Simplified Acute Physiology Score II as Predictor of Mortality in Intensive Care Units: A Decision Curve Analysis

<div><p>Background</p><p>End-of-life decision-making in Intensive care Units (ICUs) is difficult. The main problems encountered are the lack of a reliable prediction score for death and the fact that the opinion of patients is rarely taken into consideration. The Decision Curve Analysis (DCA) is a recent method developed to evaluate the prediction models and which takes into account the wishes of patients (or surrogates) to expose themselves to the risk of obtaining a false result. Our objective was to evaluate the clinical usefulness, with DCA, of the Simplified Acute Physiology Score II (SAPS II) to predict ICU mortality.</p><p>Methods</p><p>We conducted a retrospective cohort study from January 2011 to September 2015, in a medical-surgical 23-bed ICU at University Hospital. Performances of the SAPS II, a modified SAPS II (without AGE), and age to predict ICU mortality, were measured by a Receiver Operating Characteristic (ROC) analysis and DCA.</p><p>Results</p><p>Among the 4.370 patients admitted, 23.3% died in the ICU. Mean (standard deviation) age was 56.8 (16.7) years, and median (first-third quartile) SAPS II was 48 (34–65). Areas under ROC curves were 0.828 (0.813–0.843) for SAPS II, 0.814 (0.798–0.829) for modified SAPS II and of 0.627 (0.608–0.646) for age. DCA showed a net benefit whatever the probability threshold, especially under 0.5.</p><p>Conclusion</p><p>DCA shows the benefits of the SAPS II to predict ICU mortality, especially when the probability threshold is low. Complementary studies are needed to define the exact role that the SAPS II can play in end-of-life decision-making in ICUs.</p></div

Predicted ICU mortality and net benefit of SAPS II.

<p>Predicted ICU mortality and net benefit of SAPS II.</p

Characteristics of patients at admission and evolution in ICU.

<p>Characteristics of patients at admission and evolution in ICU.</p

Diagnostic performance of SAPS II in predicting ICU mortality.

<p>Diagnostic performance of SAPS II in predicting ICU mortality.</p

Decision curves showing the clinical usefulness of SAPS II, modified SAPS II and age to predict ICU mortality.

<p>Solid black line represents the net benefit of applying palliative care for no patients, assuming that all patients would be alive. Solid gray line represents the net benefit of applying palliative care for all patients, assuming that all would die. Long dashed line, medium dash line and short dash line represent the net benefit of applying palliative care to patients according to SAPS II, modified SAPS II and age, respectively.</p

Decision curves according to reason for ICU admission to predict ICU mortality.

<p>Decision curves showing the clinical usefulness of SAPS II to predict ICU mortality according to major reason for ICU admission: (a) cardiogenic shock, (b) hypovolemic shock, (c) septic shock, (d) coma and (e) respiratory distress syndrome. Solid black line represents the net benefit of applying palliative care for no patients, assuming that all patients would be alive. Solid gray line represents the net benefit of applying palliative care for all patients, assuming that all would die. Dashed line represents the net benefit of applying palliative care to patients according to SAPS II.</p

The list of contributors of the study.

BackgroundLeptospirosis is an anthropozoonosis that occurs worldwide but is more common in tropical regions. Severe forms may require intensive care unit (ICU) admission. Whether the clinical patterns and outcomes differ between tropical and non-tropical regions with similar healthcare systems is unclear. Our objective here was to address this issue by comparing two cohorts of ICU patients with leptospirosis managed in mainland France and in the overseas French department of Réunion, respectively.Methodology/Principal findingsWe compared two retrospective cohorts of patients admitted to intensive care for severe leptospirosis, one from Reunion Island in the Indian Ocean (tropical climate) and the other from metropolitan France (temperate climate). Chi-square and Student’s t tests were used for comparisons. After grouping the two cohorts, we also performed multiple correspondence analysis and hierarchical clustering to search for distinct clinical phenotypes. The Réunion and Metropolitan France cohorts comprised 128 and 160 patients respectively. Compared with the Réunion cohort, the metropolitan cohort had a higher mean age (42.5±14.1 vs. 51.4±16.5 years, pConclusions/SignificanceThe outcomes of severe leptospirosis requiring ICU admission did not differ between tropical and temperate regions with similar healthcare access, practices, and resources, despite some differences in patient characteristics. The identification of three different clinical phenotypes may assist in the early diagnosis and management of severe leptospirosis.</div

Map of clinical features of severe leptospirosis.

Two-dimensional distribution of clinical features of severe leptospirosis mapped along the first two dimensions (Dim 1 and Dim 2) identified by multiple correspondence analysis. These dimensions summarised 52.2% of the variability in the data. Hierarchical ascending classification showed that the patients were distributed in the plane in three clusters reflecting three distinct clinical phenotypes of severe leptospirosis. Cluster 1 (black; n = 167) was characterised by severe hepatic, renal, and coagulation failure; cluster 2 (red; n = 73) by moderately severe disease; and cluster 3 (green; n = 14) by severe neurological failure, usually with severe respiratory and cardiovascular failure.</p

Relationship between the first and second dimensions for the variables, with death in the ICU and cohort of inclusion as illustrative variables.

In the first dimension, central nervous system failure, cardiovascular failure, and respiratory failure (righthand side of the graph) are diagonally opposite absence of these events (lefthand side of the graph). Note the close proximity of the two cohorts. CNS: central nervous system; CV: cardiovascular; coag: coagulation; respi: respiratory (TIF)</p

Cluster dendrogram produced by hierarchical clustering on the principal components.

A dendrogram is a tree diagram that illustrates the arrangement of the clusters. Here, individuals are plotted on the X axis. The green, black, and red rectangles define the three clusters of patients: hepato-renal leptospirosis, moderately severe leptospirosis, and neurological leptospirosis, respectively. The graph in the upper right corner represents the loss of inertia along the different dimensions. (TIF)</p