Unravelling post-ICU mortality: predictors and causes of death

Eur J Anaesthesiol. 2010 May;27(5):486-90. doi: 10.1097/EJA.0b013e3283333aac.


Background and objectives: To study the characteristics of patients dying in the ICU, dying after ICU treatment during the same hospitalization period in general wards and post-ICU hospital survivors. In addition, causes of death and post-ICU mortality (PICUM) predictors were addressed.

Methods: The present study is a retrospective single centre cohort study in a mixed medical-surgical 12-bed ICU. Patients were divided into three groups: ICU deaths, post-ICU deaths and hospital survivors. Causes of death were determined by an independent review panel of three intensive care physicians. Daly's mortality prediction model was applied in retrospect to evaluate risk of PICUM. Other predictors were also tested for predictive value.

Results: In total, 405 patients were included: 146 ICU deaths, 92 post-ICU deaths and 167 survivors (random computerized sample from 680 survivors). ICU mortality was 16.3% and PICUM 10.3%. Sepsis was the most common cause of death in both ICU deaths (48.3%) and post-ICU deaths (30.1%). Multivariate analysis identified age, comorbidities, length of stay in ICU, Acute Physiology and Chronic Health Evaluation II score and a do-not-resuscitate code as independent predictors of PICUM. Based on Daly's mortality prediction model, 63% of patients were discharged with a high risk of PICUM. Of these, 51% actually died. Specificity was low.

Conclusion: Causes of deaths were equally distributed among study groups, except for sepsis. Sepsis was more frequently encountered among ICU deaths. Five PICUM predictors were found: age, Acute Physiology and Chronic Health Evaluation II score, length of ICU stay, do-not-resuscitate code and comorbidities. A do-not-resuscitate code during the first 24 h after admission was the most important predictor of PICUM. Prospective research is warranted to evaluate the applicability of PICUM prediction models in individual ICU patients.

MeSH terms

  • Age Factors
  • Aged
  • Cause of Death*
  • Cohort Studies
  • Female
  • Hospital Mortality*
  • Humans
  • Intensive Care Units / statistics & numerical data*
  • Male
  • Middle Aged
  • Patients' Rooms / statistics & numerical data
  • Predictive Value of Tests
  • Retrospective Studies
  • Sepsis / complications
  • Survivors / statistics & numerical data