Aspiration of sterile post-operative spinal fluid collections using low-dose computed tomography guidance.

Sterile postoperative seromas can develop after posterior spinal surgery and cause pain, weakness, and numbness. Management typically involves operative evacuation. We propose that these collections can be managed with percutaneous computed tomography (CT) guided aspiration, potentially saving the patient an additional surgery. Here, we evaluate the safety and efficacy of this approach. Patients who developed symptomatic postoperative seromas within 60 days following surgery for spinal canal stenosis and had stable neurologic exams were considered for CT-guided percutaneous aspiration. To be considered for this approach, patients had to have pre-procedural evidence of radiographic spinal cord or cauda equina compression, hemodynamic stability, and low suspicion for infection. A total of 16 symptomatic collections were aspirated among 15 patients. The mean volume of fluid removed was 32.0 mL. There were no peri- or post-procedural complications. Eight (50%) had resolution or substantial improvement of their symptoms (p = 0.0002 when compared to the null hypothesis). One patient had short interval improvement but return of their initial symptoms 12 h following aspiration, 3/16 (19%) had minimal improvement, and 4/16 (25%) had no change in symptoms. Fluid collections that appeared denser on the pre-procedural CT were associated with retrieval of more sanguineous appearing fluid (p = 0.08). Neither the amount nor quality of fluid aspirated was associated with outcome. We conclude that percutaneous CT-guided aspiration of postoperative seromas is safe and should be considered as an alternative to open surgical evacuation in patients with stable neurologic exams.

An integrated, ontology-driven approach to constructing observational databases for research.

The electronic health record (EHR) contains a diverse set of clinical observations that are captured as part of routine care, but the incomplete, inconsistent, and sometimes incorrect nature of clinical data poses significant impediments for its secondary use in retrospective studies or comparative effectiveness research. In this work, we describe an ontology-driven approach for extracting and analyzing data from the patient record in a longitudinal and continuous manner. We demonstrate how the ontology helps enforce consistent data representation, integrates phenotypes generated through analyses of available clinical data sources, and facilitates subsequent studies to identify clinical predictors for an outcome of interest. Development and evaluation of our approach are described in the context of studying factors that influence intracranial aneurysm (ICA) growth and rupture. We report our experiences in capturing information on 78 individuals with a total of 120 aneurysms. Two example applications related to assessing the relationship between aneurysm size, growth, gene expression modules, and rupture are described. Our work highlights the challenges with respect to data quality, workflow, and analysis of data and its implications toward a learning health system paradigm.