MedPath

The National Early Warning Score: Preceding Dynamics in the Score for Those Who Suffer an In-hospital Cardiac Arrest

Completed
Conditions
Vital Signs
Rapid Response System
Interventions
Diagnostic Test: NEWS
Registration Number
NCT03143062
Lead Sponsor
Region Skane
Brief Summary

To this date no clinical evaluation reports of the dynamics in the National Early Warning Score (NEWS) for those patients who suffer an in-hospital cardiac arrest, IHCA, exists. This process needs to be investigated in order to optimize the future care of these patients.

Research Questions H1: Patients that suffer an IHCA has had higher NEWS in the preceding 24 hours from the event compared to those who did not suffer an IHCA.

H2: The dynamics in the NEWS, differs between the patients that suffer an IHCA and those who do not in the preceding 24 hours from the event.

Detailed Description

Power:

A sample size of 300 patients in the control group and 150 patients in the group that suffered from an IHCA would generate a power estimate of 80 percent if the difference in the median is one point on the NEWS with a standard deviate of three points.

Analysis of the Research Data:

Categorical and nonparametric data will be presented in median (25-75 percentiles).

A hypothesis testing will be performed where the documented NEWS will be categorized into low-, medium- and high-risk and divided into different timespans. The timespans will be 0-6 h, 6-12 h, 12-18 and 18-24 h preceding the IHCA. In case of multiple NEWS measurements within each timespan, the worst NEWS measurement will be chosen. Each timespan during the 24 hours will not be treated as repeated measures and will be tested by the Chi square test. This test is chosen because the data is categorical. Another hypothesis test where all the NEWS measurements will be included and each documented NEWS on the same patient will be treated as repeated measures. A binary logistic regression analysis will be performed using Generalized Estimating Equations (GEE) and modelled to fit.

In order to select the covariates that is to be included in the regression analysis a non-parametric test including all the parameters in the NEWS will be executed. The level of significance for this test will be set to p=0.2 2. Collinearity within the NEWS parameters that is to be included in the regression analysis will be tested. The level of collinearity that is accepted will be \<+0,6 and \>-0,6. A binomial logistic regression analysis will be executed with the selected parameters in the NEWS The outcome of the regression analysis will be presented as odds ratio (OR).

Recruitment & Eligibility

Status
COMPLETED
Sex
All
Target Recruitment
381
Inclusion Criteria

All patients ≥18 years of age admitted to the hospitals during a period of 12 months will be reviewed for eligibility

Exclusion Criteria

Study & Design

Study Type
OBSERVATIONAL
Study Design
Not specified
Arm && Interventions
GroupInterventionDescription
ControlsNEWS300 patients that did not suffer an in-hospital cardiac arrest but was treated in a hospital ward.
CasesNEWS150 patients that suffered an in-hospital cardiac arrest in a hospital ward.
Primary Outcome Measures
NameTimeMethod
Dynamics in the National Early Warning Score (NEWS) in the 24 hours preceding an in-hospital cardiac arrest.24 hours preceding an in-hospital cardiac arrest

All documented National Early Warning Scores (NEWS) on eligible patients admitted to a hospital ward will be collected. The NEWS will be divided into different timespans in the 24 hours preceding the in-hospital cardiac arrest. A control group of patients will also have their NEWS collected. The NEWS of the control group and the cases will then be entered into the hypothesis testing. The aim is to find some dynamics in the NEWS that separates the patients that suffers an in-hospital cardiac arrest from those who do not in the 24 hours preceding the event.

Secondary Outcome Measures
NameTimeMethod

Trial Locations

Locations (1)

Region Skåne

🇸🇪

Kristianstad, Sweden

© Copyright 2025. All Rights Reserved by MedPath