Campylobacter-associated hospitalisations in an Australian provincial setting
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Moffatt, Cameron
Kennedy, Karina
Selvey, Linda
Kirk, Martyn
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BioMed Central
Abstract
Background: Campylobacter spp. infections are a globally important cause of enterocolitis, causing substantial
morbidity. Capturing accurate information on hospitalisations is challenging and limited population-level data exist
to describe the clinico-epidemiological characteristics of hospitalised cases.
Methods: Hospital administrative and laboratory datasets were linked to identify Campylobacter-associated hospitalisations
between 2004 and 2013. Accuracy of morbidity coding was assessed using laboratory diagnosis as a gold standard, with
health department surveillance data used to calculate population-based rates. Additional patient-level data were collected via
review of medical records. Descriptive statistics were used to assess changes in rates and proportions and to
assess relationships between key variables including age, length of stay, comorbidity and complications.
Results: In total 685 Campylobacter-associated hospital admissions were identified, with the sensitivity of morbidity
coding 52.8% (95% CI 48.9–56.7%). The mean annual rate of hospitalisation was 13.6%. Hospitalisation rates were
higher for females across most age-groups, while for both genders marked increases were observed for those aged
≥60 years. Median admission age was 39.5 years, with an average length of stay of 3.5 days. Comorbidities were present
in 34.5% (237/685) of admissions, with these patients more likely to develop electrolyte disturbances, hypotension,
renal impairment or acute confusion (all p < 0.001). Bacteraemia and acute kidney injury were observed in 4.1% (28/
685) and 3.6% (23/685) of admissions, respectively. Inpatient mortality was low (0.15%).
Conclusion: Under reporting of Campylobacter-associated hospitalisations is substantial but can be improved through
data linkage. We observed demographic differences among those hospitalised but further work is needed to
determine risk factors and predictors for hospitalisation.
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BMC Infectious Diseases
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Creative Commons Attribution 4.0 International License
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