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Method of Measuring Comorbidity to Predict Outcome After Intensive Care (AA)

The safety and scientific validity of this study is the responsibility of the study sponsor and investigators. Listing a study does not mean it has been evaluated by the U.S. Federal Government. Read our disclaimer for details.
 
ClinicalTrials.gov Identifier: NCT04109001
Recruitment Status : Completed
First Posted : September 30, 2019
Last Update Posted : January 10, 2020
Sponsor:
Information provided by (Responsible Party):
Uppsala University

Brief Summary:

In this study the investigators will validate the impact of comorbidity on readmission to intensive care unit (ICU) and mortality after ICU and which method of measuring comorbidity that is most predictive.

The study population included all critical care patients' registries in Swedish intensive care registry (SIR) during the years 2005 to 2012 with valid personal identity number. Data from Statistics Sweden och National Board of Health and Welfare were linked to data from SIR and de-identified.

Hospital discharge diagnoses from five year preceding the index date for the ICU admission were extracted. A composite outcome of death and readmission will be analyzed.

Analyzes with cox proportional-hazards regression, time to event, on the training data set year 2005-2010 The study population will be split in a training data set (2005-10) and a test data set (2011-12) for validating our prognostic model. The predictive ability in the test data set were evaluated based on discrimination, AUC (C index), Calibration and Brier score.


Condition or disease
Comorbidities Critical Care

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Study Type : Observational [Patient Registry]
Actual Enrollment : 223495 participants
Observational Model: Cohort
Time Perspective: Other
Target Follow-Up Duration: 5 Years
Official Title: Method of Measuring Comorbidity and Time-point to Predict Readmission and Mortality of Intensive Care Patients: an Observational Study Using Linked Data From National Registers of Hospital Care and Cause of Death
Actual Study Start Date : January 1, 2005
Actual Primary Completion Date : December 31, 2015
Actual Study Completion Date : December 31, 2015



Primary Outcome Measures :
  1. The ability of comorbidity to predict death after intensive care [ Time Frame: For each admission the follow-up ends with readmission, death or end of study (2016-12-31) whichever comes first. ]
    A composite outcome of death and readmission will be analyzed. Death and readmission will also be analyzed separately. Follow-up starts at admission. A binary status variable (no/yes) is created reflecting if the outcome has happened or not together with a corresponding time variable.

  2. The ability of comorbidity to predict readmission after intensive care [ Time Frame: For each admission the follow-up ends with readmission, death or end of study (2016-12-31) whichever comes first. ]
    A composite outcome of death and readmission will be analyzed. Death and readmission will also be analyzed separately. Follow-up starts at admission. A binary status variable (no/yes) is created reflecting if the outcome has happened or not together with a corresponding time variable.



Information from the National Library of Medicine

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Ages Eligible for Study:   Child, Adult, Older Adult
Sexes Eligible for Study:   All
Accepts Healthy Volunteers:   No
Sampling Method:   Probability Sample
Study Population
All critical care patients' registries in SIR during the years 2005 to 2012 with valid personal identity number.
Criteria

Inclusion Criteria:

  • All critical care patients' registries in SIR during the years 2005 to 2012
  • Valid personal identity number

Exclusion Criteria:

  • Age 16 and older
  • No valid personal identity number
Publications:
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Responsible Party: Uppsala University
ClinicalTrials.gov Identifier: NCT04109001    
Other Study ID Numbers: Anna Aronsson
First Posted: September 30, 2019    Key Record Dates
Last Update Posted: January 10, 2020
Last Verified: January 2020
Individual Participant Data (IPD) Sharing Statement:
Plan to Share IPD: No
Plan Description: To minimize the risk of data coming into the wrong hands, after linking the data sources personal numbers replaced with anonymous serial numbers. The data then does not leave statistic Sweden and the database MONA, and are only available to qualified researchers. All analysis and statistical processing is thus done at Statistics Sweden and only results can be obtained from there. All reporting is done at group level. If the study wants to be replicated, data from the same period can be extracted from the above mentioned register.

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Studies a U.S. FDA-regulated Drug Product: No
Studies a U.S. FDA-regulated Device Product: No