Evaluating mortality in an intensive care unit requires extended survival models

Excerpt

In a recent issue of Critical Care, we read with great interest that admission at nighttime is associated with poor outcomes in intensive care units (ICUs) [1]. However, Ju and colleagues showed cumulative survival plots predicting a poor survival in the ICU of less than 20% after 2,000 ICU-hours for patients for both groups (nighttime or office time) despite the fact that 148 out of 175 patients (84.6%) survived the ICU (nighttime group) and patients admitted during office time have even an ICU survival of 96.4%. These large discrepancies are very confusing for the reader. We argue that this result is subject to a common type of survival bias [2], which we explain as follows. A fundamental assumption for calculating Kaplan-Meier survival curves is that censoring is non-informative in the sense that the hazard of death remains unchanged when a censoring event occurs. Presumably, the authors treated discharged patients as censored (displayed as crosses in their figures [1]). It is obvious that this assumption does not hold since discharged patients are usually in a better health condition than patients who stay in the ICU. This wrong assumption led to artificially reduced survival plots. The statistical solution for this is to treat discharge as a competing event for death in the ICU [2], [3] since the cumulative probability of death in the ICU depends not only on the ICU death hazard rate but also on the discharge rate. …