Subjective and objective survival prediction in mechanically ventilated critically ill patients: a prospective cohort study
Lucas Boeck,
Hans Pargger,
Peter Schellongowski,
Charles-Edouard Luyt,
Marco Maggiorini,
Kathleen Jahn,
Grégoire Muller,
Rene Lötscher,
Evelyne Bucher,
Nadine Cueni,
Thomas Staudinger,
Jean Chastre,
Martin Siegemund,
Michael Tamm,
Daiana Stolz
Affiliations
Lucas Boeck
Department of Clinical Research, University Hospital Basel
Hans Pargger
Intensive Care Unit, Department of Acute Medicine, University Hospital Basel
Peter Schellongowski
Department of Internal Medicine I, University Hospital Vienna
Charles-Edouard Luyt
Médecine Intensive Réanimation, Institut de Cardiologie, Groupe Hospitalier Pitié-Salpêtrière, Assistance Publique-Hôpitaux de Paris, Sorbonne-Université
Marco Maggiorini
Department of Internal Medicine, Intensive Care Unit, University Hospital Zürich
Kathleen Jahn
Department of Clinical Research, University Hospital Basel
Grégoire Muller
Médecine Intensive Réanimation, Institut de Cardiologie, Groupe Hospitalier Pitié-Salpêtrière, Assistance Publique-Hôpitaux de Paris, Sorbonne-Université
Rene Lötscher
Surgical and Medical Intensive Care Medicine, Kantonsspital Baselland
Evelyne Bucher
Intensive Care Unit, Department of Acute Medicine, University Hospital Basel
Nadine Cueni
Intensive Care Unit, Department of Acute Medicine, University Hospital Basel
Thomas Staudinger
Department of Internal Medicine I, University Hospital Vienna
Jean Chastre
Médecine Intensive Réanimation, Institut de Cardiologie, Groupe Hospitalier Pitié-Salpêtrière, Assistance Publique-Hôpitaux de Paris, Sorbonne-Université
Martin Siegemund
Department of Clinical Research, University Hospital Basel
Michael Tamm
Department of Clinical Research, University Hospital Basel
Daiana Stolz
Department of Clinical Research, University Hospital Basel
Abstract Background ICU risk assessment tools, routinely used for predicting population outcomes, are not recommended for evaluating individual risk. The state of health of single patients is mostly subjectively assessed to inform relatives and presumably to decide on treatment decisions. However, little is known how subjective and objective survival estimates compare. Methods We performed a prospective cohort study in mechanically ventilated critically ill patients across five European centres, assessed 62 objective markers and asked the clinical staff to subjectively estimate the probability of surviving 28 days. Results Within the 961 included patients, we identified 27 single objective predictors for 28-day survival (73.8%) and pooled them into predictive groups. While patient characteristics and treatment models performed poorly, the disease and biomarker models had a moderate discriminative performance for predicting 28-day survival, which improved for predicting 1-year survival. Subjective estimates of nurses (c-statistic [95% CI] 0.74 [0.70–0.78]), junior physicians (0.78 [0.74–0.81]) and attending physicians (0.75 [0.72–0.79]) discriminated survivors from non-survivors at least as good as the combination of all objective predictors (c-statistic: 0.67–0.72). Unexpectedly, subjective estimates were insufficiently calibrated, overestimating death in high-risk patients by about 20% in absolute terms. Combining subjective and objective measures refined discrimination and reduced the overestimation of death. Conclusions Subjective survival estimates are simple, cheap and similarly discriminative as objective models; however, they overestimate death risking that live-saving therapies are withheld. Therefore, subjective survival estimates of individual patients should be compared with objective tools and interpreted with caution if not agreeing. Trial registration ISRCTN ISRCTN59376582 , retrospectively registered October 31st 2013.
