Prediction of recovery, dependence or death in elders who become disabled during hospitalization

Abstract

Background: Many older adults become dependent in one or more activities of daily living (ADLs: dressing, bathing, transferring, eating, toileting) when hospitalized, and their prognosis after discharge is unclear.

Objective: To develop a prognostic index to estimate one-year probabilities of recovery, dependence or death in older hospitalized patients who are discharged with incident ADL dependence.

Design: Retrospective cohort study.

Participants: 449 adults aged ≥ 70 years hospitalized for acute illness and discharged with incident ADL dependence.

Main measures: Potential predictors included demographics (age, sex, race, education, marital status), functional measures (ADL dependencies, instrumental activities of daily living [IADL] dependencies, walking ability), chronic conditions (e.g., congestive heart failure, dementia, cancer), reason for admission (e.g., neurologic, cardiovascular), and laboratory values (creatinine, albumin, hematocrit). Multinomial logistic regression was used to develop a prognostic index for estimating the probabilities of recovery, disability or death over 1 year. Discrimination of the index was assessed for each outcome based on the c statistic.

Key results: During the year following hospitalization, 36 % of patients recovered, 27 % remained dependent and 37 % died. Key predictors of recovery, dependence or death were age, sex, number of IADL dependencies 2 weeks prior to admission, number of ADL dependencies at discharge, dementia, cancer, number of other chronic conditions, reason for admission, and creatinine levels. The final prognostic index had good to excellent discrimination for all three outcomes based on the c statistic (recovery: 0.81, dependence: 0.72, death: 0.78).

Conclusions: This index accurately estimated the probabilities of recovery, dependence or death in adults aged 70 years or older who were discharged with incident disability following hospitalization. This tool may be useful in clinical settings to guide care discussions and inform decision-making related to post-hospitalization care.

Figure 1.

a–c. Predicted probabilities of recovery, dependence and death as a function of actual outcomes. The three-way predicted probabilities of recovery, dependence and death are shown for subjects who actually recovered (Fig. 1a), remained dependent (Fig. 1b) or died (Fig. 1c), such that the total predicted probability for each subject adds to 100 %. The predicted probability for each outcome may range from 0 % (base of triangle opposite the outcome of interest) to 100 % (corner of triangle for outcome of interest); the lines parallel to the base reflect predicted probabilities progressing from 10 % to 90 %. To determine a subject’s predicted probability of a given outcome, start at the base opposite the outcome (0 %) and count the number of parallel lines until the subject of interest is reached. For example, in Figure 1a, the predicted probabilities for the subject with the highest predicted probability of recovery (left corner) are 93 % recovery, 5 % dependent and 2 % death. In Figure 1b, the predicted probabilities for the subject with the highest predicted probability of dependence (top) are 72 % dependent, 21 % death and 7 % recovery. In Figure 1c, the predicted probabilities for the subject with the highest predicted probability of death (right corner) are 95 % death, 2 % recovery and 4 % dependence (numbers do not add to 100 % due to rounding).

Figure 2.

Predicted probabilities of recovery, dependence and death in all subjects combined. Figure 2 is created by stacking Figure 1a–c on top of each other, with colors used to reflect the actual outcomes for each subject (red = recovery, green = dependence, blue = death). The black triangle in the center reflects the marginal predicted probabilities for the three outcomes (36 % recovery, 27 % dependence, 37 % death).