title: Longer-term effects of SARS-CoV-2 infection on blood vessels and blood pressure
Creators: name: Lip, Stefanie Zhao Lin
Publisher: name: University of Glasgow
Year: 2025

description: Introduction:
This thesis aims to address critical gaps in our understanding of the interplay between COVID-19 infection, Renin-Angiotensin-Aldosterone System (RAAS) dysregulation, and hypertension. The first objective investigates whether COVID-19 infection increases the risk of developing hypertension post-recovery by conducting a prospective follow-up of non-hypertensive individuals over a 12-month period, assessing blood pressure and endothelial function. The second objective explores the role of RAAS dysregulation in post-COVID-19 hypertension by analysing RAAS pathway components and blood pressure changes in the same cohort. The third objective seeks to determine if whether individuals post COVID-19 have any differences in QoL utilising EQ-5D-3L instrument (EQ-5D-3L Index and Visual Analog Scale (VAS) scores). The fourth objective examines the association of ACE inhibitors and different antihypertensive drug classes and statins on the risk of SARS-CoV-2 infection using longitudinal studies and machine learning techniques to analyse linked electronic health records, adjusting for confounding variables.

Methods:
To assess whether COVID-19 increases the risk of hypertension post-recovery, we conducted a 12-month follow-up of non-hypertensive individuals. Blood pressure and endothelial function were monitored using ambulatory blood pressure monitoring and brachial flow-mediated dilation. Quality of life (QoL) was measured with the EQ-5D-3L questionnaire. RAAS components and blood pressure changes were analysed to investigate RAAS dysregulation. Advanced machine learning techniques were applied to estimate individual treatment effects (ITE) for the four major classes of antihypertensive drugs in comparison to statins across two distinct time frames of the COVID-19 pandemic.

Results:
There was a significant rise in blood pressure among recovered COVID-19 patients, with systolic pressure increasing by 4.57 mmHg and diastolic by 4.46 mmHg over 12 months compared to controls. A 3.15% reduction in flow-mediated dilation (FMD) suggested endothelial dysfunction. No significant difference in RAAS fingerprinting was observed. While recovered COVID-19 participants reported lower QoL, this was not statistically significant at 12 months follow-up. Our machine learning model found ACE inhibitors and statins were associated with increased SARS-CoV-2 infection risk, while thiazides showed mixed effects, and beta blockers and calcium channel blockers were associated with decreased risk.

Discussion:
The increase in blood pressure seen 12 months after recovery from COVID-19 suggest the need for prioritising cardiovascular monitoring in post-COVID-19 era. Although RAAS fingerprinting showed no significant difference, the blood pressure rise and reduced FMD suggest RAAS dysregulation may contribute to post-infection hypertension. Machine learning-based ITE estimation could potentially revolutionise studies of drug efficacy and adverse reactions, especially when randomised controlled trials are impractical.

Conclusion:
This thesis advances our understanding of COVID-19's cardiovascular consequences and provides insights for future mechanistic studies and clinical and public health policies. The observed blood pressure rise, and potential endothelial dysfunction post-recovery indicate the need for vigilant cardiovascular monitoring. The use of machine learning to estimate individual effects of antihypertensive drugs on COVID-19 risk underscores the importance of personalised treatment. Further research should elucidate long-term cardiovascular impacts and develop targeted interventions.