Format

Send to

Choose Destination
Chest. 2013 Apr;143(4):910-919. doi: 10.1378/chest.12-1668.

A prognostic model for 6-month mortality in elderly survivors of critical illness.

Author information

1
Division of Pulmonary, Allergy, and Critical Care, Columbia University, New York, NY. Electronic address: mrb45@columbia.edu.
2
Data Analytics Group, New York-Presbyterian Hospital, New York, NY.
3
Department of Anesthesiology, College of Physicians and Surgeons, Columbia University, New York, NY; Department of Epidemiology, New York, NY.
4
Division of Pulmonary, Allergy, and Critical Care, Columbia University, New York, NY; Department of Epidemiology, New York, NY.
5
Division of Pulmonary and Critical Care, Weill Cornell Medical College, New York, NY.
6
Division of Cardiology, College of Physicians and Surgeons, Columbia University, New York, NY.
7
Department of Health Policy and Management, Mailman School of Public Health, Columbia University, New York, NY.
8
Center for Health Policy and Outcomes, Memorial Sloan-Kettering Cancer Center, New York, NY.

Abstract

BACKGROUND:

Although 1.4 million elderly Americans survive hospitalization involving intensive care annually, many are at risk for early mortality following discharge. No models that predict the likelihood of death after discharge exist explicitly for this population. Therefore, we derived and externally validated a 6-month postdischarge mortality prediction model for elderly ICU survivors.

METHODS:

We derived the model from medical record and claims data for 1,526 consecutive patients aged ≥ 65 years who had their first medical ICU admission in 2006 to 2009 at a tertiary-care hospital and survived to discharge (excluding those patients discharged to hospice). We then validated the model in 1,010 patients from a different tertiary-care hospital.

RESULTS:

Six-month mortality was 27.3% and 30.2% in the derivation and validation cohorts, respectively. Independent predictors of mortality (in descending order of contribution to the model's predictive power) were a do-not-resuscitate order, older age, burden of comorbidity, admission from or discharge to a skilled-care facility, hospital length of stay, principal diagnoses of sepsis and hematologic malignancy, and male sex. For the derivation and external validation cohorts, the area under the receiver operating characteristic curve was 0.80 (SE, 0.01) and 0.71 (SE, 0.02), respectively, with good calibration for both (P = 0.31 and 0.43).

CONCLUSIONS:

Clinical variables available at hospital discharge can help predict 6-month mortality for elderly ICU survivors. Variables that capture elements of frailty, disability, the burden of comorbidity, and patient preferences regarding resuscitation during the hospitalization contribute most to this model's predictive power. The model could aid providers in counseling elderly ICU survivors at high risk of death and their families.

PMID:
23632902
PMCID:
PMC3616685
DOI:
10.1378/chest.12-1668
[Indexed for MEDLINE]
Free PMC Article

Supplemental Content

Full text links

Icon for Elsevier Science Icon for PubMed Central
Loading ...
Support Center