Comparing an Automated to a Conventional Sepsis Clinical Prediction Rule

The recruitment status of this study is unknown because the information has not been verified recently.
Verified January 2012 by Beth Israel Deaconess Medical Center.
Recruitment status was  Not yet recruiting
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
Choosing to participate in a study is an important personal decision. Talk with your doctor and family members or friends about deciding to join a study. To learn more about this study, you or your doctor may contact the study research staff using the Contacts provided below. For general information, see Learn About Clinical Studies.

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 July 22, 2014