Misclassification Error-Adjusted Prevalence of Injection Drug Use Among Infective Endocarditis Hospitalizations in the United States : A Serial Cross-Sectional Analysis of the 2007-2016 National Inpatient Sample

Published by Oxford University Press on behalf of the Johns Hopkins Bloomberg School of Public Health 2020..

Administrative health databases have been used to monitor trends in infective endocarditis hospitalization related to nonprescription injection drug use (IDU) using International Classification of Diseases (ICD) code algorithms. Because no ICD code for IDU exists, drug dependence and hepatitis C virus (HCV) have been used as surrogate measures for IDU, making misclassification error (ME) a threat to the accuracy of existing estimates. In a serial cross-sectional analysis, we compared the unadjusted and ME-adjusted prevalences of IDU among 70,899 unweighted endocarditis hospitalizations in the 2007-2016 National Inpatient Sample. The unadjusted prevalence of IDU was estimated with a drug algorithm, an HCV algorithm, and a combination algorithm (drug and HCV). Bayesian latent class models were used to estimate the median IDU prevalence and 95% Bayesian credible intervals and ICD algorithm sensitivity and specificity. Sex- and age group-stratified IDU prevalences were also estimated. Compared with the misclassification-adjusted prevalence, unadjusted estimates were lower using the drug algorithm and higher using the combination algorithm. The median ME-adjusted IDU prevalence increased from 9.7% (95% Bayesian credible interval (BCI): 6.3, 14.8) in 2008 to 32.5% (95% BCI: 26.5, 38.2) in 2016. Among persons aged 18-34 years, IDU prevalence was higher in females than in males. ME adjustment in ICD-based studies of injection-related endocarditis is recommended.

Medienart:

E-Artikel

Erscheinungsjahr:

2021

Erschienen:

2021

Enthalten in:

Zur Gesamtaufnahme - volume:190

Enthalten in:

American journal of epidemiology - 190(2021), 4 vom: 06. Apr., Seite 588-599

Sprache:

Englisch

Beteiligte Personen:

McGrew, Kaitlin M [VerfasserIn]
Garwe, Tabitha [VerfasserIn]
Jafarzadeh, S Reza [VerfasserIn]
Drevets, Douglas A [VerfasserIn]
Zhao, Yan Daniel [VerfasserIn]
Williams, Mary B [VerfasserIn]
Carabin, Hélène [VerfasserIn]

Links:

Volltext

Themen:

Bayesian latent class analysis
Infective endocarditis
Injection drug use
Journal Article
Misclassification error
Multicenter Study
National surveys
Prevalence
Research Support, N.I.H., Extramural
Research Support, Non-U.S. Gov't
Temporal trends

Anmerkungen:

Date Completed 20.04.2021

Date Revised 22.07.2023

published: Print

Citation Status MEDLINE

doi:

10.1093/aje/kwaa207

funding:

Förderinstitution / Projekttitel:

PPN (Katalog-ID):

NLM315676531