Cardiorespiratory Fitness Algorithm (eMERGE Mayo Network Phenotype)
Please refer to attached documents.
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Hispanic
Chronic Kidney Disease
Chronic kidney disease (CKD) is defined as an abnormality of kidney structure or function present for longer than 3 months. CKD can occur as a result of heterogeneous disorders affecting the kidney. In the United States, an estimated 13.6% of adults have CKD. Notably, adjusted mortality rates are higher for patients with CKD than those without, and rates increase with CKD stage. The purpose of this algorithm is to enable accurate CKD diagnosis and staging based on EHR data.
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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.
Validation:
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Colorectal Cancer (CRC)
A pheontype defining patients with strong evidence of having been diagnosed with colorectal cancer (cases) and patients who clearly do not have such diagnoses (controls). This phenotype is being used for sequencing studies. The only NLP involved in this phenotype is a very simple string search applied to pathology reports.
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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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Diverticular Disease Severity, Left Colonic
This algorithm builds off prior phenotyping work from Pacheco & Thompson available in the PheKB phenotype "Diverticulosis and Diverticulitis" as well as the manuscripts from Joo et al (2023)(1) and De Roo et al (2023) (2) . The objective is to approximate diverticular disease severity from the electronic medical record into groups of Diverticulosis, Mild Diverticulitis, and Operative or Recurrent Inpatient Diverticulitis.
Final
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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Electronic Health Record-based Phenotyping Algorithm for Familial Hypercholesterolemia
Familial hypercholesterolemia (FH) is a relatively common Mendelian genetic disorder that is associated with elevated plasma low-density lipoprotein cholesterol (LDL-C) levels and dramatically increased lifetime risk for premature atherosclerotic cardiovascular disease (ASCVD). FH can be diagnosed based on clinical presentation and/or genetic testing results, with a positive genetic testing considered to be the “gold standard”.
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Final