Clinical trial NCT05639452: Development of an Early Warning Score for Detecting the Deterioration of a Patients' General Condition in an Acute Hospital
Official title: Investigator-initiated, Retrospective, Single-center Study for the Development of an Early Warning Score for Detecting the Deterioration of a Patients' General Condition in an Acute Hospital
Study type: OBSERVATIONAL
Overall status: COMPLETED
Conditions: General Condition
Keywords: Early Warning Score (EWS)
Deterioration of Patients' General Condition
Lead sponsor: University Hospital, Basel, Switzerland
Sponsor class: OTHER
Collaborators: name: Innosuisse - Swiss Innovation Agency
First posted: 2022-12-06
Enrollment: 210
Sex: ALL
Minimum age (years): 18
Standard ages: ADULT
OLDER_ADULT
Accepts healthy volunteers: no
Observational model: COHORT
Time perspective: RETROSPECTIVE
Sampling method: PROBABILITY_SAMPLE
Study population: Patients hospitalized in 2016-2022 in the surgical and medical wards of the University Hospital Basel

Brief summary: An acute deterioration of a patients' general condition is often preceded by changes in individual vital parameters. An early warning system (EWS) shall be developed with a reduced number of physiological and individual parameters, compared to conventional early warning systems; and an algorithm will be generated that is able to predict clinical deterioration. Its predictive power and accuracy shall be investigated. In a second exploratory phase, different model variants will be analyzed and the applicability of the model variants in the context of continuous EWS on wearables will be examined.

Detailed description: An acute deterioration of a patients' general condition is often preceded by changes in individual vital parameters and may lead to adverse events, such as admission to the intensive care unit, heart attack or death. Some of them are potentially avoidable if appropriate measures are taken in a timely manner. Therefore early warning systems (Early Warning Scores= EWS) have been developed from a set of several physiological measurements, signs and symptoms. Individual parameters are weighted to sum up a score.

Based on this score, the deterioration of a patients' general condition may be indicated and a predetermined reaction from the professional staff be triggered (so-called track-and-trigger system). It is important to determine all parameters since missing values influence the informative value of an EWS. This requires a higher effort by the staff and is one of the reasons why early warning systems are not yet used systematically in Switzerland.

A reduction in the number of parameters to be measured could lower the hurdle for the use of these tools and enable a broader applicability. Therefore an early warning system shall be developed with a reduced number of physiological and individual parameters, compared to conventional early warning systems; and an algorithm will be generated that is able to predict clinical deterioration. Its predictive power and accuracy shall be investigated, based on various clinical outcomes such as mortality, cardiac arrest, transfer to the intensive care unit or sepsis. Retrospective, encrypted patient data (from 2016 until 2022) will be used to develop a statistical prediction model. In a second exploratory phase, different model variants will be analyzed and the applicability of the model variants in the context of continuous EWS on wearables will be examined.

Eligibility criteria: Inclusion Criteria:

* Hospitalized patients of surgical and medical wards of University Hospital Basel
* Hospital stay longer than 24 hours
* Signed general consent

Exclusion Criteria:

* Patients admitted directly to the intensive care unit
* Rejection of general consent

Primary outcomes:
measure: Accuracy of Early Warning Score
timeFrame: up to 72 hours after hospital admission
Secondary outcomes:
Other outcomes:
Locations:
city: Basel
country: Switzerland
facility: University Hospital Basel, Division of Internal Medicine
Study officials:
affiliation: University Hospital Basel, Division of Internal Medicine
name: Jens Eckstein, Prof. Dr. med.
role: PRINCIPAL_INVESTIGATOR
References: