Quantifying physiological stability in the general ward using continuous vital signs monitoring: the circadian kernel density estimator

Søren S. Rasmussen*, Katja K. Grønbæk, Jesper Mølgaard, Camilla Haahr-Raunkjær, Christian S. Meyhoff, Eske K. Aasvang, Helge B.D. Sørensen

*Corresponding author af dette arbejde

Publikation: Bidrag til tidsskriftTidsskriftartikelForskningpeer review

3 Citationer (Scopus)
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Abstract

Technological advances seen in recent years have introduced the possibility of changing the way hospitalized patients are monitored by abolishing the traditional track-and-trigger systems and implementing continuous monitoring using wearable biosensors. However, this new monitoring paradigm raise demand for novel ways of analyzing the data streams in real time. The aim of this study was to design a stability index using kernel density estimation (KDE) fitted to observations of physiological stability incorporating the patients’ circadian rhythm. Continuous vital sign data was obtained from two observational studies with 491 postoperative patients and 200 patients with acute exacerbation of chronic obstructive pulmonary disease. We defined physiological stability as the last 24 h prior to discharge. We evaluated the model against periods of eight hours prior to events defined either as severe adverse events (SAE) or as a total score in the early warning score (EWS) protocol of ≥ 6,  ≥ 8, or ≥ 10. The results found good discriminative properties between stable physiology and EWS-events (area under the receiver operating characteristics curve (AUROC): 0.772–0.993), but lower for the SAEs (AUROC: 0.594–0.611). The time of early warning for the EWS events were 2.8–5.5 h and 2.5 h for the SAEs. The results showed that for severe deviations in the vital signs, the circadian KDE model can alert multiple hours prior to deviations being noticed by the staff. Furthermore, the model shows good generalizability to another cohort and could be a simple way of continuously assessing patient deterioration in the general ward.
OriginalsprogEngelsk
TidsskriftJournal of Clinical Monitoring and Computing
Vol/bind37
Sider (fra-til)1607-1617
Antal sider11
ISSN1387-1307
DOI
StatusUdgivet - 2023

Bibliografisk note

Funding Information:
Open access funding provided by Royal Danish Library. The WARD project received core support from the Innovation Fund Denmark (8056-00055B); the Danish Cancer Society (R150-A9865-16-S48); Copenhagen Center for Health Technology (CACHET); Radiometer Medical Aps; Isansys Ltd; A.P. Møller Foundation, Bispebjerg Hospital, Rigshospitalet and the Technical University of Denmark. No sponsor had any role in the study design, collection, analysis, and interpretation of data, nor in writing the report or the decision to submit the article. Furthermore, no sponsor had access to the study data.

Publisher Copyright:
© 2023, The Author(s).

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