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Myocardial infarction and stroke subsequent to urinary tract infection (MISSOURI): protocol for a self-controlled case series using linked electronic health records
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Victoria Best,
David Gillespie ,
Kathryn Hughes,
Fiona V Lugg-Widger ,
Rebecca Cannings-John ,
Fatemeh Torabi ,
Mandy Wootton,
Ashley Akbari ,
Haroon Ahmed
BMJ Open, Volume: 12, Issue: 9, Start page: e064586
Swansea University Authors:
Victoria Best, Fatemeh Torabi , Ashley Akbari
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DOI (Published version): 10.1136/bmjopen-2022-064586
Abstract
Introduction There is increasing interest in the relationship between acute infections and acute cardiovascular events. Most previous research has focused on understanding whether the risk of acute cardiovascular events increases following a respiratory tract infection. The relationship between urin...
| Published in: | BMJ Open |
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| ISSN: | 2044-6055 2044-6055 |
| Published: |
BMJ
2022
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| Online Access: |
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| URI: | https://cronfa.swan.ac.uk/Record/cronfa61377 |
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| Abstract: |
Introduction There is increasing interest in the relationship between acute infections and acute cardiovascular events. Most previous research has focused on understanding whether the risk of acute cardiovascular events increases following a respiratory tract infection. The relationship between urinary tract infections (UTIs) and acute cardiovascular events is less well studied. Therefore, the aim of this study is to determine whether there is a causal relationship between UTI and acute myocardial infarction (MI) or stroke.Methods and analysis We will undertake a self-controlled case series study using linked anonymised general practice, hospital admission and microbiology data held within the Secure Anonymised Information Linkage (SAIL) Databank. Self-controlled case series is a relatively novel study design where individuals act as their own controls, thereby inherently controlling for time-invariant confounders. Only individuals who experience an exposure and outcome of interest are included.We will identify individuals in the SAIL Databank who have a hospital admission record for acute MI or stroke during the study period of 2010–2020. Individuals will need to be aged 30–100 during the study period and be Welsh residents for inclusion. UTI will be identified using general practice, microbiology and hospital admissions data. We will calculate the incidence of MI and stroke in predefined risk periods following an UTI and in ‘baseline’ periods (without UTI exposure) and use conditional Poisson regression models to derive incidence rate ratios.Ethics and dissemination Data access, research permissions and approvals have been obtained from the SAIL independent Information Governance Review Panel, project number 0972. Findings will be disseminated through conferences, blogs, social media threads and peer-reviewed journals. Results will be of interest internationally to primary and secondary care clinicians who manage UTIs and may inform future clinical trials of preventative therapy. |
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| College: |
Faculty of Medicine, Health and Life Sciences |
| Funders: |
This work was supported by The British Heart Foundation, grant number
PG/20/10419. The Centre for Trials Research is funded by Health and Care
Research Wales (grant number N/A) and Cancer Research UK (grant number N/A).
Population Data Science, Swansea University is supported by Health Data Research
UK (HDR-9006) and ADR Wales (grant ES/S007393/1). PRIME Centre Wales is
funded by Health and Care Research Wales. |
| Issue: |
9 |
| Start Page: |
e064586 |