An Observational Study to Identify New Health Problems Arising After an Intensive Care Unit Admission in People With Acute Respiratory Distress Syndrome in the United States

NCT ID: NCT06272942

Last Updated: 2025-08-29

Study Results

Results pending

The study team has not published outcome measurements, participant flow, or safety data for this trial yet. Check back later for updates.

Basic Information

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Recruitment Status

ACTIVE_NOT_RECRUITING

Total Enrollment

140000 participants

Study Classification

OBSERVATIONAL

Study Start Date

2024-01-31

Study Completion Date

2025-08-30

Brief Summary

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This is an observational study in which data already collected from people with acute respiratory distress syndrome (ARDS) admitted to an intensive care unit (ICU) are studied.

ARDS is a life-threatening condition in which fluid builds up in the lungs making breathing difficult.

In observational studies, only observations are made without participants receiving any advice or any changes to health care.

People who are admitted to ICU for serious illnesses, like ARDS, often experience new health problems during and after their ICU stays. These health problems that may include physical, mental, and/or emotional disorders, are called post-intensive care syndrome (PICS). Identifying these new health problems early can help people by timely treatments and care.

In this study, researchers want to identify any health problems that arise after ICU admission in people with ARDS in the United States (US). To do this, researchers will collect information on health problems, treatments, medicines, and healthcare visits in people with ARDS, 1 year before and after an ICU admission.

They will then look to see whether the health problems are in areas that have been described as the post intensive care syndrome (PICS).

In addition, they will measure healthcare related costs in the one year after admission and compare it to the one year prior to admission.

Researchers will also compare this information with data collected for people with pneumonia who did not require ICU admission. This will help them to identify any new health problems arising due to ICU stays.

The data will come from participants' medical claims information stored in the Optum Clinformatics Data Mart database from 2016 to 2022. The claims data will only be collected for people in the US.

Researchers will collect data from participants admitted to ICU for ARDS for a maximum of 1 year before and after their stay.

Detailed Description

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Conditions

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Acute Respiratory Distress Syndrome (ARDS) Post Intensive Care Syndrome (PICS)

Study Design

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Observational Model Type

COHORT

Study Time Perspective

RETROSPECTIVE

Study Groups

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Post intensive care unit (ICU) morbidity

All adult patients in Optum Claims data from January 1, 2016 until October 1, 2022.

An ICU admission and a temporally related ARDS diagnosis

Intervention Type OTHER

This is a disease study to learn more about the morbidity after an ICU admission and a temporally related ARDS diagnosis.

ARDS stands for acute respiratory distress syndrome.

Interventions

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An ICU admission and a temporally related ARDS diagnosis

This is a disease study to learn more about the morbidity after an ICU admission and a temporally related ARDS diagnosis.

ARDS stands for acute respiratory distress syndrome.

Intervention Type OTHER

Eligibility Criteria

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Inclusion Criteria

* continuous coverage of at least 365 days (\>= 1 year) pre-index date for the cohort
* age \>= 18 years
* not seen outside the healthcare system

Exclusion Criteria

* none
Minimum Eligible Age

18 Years

Eligible Sex

ALL

Accepts Healthy Volunteers

No

Sponsors

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Bayer

INDUSTRY

Sponsor Role lead

Responsible Party

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Responsibility Role SPONSOR

Locations

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Bayer

Whippany, New Jersey, United States

Site Status

Countries

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United States

Related Links

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https://clinicaltrials.bayer.com/

Click here for access to information about Bayer's transparency standards and Bayer studies.

Other Identifiers

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22722

Identifier Type: -

Identifier Source: org_study_id

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