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Validity of an Automated Algorithm to Identify Cirrhosis Using Electronic Health Records in Patients with Primary Biliary Cholangitis.
Lu, Mei; Bowlus, Christopher L; Lindor, Keith; Rodriguez-Watson, Carla V; Romanelli, Robert J; Haller, Irina V; Anderson, Heather; VanWormer, Jeffrey J; Boscarino, Joseph A; Schmidt, Mark A; Daida, Yihe G; Sahota, Amandeep; Vincent, Jennifer; Li, Jia; Trudeau, Sheri; Rupp, Loralee B; Gordon, Stuart C.
Afiliación
  • Lu M; Department of Public Health Sciences, Henry Ford Health System, Detroit, MI, USA.
  • Bowlus CL; University of California Davis School of Medicine, Sacramento, CA, USA.
  • Lindor K; College of Health Solutions, Arizona State University, Phoenix, AZ, USA.
  • Rodriguez-Watson CV; Center for Health Research Kaiser Permanente Mid-Atlantic Research Institute, Rockville, MD; Reagan-Udall Foundation for the FDA, Washington, DC, USA.
  • Romanelli RJ; Palo Alto Medical Foundation Research Institute, Palo Alto, CA, USA.
  • Haller IV; Essentia Institute of Rural Health, Essentia Health, Duluth, MN, USA.
  • Anderson H; Skaggs School of Pharmacy and Pharmaceutical Sciences, University of Colorado Anschutz Medical Campus, Aurora, CO, USA.
  • VanWormer JJ; Marshfield Clinic Research Foundation, Marshfield, WI, USA.
  • Boscarino JA; Department of Population Health Sciences, Geisinger Clinic, Danville, PA, USA.
  • Schmidt MA; Center for Health Research, Kaiser Permanente Northwest, Portland, OR, USA.
  • Daida YG; Center for Integrated Health Care Research, Kaiser Permanente Hawai'i, Honolulu, HI, USA.
  • Sahota A; Department of Research and Evaluation, Kaiser Permanente Southern California, Los Angeles, CA, USA.
  • Vincent J; Baylor, Scott & White Research Institute, Temple, TX, USA.
  • Li J; Department of Public Health Sciences, Henry Ford Health System, Detroit, MI, USA.
  • Trudeau S; Department of Public Health Sciences, Henry Ford Health System, Detroit, MI, USA.
  • Rupp LB; Center for Health Policy and Health Services Research, Henry Ford Health System, Detroit, MI, USA.
  • Gordon SC; Division of Gastroenterology and Hepatology, Henry Ford Health System; and Wayne State University School of Medicine, Detroit, MI, USA.
Clin Epidemiol ; 12: 1261-1267, 2020.
Article en En | MEDLINE | ID: mdl-33204167
BACKGROUND: Biopsy remains the gold standard for determining fibrosis stage in patients with primary biliary cholangitis (PBC), but it is unavailable for most patients. We used data from the 11 US health systems in the FibrOtic Liver Disease Consortium to explore a combination of biochemical markers and electronic health record (EHR)-based diagnosis/procedure codes (DPCs) to identify the presence of cirrhosis in PBC patients. METHODS: Histological fibrosis staging data were obtained from liver biopsies. Variables considered for the model included demographics (age, gender, race, ethnicity), total bilirubin, alkaline phosphatase, albumin, aspartate aminotransferase (AST) to platelet ratio index (APRI), Fibrosis 4 (FIB4) index, AST to alanine aminotransferase (ALT) ratio, and >100 DPCs associated with cirrhosis/decompensated cirrhosis, categorized into ten clusters. Using least absolute shrinkage and selection operator regression (LASSO), we derived and validated cutoffs for identifying cirrhosis. RESULTS: Among 4328 PBC patients, 1350 (32%) had biopsy data; 121 (9%) were staged F4 (cirrhosis). DPC clusters (including codes related to cirrhosis and hepatocellular carcinoma diagnoses/procedures), Hispanic ethnicity, ALP, AST/ALT ratio, and total bilirubin were retained in the final model (AUROC=0.86 and 0.83 on learning and testing data, respectively); this model with two cutoffs divided patients into three categories (no cirrhosis, indeterminate, and cirrhosis) with specificities of 81.8% (for no cirrhosis) and 80.3% (for cirrhosis). A model excluding DPCs retained ALP, AST/ALT ratio, total bilirubin, Hispanic ethnicity, and gender (AUROC=0.81 and 0.78 on learning and testing data, respectively). CONCLUSION: An algorithm using laboratory results and DPCs can categorize a majority of PBC patients as cirrhotic or noncirrhotic with high accuracy (with a small remaining group of patients' cirrhosis status indeterminate). In the absence of biopsy data, this EHR-based model can be used to identify cirrhosis in cohorts of PBC patients for research and/or clinical follow-up.
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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Tipo de estudio: Prognostic_studies Idioma: En Revista: Clin Epidemiol Año: 2020 Tipo del documento: Article País de afiliación: Estados Unidos Pais de publicación: Nueva Zelanda

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Tipo de estudio: Prognostic_studies Idioma: En Revista: Clin Epidemiol Año: 2020 Tipo del documento: Article País de afiliación: Estados Unidos Pais de publicación: Nueva Zelanda