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Mortality Prediction in Patients Undergoing Non-Invasive Ventilation in Intermediate Care
Diego Martinez-Urbistondo1, Félix Alegre1, Francisco Carmona-Torre1
1Clínica Universidad de Navarra, Department of Internal Medicine, Division of Intermediate Care and Hospitalists Unit, Pamplona, Spain.
Background:
Intermediate Care Units (ImCU) have become an alternative scenario to perform Non-Invasive Ventilation (NIV). The limited number of prognostic studies in this population support the need of mortality prediction evaluation in this context.
Objective:
The objective of this study is to analyze the performance of Simplified Acute Physiology Score (SAPS) II and 3 in patients undergoing NIV in an ImCU. Additionally, we searched for new variables that could be useful to customize these scores, in order to improve mortality prediction.
Design:
Cohort study with prospectively collected data from all patients admitted to a single center ImCU who received NIV. The SAPS II and 3 scores with their respective predicted mortality rates were calculated. Discrimination and calibration were evaluated by calculating the area under the receiver operating characteristic curve (AUC) and with the Hosmer-Lemeshow goodness of fit test for the models, respectively. Binary logistic regression was used to identify new variables to customize the scores for mortality prediction in this setting.
Patients:
The study included 241 patients consecutively admitted to an ImCU staffed by hospitalists from April 2006 to December 2013.
Key Results:
The observed in-hospital mortality was 32.4% resulting in a Standardized Mortality Ratio (SMR) of 1.35 for SAPS II and 0.68 for SAPS 3. Mortality discrimination based on the AUC was 0.73 for SAPS II and 0.69 for SAPS 3. Customized models including immunosuppression, chronic obstructive pulmonary disease (COPD), acute pulmonary edema (APE), lactic acid, pCO2 and haemoglobin levels showed better discrimination than old scores with similar calibration power.
Conclusions:
These results suggest that SAPS II and 3 should be customized with additional patient-risk factors to improve mortality prediction in patients undergoing NIV in intermediate care.
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