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Original Research: Critical Care |

A Prognostic Model for 6-Month Mortality in Elderly Survivors of Critical IllnessElderly ICU Survivor Mortality Prediction Model

Matthew R. Baldwin, MD; Wazim R. Narain, MPH; Hannah Wunsch, MD; Neil W. Schluger, MD; Joseph T. Cooke, MD, FCCP; Mathew S. Maurer, MD; John W. Rowe, MD; David J. Lederer, MD; Peter B. Bach, MD, MAPP
Author and Funding Information

From the Division of Pulmonary, Allergy, and Critical Care (Drs Baldwin, Schluger, and Lederer), Department of Anesthesiology (Dr Wunsch), and Division of Cardiology (Dr Maurer), College of Physicians and Surgeons, Columbia University; Data Analytics Group (Mr Narain), New York-Presbyterian Hospital; Department of Epidemiology (Drs Wunsch, Schluger, and Lederer) and Department of Health Policy and Management (Dr Rowe), Mailman School of Public Health, Columbia University; Division of Pulmonary and Critical Care (Dr Cooke), Weill Cornell Medical College; and Center for Health Policy and Outcomes (Dr Bach), Memorial Sloan-Kettering Cancer Center, New York, NY.

Correspondence to: Matthew R. Baldwin, MD, 630 W 168th St, PH-8, Room 101, New York, NY 10032; e-mail: mrb45@columbia.edu


Reproduction of this article is prohibited without written permission from the American College of Chest Physicians. See online for more details.

Funding/Support: This work was supported by the National Institutes of Health [Grants UL1 RR024156, 3P30AG022845-078, and by a Loan Repayment Grant from the National Institute on Aging for Dr Baldwin].


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

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