Validity of diagnostic codes and laboratory tests of liver dysfunction to identify acute liver failure events
2015; Wiley; Volume: 24; Issue: 7 Linguagem: Inglês
10.1002/pds.3774
ISSN1099-1557
AutoresVincent Lo Re, Dena M. Carbonari, Kimberly A. Forde, David S. Goldberg, James D. Lewis, Kevin Haynes, Kimberly B.F. Leidl, K. Rajender Reddy, Jason Roy, Daohang Sha, Amy R. Marks, Jennifer L. Schneider, Brian L. Strom, Douglas A. Corley,
Tópico(s)Liver Disease Diagnosis and Treatment
ResumoPharmacoepidemiology and Drug SafetyVolume 24, Issue 7 p. 676-683 Original Report Validity of diagnostic codes and laboratory tests of liver dysfunction to identify acute liver failure events Vincent Lo Re III, Corresponding Author Vincent Lo Re III Division of Infectious Diseases, Department of Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA Center for Clinical Epidemiology and Biostatistics, Department of Biostatistics and Epidemiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA Center for Pharmacoepidemiology Research and Training, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USACorrespondence to: Vincent Lo Re III, Center for Clinical Epidemiology and Biostatistics, 836 Blockley Hall, 423 Guardian Drive, Perelman School of Medicine, University of Pennsylvania, PA 19104-6021, USA. Email: vincentl@mail.med.upenn.eduSearch for more papers by this authorDena M. Carbonari, Dena M. Carbonari Center for Clinical Epidemiology and Biostatistics, Department of Biostatistics and Epidemiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA Center for Pharmacoepidemiology Research and Training, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USASearch for more papers by this authorKimberly A. Forde, Kimberly A. Forde Center for Clinical Epidemiology and Biostatistics, Department of Biostatistics and Epidemiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA Center for Pharmacoepidemiology Research and Training, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA Division of Gastroenterology, Department of Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USASearch for more papers by this authorDavid Goldberg, David Goldberg Center for Clinical Epidemiology and Biostatistics, Department of Biostatistics and Epidemiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA Center for Pharmacoepidemiology Research and Training, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA Division of Gastroenterology, Department of Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USASearch for more papers by this authorJames D. Lewis, James D. Lewis Center for Clinical Epidemiology and Biostatistics, Department of Biostatistics and Epidemiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA Center for Pharmacoepidemiology Research and Training, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA Division of Gastroenterology, Department of Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USASearch for more papers by this authorKevin Haynes, Kevin Haynes Center for Clinical Epidemiology and Biostatistics, Department of Biostatistics and Epidemiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA Center for Pharmacoepidemiology Research and Training, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USASearch for more papers by this authorKimberly B. F. Leidl, Kimberly B. F. Leidl Center for Clinical Epidemiology and Biostatistics, Department of Biostatistics and Epidemiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USASearch for more papers by this authorRajender K. Reddy, Rajender K. Reddy Division of Gastroenterology, Department of Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USASearch for more papers by this authorJason Roy, Jason Roy Center for Clinical Epidemiology and Biostatistics, Department of Biostatistics and Epidemiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA Center for Pharmacoepidemiology Research and Training, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USASearch for more papers by this authorDaohang Sha, Daohang Sha Center for Clinical Epidemiology and Biostatistics, Department of Biostatistics and Epidemiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USASearch for more papers by this authorAmy R. Marks, Amy R. Marks Division of Research, Kaiser Permanente Northern California, Oakland, CA, USASearch for more papers by this authorJennifer L. Schneider, Jennifer L. Schneider Division of Research, Kaiser Permanente Northern California, Oakland, CA, USASearch for more papers by this authorBrian L. Strom, Brian L. Strom Center for Clinical Epidemiology and Biostatistics, Department of Biostatistics and Epidemiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA Center for Pharmacoepidemiology Research and Training, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA Rutgers Biomedical & Health Sciences, Rutgers, The State University of New Jersey, Newark, NJ, USASearch for more papers by this authorDouglas A. Corley, Douglas A. Corley Division of Research, Kaiser Permanente Northern California, Oakland, CA, USASearch for more papers by this author Vincent Lo Re III, Corresponding Author Vincent Lo Re III Division of Infectious Diseases, Department of Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA Center for Clinical Epidemiology and Biostatistics, Department of Biostatistics and Epidemiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA Center for Pharmacoepidemiology Research and Training, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USACorrespondence to: Vincent Lo Re III, Center for Clinical Epidemiology and Biostatistics, 836 Blockley Hall, 423 Guardian Drive, Perelman School of Medicine, University of Pennsylvania, PA 19104-6021, USA. Email: vincentl@mail.med.upenn.eduSearch for more papers by this authorDena M. Carbonari, Dena M. Carbonari Center for Clinical Epidemiology and Biostatistics, Department of Biostatistics and Epidemiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA Center for Pharmacoepidemiology Research and Training, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USASearch for more papers by this authorKimberly A. Forde, Kimberly A. Forde Center for Clinical Epidemiology and Biostatistics, Department of Biostatistics and Epidemiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA Center for Pharmacoepidemiology Research and Training, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA Division of Gastroenterology, Department of Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USASearch for more papers by this authorDavid Goldberg, David Goldberg Center for Clinical Epidemiology and Biostatistics, Department of Biostatistics and Epidemiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA Center for Pharmacoepidemiology Research and Training, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA Division of Gastroenterology, Department of Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USASearch for more papers by this authorJames D. Lewis, James D. Lewis Center for Clinical Epidemiology and Biostatistics, Department of Biostatistics and Epidemiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA Center for Pharmacoepidemiology Research and Training, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA Division of Gastroenterology, Department of Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USASearch for more papers by this authorKevin Haynes, Kevin Haynes Center for Clinical Epidemiology and Biostatistics, Department of Biostatistics and Epidemiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA Center for Pharmacoepidemiology Research and Training, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USASearch for more papers by this authorKimberly B. F. Leidl, Kimberly B. F. Leidl Center for Clinical Epidemiology and Biostatistics, Department of Biostatistics and Epidemiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USASearch for more papers by this authorRajender K. Reddy, Rajender K. Reddy Division of Gastroenterology, Department of Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USASearch for more papers by this authorJason Roy, Jason Roy Center for Clinical Epidemiology and Biostatistics, Department of Biostatistics and Epidemiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA Center for Pharmacoepidemiology Research and Training, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USASearch for more papers by this authorDaohang Sha, Daohang Sha Center for Clinical Epidemiology and Biostatistics, Department of Biostatistics and Epidemiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USASearch for more papers by this authorAmy R. Marks, Amy R. Marks Division of Research, Kaiser Permanente Northern California, Oakland, CA, USASearch for more papers by this authorJennifer L. Schneider, Jennifer L. Schneider Division of Research, Kaiser Permanente Northern California, Oakland, CA, USASearch for more papers by this authorBrian L. Strom, Brian L. Strom Center for Clinical Epidemiology and Biostatistics, Department of Biostatistics and Epidemiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA Center for Pharmacoepidemiology Research and Training, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA Rutgers Biomedical & Health Sciences, Rutgers, The State University of New Jersey, Newark, NJ, USASearch for more papers by this authorDouglas A. Corley, Douglas A. Corley Division of Research, Kaiser Permanente Northern California, Oakland, CA, USASearch for more papers by this author First published: 10 April 2015 https://doi.org/10.1002/pds.3774Citations: 14Read the full textAboutPDF ToolsRequest permissionExport citationAdd to favoritesTrack citation ShareShare Give accessShare full text accessShare full-text accessPlease review our Terms and Conditions of Use and check box below to share full-text version of article.I have read and accept the Wiley Online Library Terms and Conditions of UseShareable LinkUse the link below to share a full-text version of this article with your friends and colleagues. Learn more.Copy URL Share a linkShare onFacebookTwitterLinked InRedditWechat Abstract Purpose Identification of acute liver failure (ALF) is important for post-marketing surveillance of medications, but the validity of using ICD-9 diagnoses and laboratory data to identify these events within electronic health records is unknown. We examined positive predictive values (PPVs) of hospital ICD-9 diagnoses and laboratory tests of liver dysfunction for identifying ALF within a large, community-based integrated care organization. Methods We identified Kaiser Permanente Northern California health plan members (2004–2010) with a hospital diagnosis suggesting ALF (ICD-9 570, 572.2, 572.4, 572.8, 573.3, 573.8, or V42.7) plus an inpatient international normalized ratio ≥1.5 (off warfarin) and total bilirubin ≥5.0 mg/dL. Hospital records were reviewed by hepatologists to adjudicate ALF events. PPVs for confirmed outcomes were determined for individual ICD-9 diagnoses, diagnoses plus prescriptions for hepatic encephalopathy treatment, and combinations of diagnoses in the setting of coagulopathy and hyperbilirubinemia. Results Among 669 members with no pre-existing liver disease, chart review confirmed ALF in 62 (9%). Despite the presence of co-existing coagulopathy and hyperbilirubinemia, individual ICD-9 diagnoses had low PPVs (range, 5–15%); requiring prescriptions for encephalopathy treatment did not increase PPVs of these diagnoses (range, 2–23%). Hospital diagnoses of other liver disorders (ICD-9 573.8) plus hepatic coma (ICD-9 572.2) had high PPV (67%; 95%CI, 9–99%) but only identified two (3%) ALF events. Conclusions Algorithms comprising relevant hospital diagnoses, laboratory evidence of liver dysfunction, and prescriptions for hepatic encephalopathy treatment had low PPVs for confirmed ALF events. Studies of ALF will need to rely on medical records to confirm this outcome. Copyright © 2015 John Wiley & Sons, Ltd. Citing Literature Supporting Information Filename Description pds3774-sup-0001-appendix2.docxWord 2007 document , 27 KB Supporting info item Please note: The publisher is not responsible for the content or functionality of any supporting information supplied by the authors. Any queries (other than missing content) should be directed to the corresponding author for the article. Volume24, Issue7July 2015Pages 676-683 RelatedInformation
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