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).
Autoimmune diseases (AID) refer to destructive conditions involving an aberrant chronic activation of the adaptive immune system, where the immune cells instead of producing antibodies to attack foreign invaders, mistakenly attack the body’s own healthy cells. While autoimmune diseases are heterogeneous according to symptoms, lesion types, and prognosis, and are usually studied in isolation according to groups based on organ system; various autoimmunity diseases share similar immune effector mechanisms. Recent genetic studies suggest that many autoimmune and chronic autoinflammatory condi
eMERGE-IV BMI Algorithm adapted from Geisinger Extreme Obesity Algorithm (2013). BMI is being implemented as a quantitative trait. PheKB maintains a catalog of the Geisinger Extreme Obesity algorithm, on which this is based (Phenotpe 121). This algorithm is for analysis. Sites only contributing covariates can simply compile the designated data.
Breast cancer is the most common cancer and the second leading cause of cancer-related death among women in the U.S. Known breast cancer risk factors include age, race/ethnicity, reproductive factors, and benign breast disease. Family history of breast cancer and hereditary cancer syndromes, such as BRCA1/BRCA2 mutations, confer the strongest risk for this disease.
This algorithm is for community associated MRSA (Methicillin-resistant Staphylococcus aureus, read more at http://en.wikipedia.org/wiki/MRSA). Note this algorithm will use lab results and not ICD-9 codes, as ICD-9 codes are not specific enough for this algorithm and/or are not used consistently for this phenotype. Thus, we expect the actual number of cases to be higher than what the eMERGE RC (Record Counter) estimated, and, as we will be studying patients aged 0 to 89, we would like for all sites to participate, please...