All cause and Contrast Induced Non Glomerular Acute Kidney Injury

Age, race, hypertension, diabetes mellitus, metabolic syndrome, and in particular chronic kidney disease (CKD), are risk factors for acute kidney injury (AKI) that is associated with high inpatient mortality. Recent studies demonstrate that AKI itself, even mild forms previously considered ‘benign’, are associated with severe outcomes including CKD progression, cardiovascular disease (CVD)/events and mortality, suggesting that AKI, CKD and CVD are interconnected syndromes.

In development


Appendicitis is one of the most common acquired surgical conditions of childhood.  Diagnosis of appendicitis remains difficult.  Much work has been done on validation of clinical scores to reduce the number of unnecessary surgeries and radiographic tests while maintaining a high sensitivity for disease.  However, no score performs well enough in practice to reduce these risks (Kulik et al., 2013).  It is also known that appendicitis has a familial predominance, but little is known about the genetic factors that may increase a certain child's risk for the condition (Oldmeadow et al., 2009). 



Influenza infection phenotype will be determined based on clinical information obtained from electronic health records.  We will take everyone with a diagnosis of influenza A by PCR assay or culture, and then divide them into cases and controls based on the clinical information with which we are provided.


Proof of Concept PGx Phenotypes

Assessing Variant Impact and Variant Discovery Potential in PGx – PGx Phenotypes


1) Show that we can appreciate variant effect in the EMR and

2) Proof of concept for using EMR data to identify novel functional variants

For Goal 1):

·         Identify known pathological variants (by lit review, in silico analysis, interrogating extant databases)

·         Request specific quantitative trait phenotype data from sites (simple – no algorithm)

In development

CAAD (Carotid Artery Atherosclerosis Disease)

Carotid artert atherosclerosis disease (CAAD) is measured in cases and controls by both structured data, including ICD diagnosis codes, and quantitative measurements of carotid stenosis based on doppler and other imaging technologies.

The phenotype algorithm includes typical eMERGE pseudo code for implementing the structured data components of the algorithm, as well as a portable natural language processing (NLP) system used to extract percent stenosis measurements from imaging reports.

In development