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Unravelling post-ICU mortality: predictors and causes of death
Annemarije Braber1, Arthur R H van Zanten
1Department of Intensive Care, Gelderse Vallei Hospital, Ede, The Netherlands.
Insights
This study identified key predictors of post-ICU mortality (PICUM), including age, comorbidities, ICU length of stay, and do-not-resuscitate orders. Sepsis was a common cause of death in ICU and post-ICU patients.
Area of Science:
- Critical Care Medicine
- Intensive Care Unit (ICU) Studies
- Mortality Research
Background:
- Understanding patient outcomes after ICU discharge is crucial for improving care.
- Characterizing mortality patterns in ICU survivors and non-survivors informs clinical practice.
- Identifying factors influencing post-ICU mortality (PICUM) is essential for risk stratification.
Purpose of the Study:
- To analyze characteristics of patients who died in the ICU, after ICU in general wards, and hospital survivors.
- To determine common causes of death and predictors of post-ICU mortality (PICUM).
- To evaluate the predictive performance of Daly's mortality model for PICUM.
Main Methods:
- Retrospective single-center cohort study of 12-bed mixed medical-surgical ICU patients.
- Patients categorized into three groups: ICU deaths, post-ICU deaths, and hospital survivors.
- Causes of death reviewed by an independent panel; Daly's model and other predictors assessed for PICUM risk.
Main Results:
- 16.3% ICU mortality and 10.3% PICUM observed in 405 patients.
- Sepsis was the leading cause of death in both ICU and post-ICU deaths.
- Independent PICUM predictors identified: age, comorbidities, ICU length of stay, APACHE II score, and do-not-resuscitate code.
Conclusions:
- Sepsis is a significant cause of death, particularly in ICU deaths.
- Age, APACHE II score, ICU length of stay, do-not-resuscitate status, and comorbidities predict PICUM.
- A do-not-resuscitate code within 24 hours of admission strongly predicts PICUM; prospective validation is recommended.
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.
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