Decision support tool for differential diagnosis of Acute Respiratory Distress Syndrome (ARDS) vs Cardiogenic Pulmonary Edema (CPE): a prospective validation and meta-analysis

Introduction: We recently presented a prediction score providing decision support with the often-challenging early differential diagnosis of acute lung injury (ALI) vs cardiogenic pulmonary edema (CPE). To facilitate clinical adoption, our objective was to prospectively validate its performance in an independent cohort. Methods: Over 9 months, adult patients consecutively admitted to any intensive care unit of a tertiary-care center developing acute pulmonary edema were identified in real-time using validated electronic surveillance. For eligible patients, predictors were abstracted from medical records within 48 hours of the alert. Post-hoc expert review blinded to the prediction score established gold standard diagnosis. Results: Of 1,516 patients identified by electronic surveillance, data were abstracted for 249 patients (93% within 48 hours of disease onset), of which expert review (kappa 0.93) classified 72 as ALI, 73 as CPE and excluded 104 as “other”. With an area under the curve (AUC) of 0.81 (95% confidence interval =0.73 to 0.88) the prediction score showed similar discrimination as in prior cohorts (development AUC = 0.81, P = 0.91; retrospective validation AUC = 0.80, P = 0.92). Hosmer-Lemeshow test was significant (P = 0.01), but across eight previously defined score ranges probabilities of ALI vs CPE were the same as in the development cohort (P = 0.60). Results were the same when comparing acute respiratory distress syndrome (ARDS, Berlin definition) vs CPE. Conclusion: The clinical prediction score reliably differentiates ARDS/ALI vs CPE. Pooled results provide precise estimates of the score’s performance which can be used to screen patient populations or to assess the probability of ALI/ARDS vs CPE in specific patients. The score may thus facilitate early inclusion into research studies and expedite prompt treatment. Electronic supplementary material The online version of this article (doi:10.1186/s13054-014-0659-x) contains supplementary material, which is available to authorized users

Precision Medicine for Obstructive Sleep Apnea

Increasingly, obstructive sleep apnea treatment is being recognized as amenable to a precision medicine approach. Many pathophysiologic mechanisms (endotypes) beyond anatomic compromise have now been identified and are readily determined during polysomnography, although randomized controlled trials of endotype-specific therapies are needed. Research indicates that endotypes may also be important in predicting both adherence to therapy and disease consequences (phenotypes). Biomarker discovery and Big Data approaches derived from wearable technology are areas of active investigation and may allow more robust conclusions to be drawn over time, such that patients may soon fully realize the benefits from fresh insights into sleep science