COVID-19 and kidney disease: insights from epidemiology to inform clinical practice

Abstract

Over the course of the COVID-19 pandemic, numerous studies have aimed to address the challenges faced by patients with kidney disease and their caregivers. These studies addressed areas of concern such as the high infection and mortality risk of patients on in-centre haemodialysis and transplant recipients. However, the ability to draw meaningful conclusions from these studies has in some instances been challenging, owing to barriers in aspects of usual care, data limitations and problematic methodological practices. In many settings, access to SARS-CoV-2 testing differed substantially between patient groups, whereas the incidence of SARS-CoV-2 infection varied over time and place because of differences in viral prevalence, targeted public health policies and vaccination rates. The absence of baseline kidney function data posed problems in the classification of chronic kidney disease and acute kidney injury in some studies, potentially compromising the generalizability of findings. Study findings also require attentive appraisal in terms of the effects of confounding, collider bias and chance. As this pandemic continues and in the future, the implementation of sustainable and integrated research infrastructure is needed in settings across the world to minimize infection transmission and both prevent and plan for the short-term and long-term complications of infectious diseases. Registries can support the real-world evaluation of vaccines and therapies in patients with advanced kidney disease while enabling monitoring of rare complications.

Fig. 1. The effect of collider bias on COVID-19 epidemiology studies.

Collider bias occurs when both the risk factor or exposure of interest and the factors on the pathway to the outcome of interest influence the mechanisms behind selection into a study sample population. This can result in biased associations between the exposure and outcome. a | Collider bias can occur in studies of the association between kidney transplantation (the risk factor, red box) and death (the outcome) in people hospitalized with COVID-19 (the sample population). Hospitalization is related to unmeasured COVID-19 severity (blue circle). By restricting the sample population to those who are hospitalized (grey box), collider bias may alter associations between kidney transplantation and death that cannot be generalized to the wider population (dotted lines), because the indications for hospitalization may differ between transplant recipients and other patient groups. Similar problems arise when investigating associations in populations admitted to intensive care. b | Collider bias can also occur when investigations of long-term reductions in estimated glomerular filtration rate (eGFR) following SARS-CoV-2 infection are restricted to those with available eGFR measurements and SARS-CoV-2 test results (grey box). In such instances, infection is only partially observed as a consequence of limited access to testing (in most cases early in the pandemic, based on disease severity). Serum creatinine testing is also more likely in those who are at risk of declining kidney function (for example, people with diabetes or cardiovascular disease, or those on certain drugs), or in those at risk of, or suspected to have acute kidney injury (AKI). Collider bias can induce and/or alter associations between the variables (indicated by dotted lines). c | Autopsy studies in patients who have died with COVID-19 are also at risk of collider bias. As only people who died after developing COVID-19 are selected (grey box), and because pre-existing chronic kidney disease (CKD) is a risk factor for severe COVID-19 and death more generally, collider bias can alter associations between COVID-19 and histological features of CKD at autopsy (dotted lines).