Predictive and Advanced Analytics in Emergency Medicine - Neurological Deficits (PAN-EM-NEURO)

November 19, 2024 updated by: Jan Niederdöckl, Medical University of Vienna

Future predictive modeling in emergency medicine will likely combine the use of a wide range of data points such as continuous documentation, monitoring using wearables, imaging, biomarkers, and real-time administrative data from all health care providers involved. Subsequent extensive data sets could feed advanced deep learning and neural network algorithms to accurately predict the risk of specific health conditions. Moreover, predictive analytics steers towards the development of clinical pathways that are adaptive and continuously updated, and in which healthcare decision-making is supported by sophisticated algorithms to provide the best course of action effectively and safely. The potential for predictive analytics to revolutionize many aspects of healthcare seems clear in the horizon. Information on the use in emergency medicine is scarce.

Aim of the study is to evaluate the performance of using routine-data to predict resource usage in emergency medicine using the commonly encountered symptom of acute neurologic deficit. As an outlook, this might serve as a prototype for other, similar projects using routine medical data for predictive analytics in emergency medicine.

Study Overview

Status

Recruiting

Conditions

Study Type

Observational

Enrollment (Estimated)

50000

Contacts and Locations

This section provides the contact details for those conducting the study, and information on where this study is being conducted.

Study Contact

Study Locations

Participation Criteria

Researchers look for people who fit a certain description, called eligibility criteria. Some examples of these criteria are a person's general health condition or prior treatments.

Eligibility Criteria

Ages Eligible for Study

  • Adult
  • Older Adult

Accepts Healthy Volunteers

No

Sampling Method

Non-Probability Sample

Study Population

Retrospective analysis of routinely collected data. We aim to find data patterns associated with in-hospital resource utilization of patients hospitalized by emergency medical services for suspected acute neurologic deficit.

We will use only information from the routine electronic medical documentation system for this study. No linkage to other datasets will be performed. Data in the system includes patient demographics, initial symptoms, prehospital vital signs and scores, suspected diagnosis by emergency medical services, inhospital vital signs and scores, inhospital diagnostic (computed tomography CT, magnetic resonance imaging MRI) and therapeutic (catheter intervention) procedures and final diagnosis. See 'variables' for a full set of variables.

For the purpose of this study, only a fully pseudonomyzed dataset will be used.

Description

Inclusion Criteria:

  • Female and Male subjects
  • Age ≥ 18 years

Exclusion Criteria:

- none

Study Plan

This section provides details of the study plan, including how the study is designed and what the study is measuring.

How is the study designed?

Design Details

What is the study measuring?

Primary Outcome Measures

Outcome Measure
Measure Description
Time Frame
Prediction model
Time Frame: 1.1.2025
to be developed
1.1.2025

Collaborators and Investigators

This is where you will find people and organizations involved with this study.

Sponsor

Medical University of Vienna

Publications and helpful links

The person responsible for entering information about the study voluntarily provides these publications. These may be about anything related to the study.

General Publications

Study record dates

These dates track the progress of study record and summary results submissions to ClinicalTrials.gov. Study records and reported results are reviewed by the National Library of Medicine (NLM) to make sure they meet specific quality control standards before being posted on the public website.

Study Major Dates

Study Start (Actual)

January 1, 2022

Primary Completion (Estimated)

January 1, 2025

Study Completion (Estimated)

January 1, 2030

Study Registration Dates

First Submitted

January 30, 2024

First Submitted That Met QC Criteria

January 30, 2024

First Posted (Actual)

February 7, 2024

Study Record Updates

Last Update Posted (Estimated)

November 22, 2024

Last Update Submitted That Met QC Criteria

November 19, 2024

Last Verified

November 1, 2024

More Information

Terms related to this study

Additional Relevant MeSH Terms

Other Study ID Numbers

  • EK- Nr. 1738/2022

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

This information was retrieved directly from the website clinicaltrials.gov without any changes. If you have any requests to change, remove or update your study details, please contact register@clinicaltrials.gov. As soon as a change is implemented on clinicaltrials.gov, this will be updated automatically on our website as well.

Clinical Trials on Neurologic Manifestations

Search Similar Trials

Sponsors and Collaborators

Medical Conditions

Drug Interventions

CROs by country

CROs in Cambodia

Conditions

Rare Diseases

Drug Interventions

Dietary Supplements

Sponsor/Collaborators

Locations

Subscribe