Critical Care Clinical Trial
— AAOfficial 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
Verified date | January 2020 |
Source | Uppsala University |
Contact | n/a |
Is FDA regulated | No |
Health authority | |
Study type | Observational [Patient Registry] |
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.
Status | Completed |
Enrollment | 223495 |
Est. completion date | December 31, 2015 |
Est. primary completion date | December 31, 2015 |
Accepts healthy volunteers | No |
Gender | All |
Age group | N/A and older |
Eligibility |
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 |
Country | Name | City | State |
---|---|---|---|
n/a |
Lead Sponsor | Collaborator |
---|---|
Uppsala University |
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. — View Citation
Cook RJ, Lawless JF. Analysis of repeated events. Stat Methods Med Res. 2002 Apr;11(2):141-66. Review. — View Citation
Elixhauser A, Steiner C, Harris DR, Coffey RM. Comorbidity measures for use with administrative data. Med Care. 1998 Jan;36(1):8-27. — View Citation
Type | Measure | Description | Time frame | Safety issue |
---|---|---|---|---|
Primary | 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. | |
Primary | 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. |
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