventions for the management of diabetes mellitus: An umbrella review and evidence map

Park,

Lee,

Cho

et al. 2024

Obesity Reviews

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“…Indeed, the combined use of remote monitoring devices, blood tests that can be self‐administered at home, and artificial intelligence systems to share information between patients and the multidisciplinary care team may have the potential to improve patient monitoring and disease control. 10 , 11 , 12 …”

Section: Discussionmentioning

confidence: 99%

Virtual Outpatient Visits During COVID‐19 Pandemic: So Distant, Yet So Close

Ambrosio

Gensini

Stracci

2023

JAHA

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“…As the need for virtual care with a high adaptability rate, the artificial intelligence (AI) is transforming telemedicine care across the globe. [31][32][33][34][35][36][37][38][39] WellFie rPPG technology with high predictive accuracy can offer an integral link whereby a virtual physician can gain real-time contactless insights on patient clinical data. A systematic review evaluating camera-based vital monitoring found that RGB cameras can reliably monitor HR and RR in a controlled environment [20]; while our study had a comparatively low predictive accuracy for RR, we found a very high predictive accuracy for both systolic and diastolic BP and HR.…”

Section: Percent Errormentioning

confidence: 99%

Accuracy of Smartphone-based Vital Monitoring Using Remote Photoplethysmography Technology Enabled WellFie application

Rajan¹,

Sivapuram

Kumar

et al. 2023

Preprint

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Background: Remote health monitoring technologies gained interest in the context of COVID-19 pandemic with potential for contactless monitoring of clinical patient status. Here, we examined whether vital parameters can be determined in a contactless manner using a novel smartphone-based technology called remote Photoplethysmography (rPPG) and compared with comparable certified medical devices. Methods: We enrolled a total of 150 normotensive adults in this comparative cross-sectional validation study. We used an advanced machine learning algorithm in the WellFie application to create computational models that predict reference systolic, diastolic blood pressure (BP), heart rate (HR), and respiratory rate (RR) from facial blood flow data. This study compared the predictive accuracy of smartphone-based, rPPG-enabled WellFie application with comparable certified medical devices. Results: When compared with reference standards, on average our models predicted systolic blood pressure (BP) with an accuracy of 93.94%, diastolic BP with an accuracy of 92.95%, HR with an accuracy of 97.34%, RR with accuracy of 84.44%. For the WellFie application, the relative mean absolute percentage error (RMAPE) for HR was 2.66%, for RR was 15.66%, for systolic BP was 6.06%, and for diastolic BP was 7.05%. Conclusion: Our results on normotensive adults demonstrates that rPPG technology-enabled Welfie application can determine BP, HR, RR in normotensive participants with an accuracy that is comparable to clinical standards. The Wellfie application with its integrated advanced machine learning algorithm outperformed other approved wearable devices (such as Apple watch, Fitbit charge 2, and Microsoft Band) for HR estimation. WellFie smartphone application based on rPPG technology offers a convenient contactless video-based remote solution that could be used in any modern smartphone.

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Efficacy of telemedicine for the management of cardiovascular disease: a systematic review and meta-analysis

Cited by 78 publications

References 61 publications

Efficacy of information and communication technology interventions for the management of diabetes mellitus: An umbrella review and evidence map

Efficacy of information and communication technology interventions for the management of diabetes mellitus: An umbrella review and evidence map

Virtual Outpatient Visits During COVID‐19 Pandemic: So Distant, Yet So Close

Accuracy of Smartphone-based Vital Monitoring Using Remote Photoplethysmography Technology Enabled WellFie application

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