Understanding the event structure of sentences and the whole documents is an important step in being able to extract meaningful information from text. Our task is the identification of critical illness phenotypes, specifically pneumonia, from clinical narratives. To capture those phenotypes, it is important to identify the change of state for events, in particular events that measure and compare multiple states across time. In this abstract, we describe a corpus annotated for events with change of state information. Our corpus is comprised of chest x-ray reports, where we find many descriptions of change of state comparing the volume and density of the lungs and surrounding areas.