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. Issue 4 (30th September 2020)
- Record Type:
- Journal Article
- Title:
- 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. Issue 4 (30th September 2020)
- Main Title:
- 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
- Authors:
- McGrew, Kaitlin M
Garwe, Tabitha
Jafarzadeh, S Reza
Drevets, Douglas A
Zhao, Yan Daniel
Williams, Mary B
Carabin, Hélène - Abstract:
- Abstract: 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.
- Is Part Of:
- American journal of epidemiology. Volume 190:Issue 4(2021)
- Journal:
- American journal of epidemiology
- Issue:
- Volume 190:Issue 4(2021)
- Issue Display:
- Volume 190, Issue 4 (2021)
- Year:
- 2021
- Volume:
- 190
- Issue:
- 4
- Issue Sort Value:
- 2021-0190-0004-0000
- Page Start:
- 588
- Page End:
- 599
- Publication Date:
- 2020-09-30
- Subjects:
- Bayesian latent class analysis -- infective endocarditis -- injection drug use -- misclassification error -- national surveys -- prevalence -- temporal trends
Epidemiology -- Periodicals
Public health -- Periodicals
614.4 - Journal URLs:
- http://aje.oxfordjournals.org/ ↗
http://ukcatalogue.oup.com/ ↗ - DOI:
- 10.1093/aje/kwaa207 ↗
- Languages:
- English
- ISSNs:
- 0002-9262
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - 0824.600000
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