Comparing an Automated to a Conventional Sepsis Clinical Prediction Rule

This study is not yet open for participant recruitment.
Verified January 2012 by Beth Israel Deaconess Medical Center
Sponsor:
Collaborators:
New York University
Information provided by (Responsible Party):
Beth Israel Deaconess Medical Center
ClinicalTrials.gov Identifier:
NCT01505478
First received: January 4, 2012
Last updated: January 10, 2012
Last verified: January 2012
  Purpose

The investigators will conduct a prospective cohort study to compare an automated sepsis severity score to a conventional clinical prediction rule to risk stratify patients admitted from the emergency department (ED) with suspected infection for 28 day in-hospital mortality.


Condition
Sepsis

Study Type: Observational
Study Design: Observational Model: Cohort
Time Perspective: Prospective
Official Title: Comparing an Automated to a Conventional Sepsis Clinical Prediction Rule

Resource links provided by NLM:


Further study details as provided by Beth Israel Deaconess Medical Center:

Primary Outcome Measures:
  • 28 day in-hospital mortality
    The primary endpoint is the AUC of a model to predict 28 day all cause in-hospital mortality. Patients discharged or transferred to another hospital before 28 days will be assumed to be alive at 28 days.


Secondary Outcome Measures:
  • ICU Admission
    The secondary endpoint is ICU admission from the ED or within 24 hours from the floor.


Estimated Enrollment: 2100
Study Start Date: July 2012
Groups/Cohorts
Patients admitted with infection
All consecutive ED patients during the study period that have been admitted and identified to have a suspected infection at ED disposition using a data collection tool

  Eligibility

Ages Eligible for Study:   18 Years and older
Genders Eligible for Study:   Both
Accepts Healthy Volunteers:   No
Sampling Method:   Non-Probability Sample
Study Population

Patients admitted from the Emergency Department with suspected infection.

Criteria

Inclusion Criteria:

  • All consecutive adult (age 18 or older) Emergency Department (ED) patients during the study period that have been admitted from the ED and identified by the treating clinician to have a suspected infection at the time of ED disposition will comprise our study population.

Exclusion Criteria:

  • No patients will be excluded from the study.
  Contacts and Locations
Please refer to this study by its ClinicalTrials.gov identifier: NCT01505478

Contacts
Contact: Steven Horng, MD shorng@bidmc.harvard.edu

Locations
United States, Massachusetts
Beth Israel Deaconess Medical Center
Boston, Massachusetts, United States, 02215
Sponsors and Collaborators
Beth Israel Deaconess Medical Center
New York University
Investigators
Principal Investigator: Steven Horng, MD Beth Israel Deaconess Medical Center
  More Information

No publications provided

Responsible Party: Beth Israel Deaconess Medical Center
ClinicalTrials.gov Identifier: NCT01505478     History of Changes
Other Study ID Numbers: 2011P-000356
Study First Received: January 4, 2012
Last Updated: January 10, 2012
Health Authority: United States: Institutional Review Board
United States: Federal Government

Keywords provided by Beth Israel Deaconess Medical Center:
Sepsis
Clinical Prediction Rule
Clinical Informatics
Machine Learning

Additional relevant MeSH terms:
Sepsis
Toxemia
Infection
Systemic Inflammatory Response Syndrome
Inflammation
Pathologic Processes

ClinicalTrials.gov processed this record on May 23, 2013