Case Ascertainment on Australian Registers for Acute Rheumatic Fever and Rheumatic Heart Disease

Abstract

In Australia, disease registers for acute rheumatic fever (ARF) and rheumatic heart disease (RHD) were previously established to facilitate disease surveillance and control, yet little is known about the extent of case-ascertainment. We compared ARF/RHD case ascertainment based on Australian ARF/RHD register records with administrative hospital data from the Northern Territory (NT), South Australia (SA), Queensland (QLD) and Western Australia (WA) for cases 3–59 years of age. Agreement across data sources was compared for persons with an ARF episode or first-ever RHD diagnosis. ARF/RHD registers from the different jurisdictions were missing 26% of Indigenous hospitalised ARF/RHD cases overall (ranging 17–40% by jurisdiction) and 10% of non-Indigenous hospitalised ARF/RHD cases (3–28%). The proportion of hospitalised RHD cases (36%) was half the proportion of hospitalised ARF cases (70%) notified to the ARF/RHD registers. The registers were found to capture few RHD cases in metropolitan areas (SA Metro: 13%, QLD Metro: 35%, WA Metro: 14%). Indigenous status, older age, comorbidities, drug/alcohol abuse and disease severity were predictors of cases appearing in the hospital data only (p < 0.05); sex was not a determinant. This analysis confirms that there are biases associated with the epidemiological analysis of single sources of case ascertainment for ARF/RHD using Australian data.

Long-term outcomes following rheumatic heart disease diagnosis in Australia

“…In addition to wider and more representative coverage of population groups across Australia, a major strength of this study is the augmentation of clinically confirmed register-derived RHD cases with hospitalization records, reducing biases resulting from studying register data alone. 20 This bias is best illustrated by noting that our sensitivity analyses of register-derived individuals consistently estimated lower absolute progression probabilities to the study cohort.…”

“…Australian RHD control efforts (including registers) have been mostly directed at Indigenous populations, capturing a higher proportion of Indigenous RHD cases. 8 , 20 While the Indigenous burden is high in absolute terms, the average severity of cases may be lower when compared to other groups. This is supported by progression estimates in the register-derived (mostly Indigenous) cohort which had generally lower progression probabilities than the multi-jurisdictional study cohort.…”

“…The strength of the study cohort is the inclusion of hospital-identified cases which had not previously been incorporated into analyses of RHD progression and might not be captured by register data sources. 20 The limitation of this cohort was that hospitalization records were used to identify RHD diagnosis date for 32.8% of individuals, potentially resulting in some misclassification bias due to coding error. A validated RHD prediction algorithm was applied to minimize the impact of false-positive diagnoses.…”

“…The major limitation of the register-derived cohort is that only people associated with RHD register programmes (mostly Indigenous) were included and registers are known to be incomplete. 20 …”

Predicting ICU Mortality in Rheumatic Heart Disease: Comparison of XGBoost and Logistic Regression

“…Age was included in our model as a demographic parameter. Agenson et al ( 40 ) indicated that advanced age had an adverse effect on mortality. In sub-Saharan Africa, RHD is thought to be responsible for up to 32% of heart failure cases ( 41 ).…”