Algorithm to select patients with height measures unaffected by environmental factors (i.e. diseases & medications) that can cause an abnormal change in height. Comprehensive documentation of the algorithm can be found here on this PheKB page. Similar to our T2DM algorithm, you can install an executable version of the algorithm implemented as workflows for the Konstanz Information Miner (KNIME) data mining tool.
Project Outline: Selection of all Caucasian patients with hypothyroidism without a secondary cause of surgical removal or radiological ablation. The search is designed to eliminate subclinical hypothyroidism (by requiring that patients be on a replacement medication), medication-induced hypothyroidism (e.g., PTU, lithium, or history of amiodarone), and transient causes (e.g., pregnancy or subacute thyroiditis).
This is PhEMA (Phenotype Execution Modeling Architecture, projectphema.org)'s implementation of the following BPH (Benign Prostatic Hyperplasia) case algorithm from the following BPH case and control algorithm on PheKB:
Artifacts for this phenotype, inc. an HQMF representation, a KNIME workflow that can run against an i2b2 instance, and a snapshot of the PhAT graphical representation, are posted on GitHub:
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.