Inpatient Mortality Prediction Algorithm Clinical Trial (IMPACT)

A Randomized Clinical Trial of a Mortality Prediction Algorithm

Status

Withdrawn

Phases

Study type

Interventional

Source

ClinicalTrials.gov

Registry ID

NCT03212534

Acronym

IMPACT

Enrollment

Registered

2017-07-11

Start date

2017-07-31

Completion date

2017-10-31

Last updated

2021-09-24

For informational purposes only — not medical advice. Sourced from public registries and may not reflect the latest updates. Terms

Conditions

Death, Decompensation, Heart, Decompensation; Heart, Congestive

Keywords

Dascena, patient mortality, machine learning, algorithm, diagnostic

Brief 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.

Interventions

OTHERPatient mortality prediction

Healthcare provider is notified of patient mortality prediction.

Study design

Allocation

RANDOMIZED

Intervention model

PARALLEL

Primary purpose

DIAGNOSTIC

Masking

NONE

Eligibility

Sex/Gender

ALL

Age

18 Years to No maximum

Healthy volunteers

Inclusion criteria

* All adult patients admitted to the participating units will be eligible.

Exclusion criteria

* All patients younger than 18 years of age will be excluded.

Design outcomes

Primary

Measure	Time frame
In-hospital mortality	Through study completion, an average of 30 days

Secondary

Measure	Time frame
Hospital length of stay	Through study completion, an average of 30 days

Other

Measure	Time frame
Hospital readmission	Through study completion, an average of 30 days
ICU length of stay	Through study completion, an average of 30 days

Countries

United States

Outcome results

None listed

Source: ClinicalTrials.gov · Data processed: Feb 4, 2026