Outcome prediction model for very elderly critically ill patients

David M. Nierman, Clyde B. Schechter, Lisa M. Cannon, Diane E. Meier

Research output: Contribution to journalArticlepeer-review

71 Scopus citations

Abstract

Context: Very elderly critically ill patients have three possible hospital outcomes: discharge to home, discharge to a skilled nursing or rehabilitation facility, or death. The factors associated with these outcomes are unknown. Objective: To develop a three-outcome prediction model for very elderly critically ill patients. Design: Retrospective chart abstraction with ordered logistic regression analysis. Setting: Academic medical center. Patients: Four hundred and fifty-five patients 85 yrs or older admitted to intensive care units (ICU) during 1996 and 1997. Measurements and Main Results: A fitted ordinal logistic regression predictive model was developed using data from 243 patients hospitalized in 1996, and validated on data from 212 patients hospitalized in 1997. Model variables include age, gender, baseline support level, type of ICU, heart rate at ICU admission, use of mechanical ventilation, vasopressors or a pulmonary artery catheter during the ICU stay, and the development of respiratory, neurologic or hematologic failure or sepsis while in the ICU. When tested on the 1997 data, the model was well calibrated and had a high discriminant index. Conclusions: This mathematical model can be used to predict the risks of these three hospital outcomes far this population of patients. These predictions can provide a context when discussing goals and expectations with patients, families, and other healthcare providers and to aid in hospital discharge planning.

Original languageEnglish (US)
Pages (from-to)1853-1859
Number of pages7
JournalCritical care medicine
Volume29
Issue number10
DOIs
StatePublished - Jan 1 2001
Externally publishedYes

Keywords

  • Aged, 80 yrs and older
  • Critical illness
  • Health services for the aged
  • Hospital mortality
  • Intensive care units
  • Logistic models
  • Models, statistical
  • Nursing homes
  • Treatment outcome

ASJC Scopus subject areas

  • Critical Care and Intensive Care Medicine

Fingerprint Dive into the research topics of 'Outcome prediction model for very elderly critically ill patients'. Together they form a unique fingerprint.

Cite this