title: A Comprehensive Multimorbidity Index for Predicting Mortality in Intensive Care Unit Patients.
abstract: Accurate prediction of mortality for patients admitted to the intensive care units (ICUs) is an important component of medical care. However, little is known about the role of multimorbidity in predicting end of life for high-risk and vulnerable patients.
  
  
  
  The aim of the study was to derive and validate a multimorbidity risk model in an attempt to predict all-cause mortality at 6 and 12 months posthospital discharge.
  
  
  
  This is a retrospective, observational, clinical cohort study. Data were collected on 442,692 ICU patients who received care through the Veterans Administration between January 2003 and December 2013. The primary outcome was all-cause mortality at 6 and 12 months posthospital discharge. We divided the data into derivation (80%) and validation (20%) sets. Using multivariable logistic regression models, we compared prognostic models based on age, principal diagnosis groups, physiological markers, immunosuppressants, comorbidity categories, and a newly developed multimorbidity index (MMI) based on 5695 comorbidities. The cross-validated area under the receiver operating characteristic curve (AUC) was used to report the accuracy of predicting all-cause mortality at 6 and 12 months of hospital discharge.
  
  
  
  The average age of patients was 68.87 years (standard deviation = 12.1), 95.9% were males, 44.9% were widowed, divorced, or separated. The relative order of accuracy in predicting mortality was the MMI (AUC = 0.84, CI = 0.83-0.84), VA Inpatient Evaluation Center index (AUC = 0.80, CI = 0.79-0.81), principal diagnosis groups (AUC = 0.74, CI = 0.73-0.74), comorbidities (AUC = 0.69, CI = 0.68-0.70), physiological markers (AUC = 0.65, CI = 0.64-0.65), age (AUC = 0.60, CI = 0.60-0.61),and immunosuppressant use (AUC = 0.59, CI = 0.58-0.59).
  
  
  
  The MMI improved the accuracy of predicting short- and long-term all-cause mortality for ICU patients. Further prospective studies are needed to validate the index in different clinical settings and test generalizability of results in patients outside the VA system of care.
authors.affiliation: 1 Department of Health Administration and Policy, George Mason University , Fairfax, Virginia.
authors.forename: Hua
authors.initials: H
authors.lastname: Min
authors.affiliation: 1 Department of Health Administration and Policy, George Mason University , Fairfax, Virginia.
authors.forename: Sanja
authors.initials: S
authors.lastname: Avramovic
authors.affiliation: 1 Department of Health Administration and Policy, George Mason University , Fairfax, Virginia.
authors.forename: Janusz
authors.initials: J
authors.lastname: Wojtusiak
authors.affiliation: 2 Veterans Affairs Medical Center , Washington, DC.|3 School of Medicine and Health Sciences, George Washington University , Washington, DC.
authors.forename: Rahul
authors.initials: R
authors.lastname: Khosla
authors.affiliation: 2 Veterans Affairs Medical Center , Washington, DC.|4 School of Medicine, Georgetown University , Washington, DC.
authors.forename: Ross D
authors.initials: RD
authors.lastname: Fletcher
authors.affiliation: 1 Department of Health Administration and Policy, George Mason University , Fairfax, Virginia.|2 Veterans Affairs Medical Center , Washington, DC.
authors.forename: Farrokh
authors.initials: F
authors.lastname: Alemi
authors.affiliation: 2 Veterans Affairs Medical Center , Washington, DC.|3 School of Medicine and Health Sciences, George Washington University , Washington, DC.
authors.forename: Raya
authors.initials: RE
authors.lastname: Kheirbek
mesh_terms: D000328:Adult; D000368:Aged; D000369:Aged, 80 and over; D015331:Cohort Studies; D003422:Critical Care / Q000706:statistics & numerical data*; D005260:Female; D005544:Forecasting; D017052:Hospital Mortality / Q000639:trends*; D006801:Humans; D007297:Inpatients / Q000706:statistics & numerical data*; D007362:Intensive Care Units / Q000706:statistics & numerical data*; D016015:Logistic Models; D008297:Male; D008875:Middle Aged; D000076322:Multimorbidity / Q000639:trends*; D011446:Prospective Studies; D012189:Retrospective Studies; D018570:Risk Assessment / Q000379:methods; D014481:United States; D014493:United States Department of Veterans Affairs / Q000706:statistics & numerical data*
keywords: intensive care units; mortality; multimorbidity; prognosis; veterans