Validity of diagnostic codes and laboratory measurements to identify patients with idiopathic acute liver injury in a hospital database.

Autor: Udo R; Division of Pharmacoepidemiology and Clinical Pharmacology, Utrecht Institute for Pharmaceutical Sciences, Utrecht University, The Netherlands.; Medicines Evaluation Board, Utrecht, The Netherlands., Maitland-van der Zee AH; Division of Pharmacoepidemiology and Clinical Pharmacology, Utrecht Institute for Pharmaceutical Sciences, Utrecht University, The Netherlands., Egberts TC; Division of Pharmacoepidemiology and Clinical Pharmacology, Utrecht Institute for Pharmaceutical Sciences, Utrecht University, The Netherlands.; Department of Clinical Pharmacy, University Medical Center Utrecht, The Netherlands., den Breeijen JH; Division of Pharmacoepidemiology and Clinical Pharmacology, Utrecht Institute for Pharmaceutical Sciences, Utrecht University, The Netherlands.; Department of Clinical Pharmacy, University Medical Center Utrecht, The Netherlands., Leufkens HG; Division of Pharmacoepidemiology and Clinical Pharmacology, Utrecht Institute for Pharmaceutical Sciences, Utrecht University, The Netherlands.; Medicines Evaluation Board, Utrecht, The Netherlands., van Solinge WW; Division of Pharmacoepidemiology and Clinical Pharmacology, Utrecht Institute for Pharmaceutical Sciences, Utrecht University, The Netherlands.; Department of Clinical Chemistry and Haematology, University Medical Center Utrecht, Utrecht, The Netherlands., De Bruin ML; Division of Pharmacoepidemiology and Clinical Pharmacology, Utrecht Institute for Pharmaceutical Sciences, Utrecht University, The Netherlands.; Medicines Evaluation Board, Utrecht, The Netherlands.
Jazyk: angličtina
Zdroj: Pharmacoepidemiology and drug safety [Pharmacoepidemiol Drug Saf] 2016 Mar; Vol. 25 Suppl 1, pp. 21-8. Date of Electronic Publication: 2015 Jul 05.
DOI: 10.1002/pds.3824
Abstrakt: Purpose: The development and validation of algorithms to identify cases of idiopathic acute liver injury (ALI) are essential to facilitate epidemiologic studies on drug-induced liver injury. The aim of this study is to determine the ability of diagnostic codes and laboratory measurements to identify idiopathic ALI cases.
Methods: In this cross-sectional validation study, patients were selected from the hospital-based Utrecht Patient Oriented Database between 2008 and 2010. Patients were identified using (I) algorithms based on ICD-9-CM codes indicative of idiopathic ALI combined with sets of liver enzyme values (ALT > 2× upper limit of normal (ULN); AST > 1ULN + AP > 1ULN + bilirubin > 1ULN; ALT > 3ULN; ALT > 3ULN + bilirubin > 2ULN; ALT > 10ULN) and (II) algorithms based on solely liver enzyme values (ALT > 3ULN + bilirubin > 2ULN; ALT > 10ULN). Hospital medical records were reviewed to confirm final diagnosis. The positive predictive value (PPV) of each algorithm was calculated.
Results: A total of 707 cases of ALI were identified. After medical review 194 (27%) patients had confirmed idiopathic ALI. The PPV for (I) algorithms with an ICD-9-CM code as well as abnormal tests ranged from 32% (13/41) to 48% (43/90) with the highest PPV found with ALT > 2ULN. The PPV for (II) algorithms with liver test abnormalities was maximally 26% (150/571).
Conclusions: The algorithm based on ICD-9-CM codes indicative of ALI combined with abnormal liver-related laboratory tests is the most efficient algorithm for identifying idiopathic ALI cases. However, cases were missed using this algorithm, because not all ALI cases had been assigned the relevant diagnostic codes in daily practice.
(Copyright © 2015 John Wiley & Sons, Ltd.)
Databáze: MEDLINE
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