Evidence map›Paper›PMID 37647104›Full record

ArticleJMIR perioperative medicine2023

Early Warning Scores to Support Continuous Wireless Vital Sign Monitoring for Complication Prediction in Patients on Surgical Wards: Retrospective Observational Study.

Mathilde C van Rossum, Robin E M Bekhuis, Ying Wang, Johannes H Hegeman, Ellis C Folbert, Miriam M R Vollenbroek-Hutten, Cornelis J Kalkman, Ewout A Kouwenhoven, Hermie J Hermens

Open access · diamondAbstract read
In one paragraph

Article in JMIR perioperative medicine, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
2.9field-weighted citation impact, top 9% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

4 citing papers in PubMed, 9 citations in OpenAlex.

  1. Exploring Collaboration Breakdowns Between Provider Teams and Patients in Post-Surgery Care.Proceedings of the SIGCHI conference on human factors in computing systems. CHI Conference · 2026
    Article
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  4. Observational
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

9 authors at 3 institutions in 1 country.

Mathilde C van RossumDepartment of Biomedical Signals and Systems, University of Twente, Enschede, Netherlands.ORCID https://orcid.org/0000-0002-1144-3793
Robin E M BekhuisDepartment of Surgery, Hospital Group Twente, Almelo, Netherlands.ORCID https://orcid.org/0000-0003-4109-0404
Ying WangDepartment of Biomedical Signals and Systems, University of Twente, Enschede, Netherlands.ORCID https://orcid.org/0000-0003-4385-9117
Johannes H HegemanDepartment of Surgery, Hospital Group Twente, Almelo, Netherlands.ORCID https://orcid.org/0000-0003-2188-2738
Ellis C FolbertDepartment of Surgery, Hospital Group Twente, Almelo, Netherlands.ORCID https://orcid.org/0000-0003-4865-0865
Miriam M R Vollenbroek-HuttenDepartment of Biomedical Signals and Systems, University of Twente, Enschede, Netherlands.ORCID https://orcid.org/0000-0001-8730-1487
Cornelis J KalkmanDepartment of Anesthesiology, University Medical Center Utrecht, Utrecht, Netherlands.ORCID https://orcid.org/0000-0002-8372-6960
Ewout A Kouwenhoven *Department of Surgery, Hospital Group Twente, Almelo, Netherlands.ORCID https://orcid.org/0000-0001-8986-9076
Hermie J Hermens *Department of Biomedical Signals and Systems, University of Twente, Enschede, Netherlands.ORCID https://orcid.org/0000-0002-3065-3876
Ziekenhuis Groep Twente · NLUniversity of Twente · NLUniversity Medical Center Utrecht · NL

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundWireless vital sign sensors are increasingly being used to monitor patients on surgical wards. Although early warning scores (EWSs) are the current standard for the identification of patient deterioration in a ward setting, their usefulness for continuous monitoring is unknown.

objectiveThis study aimed to explore the usability and predictive value of high-rate EWSs obtained from continuous vital sign recordings for early identification of postoperative complications and compares the performance of a sensor-based EWS alarm system with manual intermittent EWS measurements and threshold alarms applied to individual vital sign recordings (single-parameter alarms).

methodsContinuous vital sign measurements (heart rate, respiratory rate, blood oxygen saturation, and axillary temperature) collected with wireless sensors in patients on surgical wards were used for retrospective simulation of EWSs (sensor EWSs) for different time windows (1-240 min), adopting criteria similar to EWSs based on manual vital signs measurements (nurse EWSs). Hourly sensor EWS measurements were compared between patients with (event group: 14/46, 30%) and without (control group: 32/46, 70%) postoperative complications. In addition, alarms were simulated for the sensor EWSs using a range of alarm thresholds (1-9) and compared with alarms based on nurse EWSs and single-parameter alarms. Alarm performance was evaluated using the sensitivity to predict complications within 24 hours, daily alarm rate, and false discovery rate (FDR).

resultsThe hourly sensor EWSs of the event group (median 3.4, IQR 3.1-4.1) was significantly higher (P<.004) compared with the control group (median 2.8, IQR 2.4-3.2). The alarm sensitivity of the hourly sensor EWSs was the highest (80%-67%) for thresholds of 3 to 5, which was associated with alarm rates of 2 (FDR=85%) to 1.2 (FDR=83%) alarms per patient per day respectively. The sensitivity of sensor EWS-based alarms was higher than that of nurse EWS-based alarms (maximum=40%) but lower than that of single-parameter alarms (87%) for all thresholds. In contrast, the (false) alarm rates of sensor EWS-based alarms were higher than that of nurse EWS-based alarms (maximum=0.6 alarm/patient/d; FDR=80%) but lower than that of single-parameter alarms (2 alarms/patient/d; FDR=84%) for most thresholds. Alarm rates for sensor EWSs increased for shorter time windows, reaching 70 alarms per patient per day when calculated every minute.

conclusionsEWSs obtained using wireless vital sign sensors may contribute to the early recognition of postoperative complications in a ward setting, with higher alarm sensitivity compared with manual EWS measurements. Although hourly sensor EWSs provide fewer alarms compared with single-parameter alarms, high false alarm rates can be expected when calculated over shorter time spans. Further studies are recommended to optimize care escalation criteria for continuous monitoring of vital signs in a ward setting and to evaluate the effects on patient outcomes.

Indexed as

clinical alarmsearly warning scoresperioperative nursingphysiological monitoringpostoperative complicationstelemedicinevital signs

Identifiers

PMID37647104
PMCPMC10500362
OpenAlexW4383504684

What OpenQuestion holds

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LicenceCC BY
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Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.