Method of Measuring Comorbidity to Predict Outcome After Intensive Care

NCT04109001 | Completed

• 1 other identifier: Anna Aronsson
• Study Type: observational
• Target: 223,495
• Locations: 0 countries
• Sites: N/A

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.

Conditions

Comorbidities; Critical Care

Outcome Measures

Primary Outcomes (2)

• The ability of comorbidity to predict death after intensive care

  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.

  For each admission the follow-up ends with readmission, death or end of study (2016-12-31) whichever comes first.

• The ability of comorbidity to predict readmission after intensive care

  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.

  For each admission the follow-up ends with readmission, death or end of study (2016-12-31) whichever comes first.

Eligibility Criteria

• Sex: all
• Healthy Volunteers: No
• Age Groups: Child (0-17), Adult (18-64), Older Adult (65+)
• Sampling Method: Probability Sample

Study Population

All critical care patients' registries in SIR during the years 2005 to 2012 with valid personal identity number.

You may qualify if:

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

You may not qualify if:

• Age 16 and older
• No valid personal identity number

Sponsors & Collaborators

• Uppsala University: lead

Related Publications (4)

• Christensen S, Johansen MB, Christiansen CF, Jensen R, Lemeshow S. Comparison of Charlson comorbidity index with SAPS and APACHE scores for prediction of mortality following intensive care. Clin Epidemiol. 2011;3:203-11. doi: 10.2147/CLEP.S20247. Epub 2011 Jun 17.

  PMID: 21750629 BACKGROUND

• Cook RJ, Lawless JF. Analysis of repeated events. Stat Methods Med Res. 2002 Apr;11(2):141-66. doi: 10.1191/0962280202sm278ra.

  PMID: 12040694 BACKGROUND

• Elixhauser A, Steiner C, Harris DR, Coffey RM. Comorbidity measures for use with administrative data. Med Care. 1998 Jan;36(1):8-27. doi: 10.1097/00005650-199801000-00004.

  PMID: 9431328 BACKGROUND

• Aronsson Dannewitz A, Svennblad B, Michaelsson K, Lipcsey M, Gedeborg R. Optimized diagnosis-based comorbidity measures for all-cause mortality prediction in a national population-based ICU population. Crit Care. 2022 Oct 6;26(1):306. doi: 10.1186/s13054-022-04172-0.

  PMID: 36203163 DERIVED

Study Design

• Study Type: observational
• Observational Model: COHORT
• Time Perspective: OTHER
• Target Duration: 5 Years
• Sponsor Type: OTHER
• Responsible Party: SPONSOR

Study Record Dates

• First Submitted: September 26, 2019
• First Posted: September 30, 2019
• Study Start: January 1, 2005
• Primary Completion: December 31, 2015
• Study Completion: December 31, 2015
• Last Updated: January 10, 2020

Record last verified: 2020-01

Data Sharing

• IPD Sharing: Will not share