MedTrace Logo

Method of Measuring Comorbidity to Predict Outcome After Intensive Care

NCT04109001 · Status: COMPLETED · Type: OBSERVATIONAL · Enrollment: 223495

Last updated 2020-01-10

No results posted yet for this study

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

Sponsors & Collaborators

  • Uppsala University

    lead OTHER

Eligibility

Sex
ALL
Healthy Volunteers
No

Timeline & Regulatory

Start
2005-01-01
Primary Completion
2015-12-31
Completion
2015-12-31

More Related Trials

Read the full study record

This page highlights key information. For complete eligibility criteria, study locations, investigator contacts, and the full protocol, visit the original record on ClinicalTrials.gov.

View NCT04109001 on ClinicalTrials.gov