Vital Signs Monitoring with Wearable Sensors in High-risk Surgical Patients: A Clinical Validation Study

Publication date

2020-03

Authors

Breteler, Martine J.M.ORCID 0000-0001-7342-0741
KleinJan, Eline J
Dohmen, Daan A J
Leenen, L. P.H.ORCID 0000-0001-8385-1801ISNI 0000000390070047
van Hillegersberg, RichardORCID 0000-0002-7134-261XISNI 0000000387532685
Ruurda, J PORCID 0000-0001-6584-1677ISNI 0000000397120932
van Loon, KimORCID 0000-0002-5225-8746ISNI 0000000393937603
Blokhuis, Taco J.ISNI 0000000387212593
Kalkman, Cor J.ORCID 0000-0002-8372-6960ISNI 0000000390649876

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Article

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taverne

Abstract

BACKGROUND: Vital signs are usually recorded once every 8 h in patients at the hospital ward. Early signs of deterioration may therefore be missed. Wireless sensors have been developed that may capture patient deterioration earlier. The objective of this study was to determine whether two wearable patch sensors (SensiumVitals [Sensium Healthcare Ltd., United Kingdom] and HealthPatch [VitalConnect, USA]), a bed-based system (EarlySense [EarlySense Ltd., Israel]), and a patient-worn monitor (Masimo Radius-7 [Masimo Corporation, USA]) can reliably measure heart rate (HR) and respiratory rate (RR) continuously in patients recovering from major surgery. METHODS: In an observational method comparison study, HR and RR of high-risk surgical patients admitted to a step-down unit were simultaneously recorded with the devices under test and compared with an intensive care unit-grade monitoring system (XPREZZON [Spacelabs Healthcare, USA]) until transition to the ward. Outcome measures were 95% limits of agreement and bias. Clarke Error Grid analysis was performed to assess the ability to assist with correct treatment decisions. In addition, data loss and duration of data gaps were analyzed. RESULTS: Twenty-five high-risk surgical patients were included. More than 700 h of data were available for analysis. For HR, bias and limits of agreement were 1.0 (-6.3, 8.4), 1.3 (-0.5, 3.3), -1.4 (-5.1, 2.3), and -0.4 (-4.0, 3.1) for SensiumVitals, HealthPatch, EarlySense, and Masimo, respectively. For RR, these values were -0.8 (-7.4, 5.6), 0.4 (-3.9, 4.7), and 0.2 (-4.7, 4.4) respectively. HealthPatch overestimated RR, with a bias of 4.4 (limits: -4.4 to 13.3) breaths/minute. Data loss from wireless transmission varied from 13% (83 of 633 h) to 34% (122 of 360 h) for RR and 6% (47 of 727 h) to 27% (182 of 664 h) for HR. CONCLUSIONS: All sensors were highly accurate for HR. For RR, the EarlySense, SensiumVitals sensor, and Masimo Radius-7 were reasonably accurate for RR. The accuracy for RR of the HealthPatch sensor was outside acceptable limits. Trend monitoring with wearable sensors could be valuable to timely detect patient deterioration.

Keywords

Taverne, Anesthesiology and Pain Medicine, Journal Article

Citation

Breteler, M J M, KleinJan, E J, Dohmen, D A J, Leenen, L P H, van Hillegersberg, R, Ruurda, J P, van Loon, K, Blokhuis, T J & Kalkman, C J 2020, 'Vital Signs Monitoring with Wearable Sensors in High-risk Surgical Patients : A Clinical Validation Study', Anesthesiology, vol. 132, no. 3, pp. 424-439. https://doi.org/10.1097/ALN.0000000000003029