Algorithmic distinction of ARDS and Heart Failure in ICU data from medical embedded systems by using a computer model

Acute Respiratory Distress Syndrome (ARDS) is a common cause for respiratory failure and has a high mortality rate of 30-40% in most studies. The current standard for the diagnosis of ARDS was proposed by the Berlin Definition from 2012. This article proposes an algorithmic classification to distinguish between patients with ARDS and those with heart failure (HF). Currently, the available database is not sufficient in regards to the necessary data quality to evaluate this classification. Therefore an approach of simulating data for patients with ARDS and HF by using a computer model was implemented. The model and classification are evaluated using selected patient data, which is recorded with medical embedded systems in intensive care units, as an input for the simulation. The included scores provide a retrospective assessment of whether or not a patient has developed an ARDS.