Abstract
BackgroundA recently developed prediction score based on age, arterial oxygen partial pressure to fractional inspired oxygen ratio (PaO2/FiO2) and plateau pressure (abbreviated as ‘APPS’) was shown to accurately predict mortality in patients diagnosed with the acute respiratory distress syndrome (ARDS). After thorough temporal external validation of the APPS, we tested the spatial external validity in a cohort of ARDS patients recruited during 3 years in two hospitals in the Netherlands.MethodsConsecutive patients with moderate or severe ARDS according to the Berlin definition were included in this observational multicenter cohort study from the mixed medical-surgical ICUs of two university hospitals. The APPS was calculated per patient with the maximal airway pressure instead of the plateau pressure as all patients were ventilated in pressure-controlled mode. The predictive accuracy for hospital mortality was evaluated by calculating the area under the receiver operating characteristics curve (AUC-ROC). Additionally, the score was recalibrated and reassessed.ResultsIn total, 439 patients with moderate or severe ARDS were analyzed. All-cause hospital mortality was 43 %. The APPS predicted all-cause hospital mortality with moderate accuracy, with an AUC-ROC of 0.62 [95 % confidence interval (CI) 0.56–0.67]. Calibration was moderate using the original cutoff values (Hosmer–Lemeshow goodness of fit P < 0.001), and recalibration was performed for the cutoff value for age and plateau pressure. This resulted in good calibration (P = 1.0), but predictive accuracy did not improve (AUC-ROC 0.63, 95 % CI 0.58–0.68).ConclusionsThe predictive accuracy for all-cause hospital mortality of the APPS was moderate, also after recalibration of the score, and thus the APPS does not seem to be fitted for that purpose. The APPS might serve as simple tool for stratification of mortality in patients with moderate or severe ARDS. Without recalibrations, the performance of the APPS was moderate and we should therefore hesitate to blindly apply the score to other cohorts of ARDS patients.Electronic supplementary materialThe online version of this article (doi:10.1186/s13613-016-0190-0) contains supplementary material, which is available to authorized users.
Highlights
A recently developed prediction score based on age, arterial oxygen partial pressure to fractional inspired oxygen ratio (PaO2/FiO2) and plateau pressure was shown to accurately predict mortality in patients diagnosed with the acute respiratory distress syndrome (ARDS)
Our study started in 2011, before the recent ‘Berlin definition for ARDS’, we found that 100 % patients would have fulfilled the criteria of the new definition
Patients that were discharged or transferred to another intensive care unit (ICU) within 24 h after the diagnosis of ARDS were excluded from the present analysis, as they could not be used to validate the results reported by the ALIEN Network investigators
Summary
A recently developed prediction score based on age, arterial oxygen partial pressure to fractional inspired oxygen ratio (PaO2/FiO2) and plateau pressure (abbreviated as ‘APPS’) was shown to accurately predict mortality in patients diagnosed with the acute respiratory distress syndrome (ARDS). Other scoring systems have been developed for selective patient groups in the intensive care unit (ICU), e.g., for patients who develop acute kidney injury [3, 4] and liver failure [5] No such prediction system has been developed for patients with the acute respiratory distress syndrome (ARDS). A scoring system was developed that predicts hospital mortality with good accuracy in patients with ARDS [10] This score is based on three routinely available variables: age, the arterial oxygen partial pressure to fractional inspired oxygen ratio (PaO2/FiO2) and plateau pressure measured 24 h after the initial diagnosis of ARDS, and was coined the APPS. After excellent results of temporal external validation of this so-called APPS by the original authors, spatial external validation (e.g., the accuracy of prediction in another location) is highly needed
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