Herpes zoster, also known as zoster or shingles, is caused by a virus called varicella zoster virus (VZV). Initial infection with the virus causes chickenpox. After chickenpox resolves the virus continues to resides in certain nerve cells. It may remain latent for many years. It may also re-activate, many years later, and cause shingles which is a painful skin rash. How the virus remains latent in the body is not well understood.
The KPWA/UW-led ovarian/uterine cancer phenotype has been validated at Mayo Clinic, the secondary phenotype development site. Validation results at both the primary and secondary sites were strong and the phenotype is ready for network wide implementation. The pseudo code document posted 11/30/2017 is correct as is and should be used by network sites for phenotype implementation. A validated data dictionary of covariates for this phenotype will be added to PheKB by 2/15/2018, but sites are encouraged to begin implementing the phenotype algorithm now.
Identify bacterial pneumonia, similar to that reported with genetic association risk in CD143 and TLR4 A229G in literature.
This rheumatoid arthritis (RA) algorithm was created using a machine-learning logistic regression model.
Systemic Lupus Erythematosus (SLE) is a chronic, systemic autoimmune disease that can affect many parts of the body including skin, lungs, brain, heart, kidneys, joints, and blood vessels. SLE presentation can vary significantly between patients. Because of this, it can be challenging to identify a patient as having SLE. Between 300,000 and 2,000,000 people in the US are estimated to have SLE. Determination of an exact number of people affected is challenging as the disease is difficult to identify given the diverse presentations and the length of time it may take for symptoms to appear.
We used Vanderbilt’s Synthetic Derivative (SD), a de-identified version of the EHR, with 2.5 million subjects. We selected all individuals with at least one SLE ICD-9 code (710.0) yielding 5959 individuals. To create a training set, 200 were randomly selected for chart review. A subject was defined as a case if diagnosed with SLE by a rheumatologist, nephrologist, or dermatologist.
Phenotype Algorithm for Type 1 Diabetes – eMERGE Phase-IV Program
Phenotyping algorithm for the identification of patients with type 1 or type 2 diabetes mellitus (DM) preoperatively using routinely available clinical data from electronic
Description of a weakly supervised machine learning approach for extracting treatment-related side effects (Urinary Incontinence) following prostate cancer therapy from multiple types of free-text clinical narratives, including progress notes, discharge summaries, history and physical notes. Prostatectomy surgery and radiation therapy are our treatments of interest for prostate cancer.