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Inpatient Mortality Prediction Algorithm Clinical Trial (IMPACT)

NCT03212534 · Status: WITHDRAWN · Phase: NA · Type: INTERVENTIONAL

Last updated 2021-09-24

No results posted yet for this study

Summary

Through the mapping of retrospective patient data into a discrete multidimensional space, a novel algorithm for homeostatic analysis, was built to make outcome predictions. In this prospective study, the ability of the algorithm to predict patient mortality and influence clinical outcomes, will be investigated.

Conditions

  • Decompensation, Heart
  • Decompensation; Heart, Congestive
  • Death

Interventions

OTHER

Patient mortality prediction

Healthcare provider is notified of patient mortality prediction.

Sponsors & Collaborators

Principal Investigators

  • David Shimabukuro · University of California, San Francisco

Study Design

Allocation
RANDOMIZED
Purpose
DIAGNOSTIC
Masking
NONE
Model
PARALLEL

Eligibility

Min Age
18 Years
Sex
ALL
Healthy Volunteers
No

Timeline & Regulatory

Start
2017-07-31
Primary Completion
2017-10-31
Completion
2017-10-31

Countries

  • United States

Study Locations

More Related Trials

Entities

Companies

Read the full study record

This page highlights key information. For complete eligibility criteria, study locations, investigator contacts, and the full protocol, visit the original record on ClinicalTrials.gov.

View NCT03212534 on ClinicalTrials.gov