Completed

NCT Number: NCT05639452

Development of an Early Warning Score for Detecting the Deterioration of a Patients' General Condition in an Acute Hospital

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.

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Key information

Conditions

General Condition

Age range

18 year and older

Sex eligibility

All sexes

Study type

Observational

Primary location

University Hospital Basel, Division of Internal Medicine

Basel, 4031, Switzerland

About this study

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.

Who can participate

Healthy volunteers accepted: No

Only the study team can determine whether someone qualifies for participation.

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

Treatment and study plan

Data collection for developing an algorithm for an Early Warning Score

Other

Data collection of patient parameters (heart rate, respiratory rate, clinical outcomes (death, transfer to intensive care unit, adverse events like sepsis, infection, heart attack))

Primary outcomes

Accuracy of Early Warning Score

Time frame: up to 72 hours after hospital admission

The accuracy of the early warning system in terms of its predictive power is measured by using the respective medical outcomes. Data models are used to create a relationship between the patient parameters (the predictors) and the clinical outcome (Condition stable vs. condition unstable: death, transfer to intensive care unit, heart attack, infection/sepsis, etc.) as a binary response variable (whether a deterioration occurs or not).

Sponsors and collaborators

Lead sponsor

University Hospital, Basel, Switzerland

Other

Collaborators

Innosuisse - Swiss Innovation Agency

Registry information

Official study 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

Important dates

Study start: 2022
Primary completion: 2023
Study completion: 2023
First posted: Dec 6, 2022
Registry last updated: Feb 16, 2024

OpenTrials presents study information sourced from ClinicalTrials.gov. The official registry record should be consulted for the latest information.

View the official ClinicalTrials.gov record (opens in a new tab)

This listing is for discovery and informational purposes only. It is not medical advice, does not guarantee that a study is recruiting, and does not determine eligibility. Contact the study team and a qualified healthcare professional when considering participation.