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

NCT05639452 | Completed

• 1 other identifier: 2022-01681; am22Eckstein3
• Study Type: observational
• Target: 210
• Locations: 1 country
• Sites: 1

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.

Conditions

General Condition

Keywords

Early Warning Score (EWS); Deterioration of Patients' General Condition

Outcome Measures

Primary Outcomes (1)

• Accuracy of Early Warning Score

  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).

  up to 72 hours after hospital admission

Interventions

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))

Eligibility Criteria

• Age: 18 Years+
• Sex: all
• Healthy Volunteers: No
• Age Groups: Adult (18-64), Older Adult (65+)
• Sampling Method: Probability Sample

Study Population

Patients hospitalized in 2016-2022 in the surgical and medical wards of the University Hospital Basel

You may qualify if:

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

You may not qualify if:

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

Sponsors & Collaborators

• University Hospital, Basel, Switzerland: lead
• Innosuisse - Swiss Innovation Agency: collaborator

Study Sites (1)

University Hospital Basel, Division of Internal Medicine

Basel, 4031, Switzerland

Location

MeSH Terms

Interventions

Data Collection

Intervention Hierarchy (Ancestors)

Epidemiologic Methods; Investigative Techniques; Health Care Evaluation Mechanisms; Quality of Health Care; Health Care Quality, Access, and Evaluation; Public Health; Environment and Public Health

Study Officials

• Jens Eckstein, Prof. Dr. med.

  University Hospital Basel, Division of Internal Medicine

  PRINCIPAL INVESTIGATOR

Study Design

• Study Type: observational
• Observational Model: COHORT
• Time Perspective: RETROSPECTIVE
• Sponsor Type: OTHER
• Responsible Party: SPONSOR

Study Record Dates

• First Submitted: November 28, 2022
• First Posted: December 6, 2022
• Study Start: October 5, 2022
• Primary Completion: October 31, 2023
• Study Completion: October 31, 2023
• Last Updated: February 16, 2024

Record last verified: 2024-02

Locations

CH (1)