Acute kidney injury (AKI) is a serious condition where the function of kidneys suddenly decreases. In some countries, the number of hospitalisations due to AKI are higher in the colder winter season, a time when there are many infectious diseases being transmitted between people. One infectious pathogen that might lead to a higher number of AKI hospitalisations in the winter is norovirus, also commonly known as the “winter-vomiting bug”. Norovirus causes diarrhoea and vomiting, which may lead to dehydration, which in turn can trigger AKI in people vulnerable to AKI, such as those with chronic kidney disease.
To investigate this relationship further, we will develop a mathematical model representing the spread of norovirus in the community. Using the model we want to see by how much increases in the number of people sick with norovirus leads to increases in AKI hospitalisations. Understanding whether AKI hospitalisations are related to norovirus in the winter is important because a norovirus vaccine will become available soon. If we can demonstrate that winter increases in AKI hospitalisations are related to norovirus in the winter, then the norovirus vaccine may have the potential to prevent norovirus and also reduce the risk of being hospitalised with AKI in vulnerable people. Such additional benefits of vaccination are important to be included for an accurate estimation of the benefits of vaccination for society.
AKI is a syndrome defined by rapid decline in kidney function leading to disruption in metabolic, electrolyte, and fluid homeostasis. Between 20-25% of hospitalised patients in the UK have AKI, which is associated with a 4-16 fold increase in odds of death. Recent studies have shown that AKI hospitalisations in the UK may have a seasonal pattern, indicating potential associations with communicable diseases such as norovirus. The aim of this project is to quantify to what extent norovirus transmission patterns drive AKI hospitalisation trends. Any association would be an important consideration in future work modelling the health economic impacts of adopting a norovirus vaccination programme in the UK.
Objectives: i) develop a population-level age-structured deterministic compartmental dynamic transmission model for norovirus ii) fit the transmission model to hospitalisation and national norovirus surveillance data
Databases to be used: Hospital Episodes Statistics Admitted Patient Care and CPRD Aurum
Study populations: patients hospitalised with AKI, patients hospitalised with gastroenteritis, patients presenting to primary care for gastroenteritis, patients presenting to primary care for acute kidney injury.
Primary outcome: hospitalisation with AKI.
Exposures: gastroenteritis diagnosed in primary care, gastroenteritis diagnosed in secondary care, age, region.
Study design: population level modelling study.
Data analysis: i) trend analysis of AKI and gastroenteritis hospitalisations over time ii) fitting norovirus transmission model to hospitalisations and primary care trend data using likelihood-based Markov chain Monte Carlo (MCMC) methods to estimate what proportion of norovirus in the community leads to AKI diagnosed in primary and secondary care.
Acute kidney injury diagnosed in secondary care; Admitted Patient Care. We will define AKI in HES as having a record of at least one AKI ICD-10 N-17 code in any diagnostic position during an admission.
Rosalind Eggo - Chief Investigator - London School of Hygiene & Tropical Medicine ( LSHTM )
Hikaru Bolt - Corresponding Applicant - London School of Hygiene & Tropical Medicine ( LSHTM )
Frank Sandmann - Collaborator - London School of Hygiene & Tropical Medicine ( LSHTM )
Laurie Tomlinson - Collaborator - London School of Hygiene & Tropical Medicine ( LSHTM )
HES Admitted Patient Care