Identification of High-Risk Subgroups in very elderly ICU patients

October 2017

Ageing

Country of origin: Holland

Current prognostic models for ICU patients have not been specifically developed or validated in the very elderly. The aim of this study was to develop a prognostic model for ICU patients aged 80 years and older to predict in-hospital mortality using data obtained within 24 hours after ICU admission. Aside from good overall performance, the model should reliably identify specifically subgroups at very high risk of dying.

A total of 6867 consecutive patients aged 80 years and older from 21 Dutch ICUs were studied. Data necessary to calculate the Glasgow Coma Scale, APACHE II, SAPS II, MPMII scores, and ICU and hospital survival were recorded. Data were randomly divided in a developmental (n=4587) and a validation set (n=2289). Using recursive partitioning analysis a classification tree was developed predicting in-hospital mortality. This model was compared with the original SAPS II model and with the SAPS II model after recalibration for Dutch very elderly ICU patients.

Overall performance measured by the area under the receiver operating characteristic curve and by the Brier-score was similar for the classification tree, the original SAPS II model and the recalibrated SAPS II model. The tree identified most patients with very high risk of mortality (9.2% of patients had risk > 80% vs. 8.9% for original SAPS II and 5.9% for recalibrated SAPS II). Using a cut-point at risk of 80%, the positive predictive value was 0.88 for the tree, 0.83 for original SAPS II and 0.87 for the recalibrated SAPS II.

Prognostic models with good overall performance may also reliably identify subgroups of very elderly ICU patients with a very high risk of dying before hospital discharge. The classification tree has the advantage of identifying the separate factors contributing to bad outcome and of using few variables. Up to 9.5% of patients were found to have a risk to die > 85%.

The complete article is available as a provisional PDF.

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