Application of Accelerated Time Models to Compare Performance of Two Comorbidity -adjusting Methods with APACHE II in Predicting Short-term Mortality Among the Critically Ill

George Mnatzaganian, Melanie Bish, Jason Fletcher, Cameron Knott, John Stephenson

Research output: Contribution to journalArticle

2 Citations (Scopus)

Abstract

Objective
This study aimed to determine how the abilities of the Charlson Index and Elixhauser comorbidities compared with the chronic health components of the Acute Physiology and Chronic Health Evaluation (APACHE II) to predict in-hospital 30 day mortality among adult critically ill patients treated inside and outside of Intensive Care Unit (ICU).

Methods
A total of 701 critically ill patients, identified in a prevalence study design on four randomly selected days in five acute care hospitals, were followed up from the date of becoming critically ill for 30 days or until death, whichever occurred first. Multiple data sources including administrative, clinical, pathology, microbiology and laboratory patient records captured the presence of acute and chronic illnesses. The exponential, Gompertz, Weibull, and log-logistic distributions were assessed as candidate parametric distributions available for the modelling of survival data. Of these, the log-logistic distribution provided the best fit and was used to construct a series of parametric survival models.

Results
Of the 701 patients identified in the initial prevalence study, 637 (90.9%) had complete data for all fields used to calculate APACHE II score. Controlling for age, sex and Acute Physiology Score (APS), the chronic health components of the APACHE II score, as a group, were better predictors of survival than Elixhauser comorbidities and Charlson Index. Of the APACHE II chronic health components, only the relatively uncommon conditions of liver failure (3.4%) and immunodeficiency (9.6%) were statistically associated with inferior patient survival with acceleration factors of 0.35 (95% CI 0.17, 0.72) for liver failure, and 0.42 (95% CI 0.26, 0.72) for immunodeficiency. Sensitivity analyses on an imputed dataset that also included the 64 individuals with imputed APACHE II score showed identical results.

Conclusion
Our study suggests that, in acute critical illness, most co-existing comorbidities are not major determinants of short-term survival, indicating that observed variations in ICU patient 30-day mortality may not be confounded by lack of adjustment to pre-existing comorbidities.
LanguageEnglish
Pages81-88
Number of pages8
JournalMethods of Information in Medicine
Volume57
Issue number1
Early online date5 Apr 2018
DOIs
Publication statusPublished - 2018

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APACHE
Critical Illness
Comorbidity
Mortality
Survival
Liver Failure
Intensive Care Units
Health
Cross-Sectional Studies
Clinical Pathology
Information Storage and Retrieval
Microbiology
Chronic Disease

Cite this

@article{62c3b700f4a84d0c9d00162154ed57d4,
title = "Application of Accelerated Time Models to Compare Performance of Two Comorbidity -adjusting Methods with APACHE II in Predicting Short-term Mortality Among the Critically Ill",
abstract = "ObjectiveThis study aimed to determine how the abilities of the Charlson Index and Elixhauser comorbidities compared with the chronic health components of the Acute Physiology and Chronic Health Evaluation (APACHE II) to predict in-hospital 30 day mortality among adult critically ill patients treated inside and outside of Intensive Care Unit (ICU).MethodsA total of 701 critically ill patients, identified in a prevalence study design on four randomly selected days in five acute care hospitals, were followed up from the date of becoming critically ill for 30 days or until death, whichever occurred first. Multiple data sources including administrative, clinical, pathology, microbiology and laboratory patient records captured the presence of acute and chronic illnesses. The exponential, Gompertz, Weibull, and log-logistic distributions were assessed as candidate parametric distributions available for the modelling of survival data. Of these, the log-logistic distribution provided the best fit and was used to construct a series of parametric survival models.ResultsOf the 701 patients identified in the initial prevalence study, 637 (90.9{\%}) had complete data for all fields used to calculate APACHE II score. Controlling for age, sex and Acute Physiology Score (APS), the chronic health components of the APACHE II score, as a group, were better predictors of survival than Elixhauser comorbidities and Charlson Index. Of the APACHE II chronic health components, only the relatively uncommon conditions of liver failure (3.4{\%}) and immunodeficiency (9.6{\%}) were statistically associated with inferior patient survival with acceleration factors of 0.35 (95{\%} CI 0.17, 0.72) for liver failure, and 0.42 (95{\%} CI 0.26, 0.72) for immunodeficiency. Sensitivity analyses on an imputed dataset that also included the 64 individuals with imputed APACHE II score showed identical results.ConclusionOur study suggests that, in acute critical illness, most co-existing comorbidities are not major determinants of short-term survival, indicating that observed variations in ICU patient 30-day mortality may not be confounded by lack of adjustment to pre-existing comorbidities.",
keywords = "Accelerated time modelling, APACHE II, Charlson Index, Critically ill, Elixhauser comorbidities, In-hospital mortality",
author = "George Mnatzaganian and Melanie Bish and Jason Fletcher and Cameron Knott and John Stephenson",
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Application of Accelerated Time Models to Compare Performance of Two Comorbidity -adjusting Methods with APACHE II in Predicting Short-term Mortality Among the Critically Ill. / Mnatzaganian, George; Bish, Melanie; Fletcher, Jason; Knott, Cameron; Stephenson, John.

In: Methods of Information in Medicine, Vol. 57, No. 1, 2018, p. 81-88.

Research output: Contribution to journalArticle

TY - JOUR

T1 - Application of Accelerated Time Models to Compare Performance of Two Comorbidity -adjusting Methods with APACHE II in Predicting Short-term Mortality Among the Critically Ill

AU - Mnatzaganian, George

AU - Bish, Melanie

AU - Fletcher, Jason

AU - Knott, Cameron

AU - Stephenson, John

N1 - This article is not an exact copy of the original published article in Methods of Information in Medicine. The definitive publisher-authenticated version of Mnatzaganian, G. et al (2018) Application of Accelerated Time Models to Compare Performance of Two Comorbidity-adjusting Methods with APACHE II in Predicting Short-term Mortality Among the Critically Ill. Methods Inf Med 2018; 57(01): 81-88, is available online at: https://www.thieme-connect.com/products/ejournals/abstract/10.3414/ME17-01-0097.

PY - 2018

Y1 - 2018

N2 - ObjectiveThis study aimed to determine how the abilities of the Charlson Index and Elixhauser comorbidities compared with the chronic health components of the Acute Physiology and Chronic Health Evaluation (APACHE II) to predict in-hospital 30 day mortality among adult critically ill patients treated inside and outside of Intensive Care Unit (ICU).MethodsA total of 701 critically ill patients, identified in a prevalence study design on four randomly selected days in five acute care hospitals, were followed up from the date of becoming critically ill for 30 days or until death, whichever occurred first. Multiple data sources including administrative, clinical, pathology, microbiology and laboratory patient records captured the presence of acute and chronic illnesses. The exponential, Gompertz, Weibull, and log-logistic distributions were assessed as candidate parametric distributions available for the modelling of survival data. Of these, the log-logistic distribution provided the best fit and was used to construct a series of parametric survival models.ResultsOf the 701 patients identified in the initial prevalence study, 637 (90.9%) had complete data for all fields used to calculate APACHE II score. Controlling for age, sex and Acute Physiology Score (APS), the chronic health components of the APACHE II score, as a group, were better predictors of survival than Elixhauser comorbidities and Charlson Index. Of the APACHE II chronic health components, only the relatively uncommon conditions of liver failure (3.4%) and immunodeficiency (9.6%) were statistically associated with inferior patient survival with acceleration factors of 0.35 (95% CI 0.17, 0.72) for liver failure, and 0.42 (95% CI 0.26, 0.72) for immunodeficiency. Sensitivity analyses on an imputed dataset that also included the 64 individuals with imputed APACHE II score showed identical results.ConclusionOur study suggests that, in acute critical illness, most co-existing comorbidities are not major determinants of short-term survival, indicating that observed variations in ICU patient 30-day mortality may not be confounded by lack of adjustment to pre-existing comorbidities.

AB - ObjectiveThis study aimed to determine how the abilities of the Charlson Index and Elixhauser comorbidities compared with the chronic health components of the Acute Physiology and Chronic Health Evaluation (APACHE II) to predict in-hospital 30 day mortality among adult critically ill patients treated inside and outside of Intensive Care Unit (ICU).MethodsA total of 701 critically ill patients, identified in a prevalence study design on four randomly selected days in five acute care hospitals, were followed up from the date of becoming critically ill for 30 days or until death, whichever occurred first. Multiple data sources including administrative, clinical, pathology, microbiology and laboratory patient records captured the presence of acute and chronic illnesses. The exponential, Gompertz, Weibull, and log-logistic distributions were assessed as candidate parametric distributions available for the modelling of survival data. Of these, the log-logistic distribution provided the best fit and was used to construct a series of parametric survival models.ResultsOf the 701 patients identified in the initial prevalence study, 637 (90.9%) had complete data for all fields used to calculate APACHE II score. Controlling for age, sex and Acute Physiology Score (APS), the chronic health components of the APACHE II score, as a group, were better predictors of survival than Elixhauser comorbidities and Charlson Index. Of the APACHE II chronic health components, only the relatively uncommon conditions of liver failure (3.4%) and immunodeficiency (9.6%) were statistically associated with inferior patient survival with acceleration factors of 0.35 (95% CI 0.17, 0.72) for liver failure, and 0.42 (95% CI 0.26, 0.72) for immunodeficiency. Sensitivity analyses on an imputed dataset that also included the 64 individuals with imputed APACHE II score showed identical results.ConclusionOur study suggests that, in acute critical illness, most co-existing comorbidities are not major determinants of short-term survival, indicating that observed variations in ICU patient 30-day mortality may not be confounded by lack of adjustment to pre-existing comorbidities.

KW - Accelerated time modelling

KW - APACHE II

KW - Charlson Index

KW - Critically ill

KW - Elixhauser comorbidities

KW - In-hospital mortality

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