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Combining K-72 Hepatic Failure with 15 Individual T-Codes to Identify Patients with Idiosyncratic Drug-Induced Liver Injury in the Electronic Medical Record

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Abstract

Background

The aim of this study was to determine the utility of combining three K72 codes (hepatic failure) with 15 individual T-Codes (drug toxicity/poisoning) to identify potential DILI cases.

Methods

The EMR was searched for encounters that had a K72 code combined with a T-code that also met minimal liver injury laboratory criteria between 10/1/15 and 9/30/18. After manual chart review, a DILIN expert opinion causality score (1–5) was assigned to each case.

Results

Among the 345 patient encounters identified, mean age was 57 years, 53% were male, and 89% Caucasian. Thirty-seven cases (10.7%) were adjudicated as probable DILI with antibiotics being the most frequently identified suspect drugs. Of the 308 non-DILI cases, liver injury was most commonly due to congestive hepatopathy (38%) and hepatic metastases (15%). The probable-DILI cases were significantly more likely to have hepatocellular liver injury (57% vs 32.5%, p = 0.01), higher total bilirubin levels (7.7 vs 4.6 mg/dl, p = 0.03), and more severe liver injury scores (p < 0.01). The K72.0 (acute/ subacute hepatic failure) yielded the most DILI cases (29) compared to K72.9 (13) and K72.1 (0). The positive predictive value of the searching algorithm was 10.7% and improved to 15% when using only the K72.0 codes.

Conclusions

K72 codes combined with drug poisoning T-codes had a low positive predictive value in identifying patients with idiosyncratic DILI. These data support further refinement of ICD-10-based algorithms to detect DILI cases in the EMR.

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Abbreviations

ALF:

Acute liver failure

ALP:

Alkaline phosphatase

ALT:

Alanine aminotransferase

AST:

Aspartate aminotransferase

DILI:

Drug-induced liver injury

DILIN:

Drug-induced liver injury network

EMR:

Electronic medical record

ICD:

International classification of diseases

INR:

International normalized ratio

IQR:

Interquartile range

SD:

Standard deviation

ULN:

Upper limit of normal

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Funding

Jeremy Louissaint was supported by the NIH T32DK062708 Grant. Amoah Yeboah-Korang was supported by the 2018 AASLD Foundation Advanced/Transplant Hepatology Award. Robert J. Fontana has received research support from Gilead, BristolMyersSquibb, and Abbvie and consults for Sanofi.

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Authors and Affiliations

  1. Division of Gastroenterology and Hepatology, University of Michigan, 1500 E Medical Center Dr, Ann Arbor, MI, 48109, USA

    Jeremy Louissaint & Robert J. Fontana

  2. Division of Hospital Medicine, University of Michigan, Ann Arbor, USA

    Ihab Kassab

  3. Digestive Diseases, University of Cincinnati Medical Center, Cincinnati, USA

    Amoah Yeboah-Korang

Authors
  1. Jeremy Louissaint
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  2. Ihab Kassab
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  3. Amoah Yeboah-Korang
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  4. Robert J. Fontana
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Contributions

Roles a. Concept: L, Y-K, F, b. Data Acquisition: L, K, Y-K, c. Statistical Analysis: L, K, d. Writing: L, d. Revision: F, Y-K, K.

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Correspondence to Robert J. Fontana.

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Louissaint, J., Kassab, I., Yeboah-Korang, A. et al. Combining K-72 Hepatic Failure with 15 Individual T-Codes to Identify Patients with Idiosyncratic Drug-Induced Liver Injury in the Electronic Medical Record. Dig Dis Sci 67, 4243–4249 (2022). https://doi.org/10.1007/s10620-021-07223-8

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