Remote wireless vital signs monitoring on the ward for early detection of deteriorating patients: A case series

Posthuma, Linda M.; Downey, Candice; Visscher, Maarten J.; Ghazali, Daniel Aiham; Joshi, Meera; Ashrafian, Hutan; Khan, Sadia; Darzi, Ara; Goldstone, J; Preckel, Benedikt

doi:10.1016/j.ijnurstu.2019.103515

Cited by 38 publications

(28 citation statements)

References 32 publications

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“…We demonstrated in this trial a very good correlation with the conventional 24h Holter monitor and the ability of the adhesive patch to capture arrhythmia, pauses, and conduction abnormalities with a comparable accuracy during the recording time. Other devices, already commercialized, have similar efficiency in arrhythmia detection (13)(14)(15). Wireless monitoring has been confirmed as a valuable tool to detect adverse events in high risk patients (14,(16)(17)(18)(19).…”

Section: Discussionmentioning

confidence: 99%

Cardiac Ambulatory Monitoring: New Wireless Device Validated Against Conventional Holter Monitoring in a Case Series

Murali

Brugger

Rincon

et al. 2020

Front. Cardiovasc. Med.

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Background: Cardiac arrhythmias are very common but underdiagnosed due to their transient and asymptomatic nature. An optimization of arrhythmia detection would permit to better treat patients and could substantially reduce morbidity and mortality. The SmartCardia ScaAI wireless patch is a novel CE IIa approved, single-lead electrocardiographic (ECG) ambulatory monitor designed for cardiac arrhythmias detection.Hypothesis: The accuracy of the new SmartCardia wireless patch to detect arrhythmias is comparable to the conventional Holter monitoring.Methods: Patients referred for a suspicion of arrhythmia between February and March 2020 were included in the trial. Simultaneous ambulatory ECG were recorded using a conventional 24-h Holter and the SmartCardia. The primary endpoint was the detection of cardiac arrhythmias over the total wear time of the devices, defined as premature atrial contraction (PAC), supraventricular tachycardia ≥3 beats, premature ventricular contraction (PVC), and ventricular tachycardia ≥3 beats. Conduction abnormalities, pause ≥2 s and atrioventricular block (AVB), were also tracked. McNemar's test was used to compare the matched pairs of data from both devices.Results: A total of 40 patients were included in the trial. Over the total wear time, there was no significant difference between the devices for ventricular and supraventricular arrhythmias detection. Pauses and AVB were equally identified by the two devices in three patients.Conclusion: Over the total wear time, the SmartCardia device showed an accuracy to detect arrhythmia similar to the 24-h Holter monitoring: single-lead, adhesive-patch monitoring might become an interesting alternative to the conventional Holter monitoring.

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Section: Discussionmentioning

confidence: 99%

Cardiac Ambulatory Monitoring: New Wireless Device Validated Against Conventional Holter Monitoring in a Case Series

Murali

Brugger

Rincon

et al. 2020

Front. Cardiovasc. Med.

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“…Remote monitoring systems are only bene cial to the clinical staff if they are easy to use and clinicians understand the potential bene t for patient clinical outcomes [57]. This review is part of a wider phased project, the virtual High Dependency Unit (vHDU) study.…”

Section: Future Researchmentioning

confidence: 99%

What Is the Impact of Ambulatory Vital Sign Monitoring on Deterioration Detection and Related Clinical Outcomes in Hospitalised Patients: a Systematic Review and Meta-analysis.

Areia

Biggs

Santos

et al. 2021

Preprint

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Background: Timely recognition of the deteriorating inpatient remains challenging. Ambulatory monitoring systems (AMS) may augment current monitoring practices. However, there are many challenges to implementation in the hospital environment, and evidence describing the clinical impact of AMS on deterioration detection and patient outcome remains unclear. Objective: To assess the impact of vital signs monitoring on detection of deterioration and related clinical outcomes in hospitalised patients using ambulatory monitoring systems, in comparison with standard care.Methods: A systematic search was conducted in August 2020 using MEDLINE, Embase, CINAHL, Cochrane Database of Systematic Reviews, CENTRAL and Health Technology Assessment databases, as well as grey literature. Studies comparing the use of AMS against standard care for deterioration detection and related clinical outcomes in hospitalised patients were included. Deterioration related outcomes (primary) included unplanned intensive care admissions, rapid response team or cardiac arrest activation, total and major complications rate. Other clinical outcomes (secondary) included in-hospital mortality and hospital length of stay. Exploratory outcomes included alerting system parameters and clinical trial registry information. Results: Of 8706 citations, 10 studies with different designs met the inclusion criteria, of which 7 were included in the meta-analyses. Overall study quality was moderate. The meta-analysis indicated that the AMS, when compared with standard care, was associated with a reduction in intensive care transfers (risk ratio, RR, 0.87; 95% confidence interval, CI, 0.66 to 1.15), rapid response or cardiac arrest team activation (RR, 0.84; 95% CI 0.69 to 1.01), total (RR, 0.77; 95% CI 0.44 to 1.32) and major (RR, 0.55; 95% CI 0.24 to 1.30) complications prevalence. There was also association with reduced mortality (RR, 0.48; 95% CI 0.18 to 1.29) and hospital length of stay (mean difference, MD, -0.09; 95% CI -0.43 to 0.44). However, none were statistically significant.Conclusion: This systematic review indicates that implementation of AMS may have a positive impact on early deterioration detection and associated clinical outcomes, but differing design/quality of available studies and diversity of outcomes measures limits a definite conclusion. Our narrative findings suggested that alarms should be adjusted to minimise false alerts and promote rapid clinical action in response to deterioration.PROSPERO Registration number: CRD42020188633

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“…At present, the more advanced contact vital signal detection methods include Forcecardiography [ 4 ], Seismocardiography [ 5 ], Gyrocardiography [ 6 , 7 ], and Piezoresistive Breathing Sensing System [ 8 , 9 ] with wearable shell for measuring respiration. Advanced noncontact detection equipment includes remote wireless monitoring system [ 10 , 11 ], millimeter-wave radar system [ 12 ] for detecting multiple vital signs, active integrated antenna and envelope detector [ 13 , 14 ], monitoring system integrated into hearing protection device [ 15 ] for detecting heartbeat and pulse, etc. High-frequency millimeter-wave radar has the advantages of small size, low power consumption, and high accuracy [ 16 ].…”

Section: Introductionmentioning

confidence: 99%

Frequency-Modulated Continuous Wave Radar Respiratory Pattern Detection Technology Based on Multifeature

Wang

Dong

Cao

et al. 2021

Journal of Healthcare Engineering

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Respiratory diseases including apnea are often accompanied by abnormal respiratory depth, frequency, and rhythm. If different abnormal respiratory patterns can be detected and recorded, with their depth, frequency, and rhythm analyzed, the detection and diagnosis of respiratory diseases can be achieved. High-frequency millimeter-wave radar (76–81 GHz) has low environmental impact, high accuracy, and small volume, which is more suitable for respiratory signal detection and recognition compared with other contact equipment. In this paper, the experimental platform of frequency-modulated continuous wave (FMCW) radar was built at first, realizing the noncontact measurement of vital signs. Secondly, the energy intensity and threshold of respiration signal during each period were calculated by using the rectangular window, and the accurate judgment of apnea was realized via numerical comparison. Thirdly, the features of respiratory and heart rate signals, the number of peaks and valleys, the difference between peaks and valleys, the average and the standard deviation of normalized short-term energy, and the average and the standard deviation and the minimum of instantaneous frequency, were extracted and analyzed. Finally, support vector machine (SVM) and K-nearest neighbor (KNN) were used to classify the extracted features, and the accuracy was 98.25% and 88.75%, respectively. The classification and recognition of respiratory patterns have been successfully realized.

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Remote wireless vital signs monitoring on the ward for early detection of deteriorating patients: A case series

Cited by 38 publications

References 32 publications

Cardiac Ambulatory Monitoring: New Wireless Device Validated Against Conventional Holter Monitoring in a Case Series

Cardiac Ambulatory Monitoring: New Wireless Device Validated Against Conventional Holter Monitoring in a Case Series

What Is the Impact of Ambulatory Vital Sign Monitoring on Deterioration Detection and Related Clinical Outcomes in Hospitalised Patients: a Systematic Review and Meta-analysis.

Frequency-Modulated Continuous Wave Radar Respiratory Pattern Detection Technology Based on Multifeature

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