Prediction of Intrahospital Cardiac Arrest Outcomes (PREDIHCA)

Intrahospital cardiovascular arrest is one of the most common causes of death in hospitalized patients. In contrast to extramural cases of cardiovascular arrest, hospitalized patients often have severe medical conditions that can affect the outcome of resuscitation. Nevertheless, survival rates from resuscitation are better in hospitals than outside, because there is often a rapid start of resuscitation measures and predefined resuscitation standards. Regular CPR training and the availability of defibrillators in all bedside units can also positively influence outcome. Despite these many efforts, survival rates, especially of patients with good neurological outcome, remained stable at low levels even within hospitals in recent years and did not improve.

Most outcome parameters are nowadays well known. (e.g., initial rhythm, age, early defibrillation, etc.) Nevertheless, we still do not know today how relevant the corresponding factors actually are, especially in relation to each other. One approach to this might be machine learning methods such as "random forest", which might be able to create a predictive model. However, this has not been attempted to date.

The hypothesis of this work is to find out if it is possible to accurately predict the probability of surviving an in-hospital resuscitation using the machine learning method "random forest" and if particularly relevant outcome parameters can be identified.

Design: retrospective data analysis of all data sets recorded in the resuscitation register of Kepler University Hospital.

Measures and Procedure: Review of the registry for missing data as well as false alarms of the CPR team and, if necessary, exclusion of these data sets; evaluation of the data sets using the machine learning method random forest.

Study Overview

• Status: Completed
• Conditions: Cardiac Arrest
• Intervention / Treatment: Diagnostic test: CPC

• Study Type: Observational
• Enrollment (Actual): 668

Contacts and Locations

Study Locations

• Austria
  • Upper Austria
    • Linz, Upper Austria, Austria, 4021
      • Kepler University Hospital

Participation Criteria

Eligibility Criteria

• Ages Eligible for Study: Adult; Older Adult
• Accepts Healthy Volunteers: N/A

• Sampling Method: Non-Probability Sample

Study Population

As described in the inclusion criteria.

Description

Inclusion Criteria:

• All adults patients suffering cardiac arrest and having been resuscitated by the medical emergency team of the Kepler University Hospital, Linz, Austria in the period of 2006-01-01 to 2018-10-31.

Exclusion Criteria:

• None.

Study Plan

How is the study designed?

Number of groups / cohorts

2

Cohorts and Interventions

Group / Cohort	Intervention / Treatment
Outcome CPC Positive	Diagnostic test: CPC; CPC
Outcome CPC Negative	Diagnostic test: CPC; CPC

What is the study measuring?

Primary Outcome Measures

Outcome Measure	Measure Description	Time Frame
AUROC for Classification of Outcome CPC	AUROC for Classification of Outcome CPC	2006-01-01 to 2018-12-31

Secondary Outcome Measures

Outcome Measure	Measure Description	Time Frame
Confusion Matrix	Confusion Matrix Results: true positives, true negatives, false positive, false negatives and values calculated from these results.	2006-01-01 to 2018-12-31
Descriptive Statistics	Descriptive Statistics (age in years, delay in seconds, gender as male/female, agonal breathing/initial rhythm/airway management/iv-access/witnessed cardiac arrest/use of AED/chest compressions as binary features) This outcome measure will compare the individual feature (e. g. height in cm) in one group vs. the other. Significant difference will be described by p-value.	2006-01-01 to 2018-12-31

Collaborators and Investigators

• Sponsor: Kepler University Hospital
• Investigators: Principal Investigator: Thomas Tschoellitsch, MD, Kepler University Hospital and Johannes Kepler University, Linz, Austria

Study record dates

Study Major Dates

• Study Start (Actual): June 1, 2022
• Primary Completion (Actual): July 31, 2022
• Study Completion (Actual): July 31, 2022

Study Registration Dates

• First Submitted: July 12, 2022
• First Submitted That Met QC Criteria: July 17, 2022
• First Posted (Actual): July 20, 2022

Study Record Updates

• Last Update Posted (Actual): May 3, 2023
• Last Update Submitted That Met QC Criteria: April 29, 2023
• Last Verified: April 1, 2023

More Information

Terms related to this study

• Additional Relevant MeSH Terms: Heart Diseases; Cardiovascular Diseases; Heart Arrest
• Other Study ID Numbers: PREDIHCA

Plan for Individual participant data (IPD)

• Plan to Share Individual Participant Data (IPD)?: NO

Drug and device information, study documents

• Studies a U.S. FDA-regulated drug product: No
• Studies a U.S. FDA-regulated device product: No