Mixed Race

Clostridium Difficile Colitis

Clostridium difficile, also known as "C. diff," is a species of bacteria that causes severe diarrhea and other intestinal disease when competing bacteria in the gut have been wiped out by antibiotics (see Wikipedia entry). In rare cases a C. diff infection can progress to toxic megacolon which can be life-threatening. In a very small percentage of the adult population C. difficile bacteria naturally reside in the gut. Other people accidentally ingest spores of the bacteria while patients in a hospital or nursing home.

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Depression

Depression accounts for substantial morbidity and mortality worldwide and risk of experiencing it may have a genetic component.  Depressive disorders manifest along a gradient from mild to severe.[1]  Electronic health record (EHR) data linked to large, multi-site biobanks[2] facilitate exploration of the genetic component of depression.

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Developmental Language Disorder

APT-DLD
Version 1.0, July 2020

Automated Phenotyping Tool for identifying DLD cases in health-systems data (APT-DLD) is an algorithm for classifying/identifying developmental language disorder cases in electronic health records system data. APT-DLD can be used to:
1. Identify pediatric DLD cases from electronic health record systems using ICD9 and ICD10 codes
2. Study epidemiology and population-level charateristics of DLD from EHRs

The How-To guide for using APT-DLD is provided in the files listed below.

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Diverticulosis and Diverticulitis

An algorithm for finding patients with diverticulosis, and of those, patients who also have diverticulitis, and to also find control patients.  Control patients will have had a colonoscopy but have no evidence of diverticula.

Simple NLP (a portable program is posted here, with instructions, and support is availabe from NU as needed) of colonoscopy reports is the gold standard algorithm, but if the text of colonoscopy reports is not available, an alternate algorithm using CPT & ICD-9 codes can be used, which is also posted.

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Hearing Loss

Phenotype Description:  individuals with sensorineural hearing loss (SNHL)
Below are algorithms used to identify individuals with SNHL at BioVU. If you have questions regarding any of the information presented on this page, you may contact either:
Wei-Qi Wei at wei-qi.wei@vanderbilt.edu or Joshua Denny at josh.denny@vanderbilt.edu

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