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. 2025 Jun 18:55:101338.
doi: 10.1016/j.lanepe.2025.101338. eCollection 2025 Aug.

Long-term kidney outcomes after COVID-19: a matched cohort study using the OpenSAFELY platform

Viyaasan Mahalingasivam  1   2 , Bang Zheng  1 , Kevin Wing  3 , Edward P K Parker  4 , Krishnan Bhaskaran  1 , Juan Jesús Carrero  5 , Sandra Jayacodi  6 , Edith Jumbo  6 , Tamanna Miah  6 , Brian Gracey  6 , John Tazare  7 , Shalini Santhakumaran  8 , Rohini Mathur  9 , Ruth E Costello  1 , Emily Herrett  1 , Qing Wen  1 , Thomas Hartney  1 , Ian J Douglas  1 , Amelia Green  10 , Louis Fisher  10 , Helen J Curtis  10 , Alex J Walker  10 , Brian MacKenna  10 , William J Hulme  10 , Amir Mehrkar  10 , Sebastian Bacon  10 , Ben Goldacre  10 , Elizabeth Williamson  7 , Dorothea Nitsch  1   8 , Kathryn E Mansfield  11 , Laurie Tomlinson  1
Affiliations

Long-term kidney outcomes after COVID-19: a matched cohort study using the OpenSAFELY platform

Viyaasan Mahalingasivam et al. Lancet Reg Health Eur. .

Abstract

Background: COVID-19 severe enough to require hospitalisation is commonly associated with acute kidney injury. However, it remains unclear whether COVID-19 leads to long-term kidney outcomes in the broader population.

Methods: We undertook a population-based, matched cohort study. With the approval of NHS England, we used primary and secondary care electronic health records from England using the OpenSAFELY-TPP platform. We compared people with and without COVID-19 using fully-adjusted, stratified, cause-specific Cox models for kidney failure, 50% reduction in kidney function, and death.

Findings: Overall, all outcomes were increased after COVID-19 over the course of follow-up (HR for kidney failure 1.93 [95% CI 1.84-2.03]). Hazards of kidney failure were greatest after hospitalisation (HR 7.74 [95% CI 7.00-8.56]) and remained increased beyond 180 days of follow-up. There was no evidence of increased risk in those not hospitalised (HR 0.85 [95% CI 0.79-0.90]). Increased kidney failure was more pronounced in black ethnicity (HR 4.50 [95% CI 2.92-6.92]) compared to white ethnicity (HR 1.82 [95% CI 1.71-1.94]). Amongst those hospitalised with COVID-19, there was no attenuation of kidney failure between the first wave (HR 8.74 [95% CI 6.88-11.08]) and the Omicron wave (HR 8.36 [95% CI 6.81-10.27]).

Interpretation: We observed increased long-term kidney outcomes in people hospitalised with COVID-19, as well as notable ethnic differences. Our results suggest strategies to minimise severe COVID-19 should continue to be optimised among vulnerable groups, and that kidney function should be proactively monitored after hospital discharge.

Funding: National Institute for Health and Care Research.

Keywords: CKD; COVID-19; Chronic kidney disease; ESKD; ESRD; End-stage kidney disease; End-stage renal disease; Kidney; Kidney failure.

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Conflict of interest statement

VM held a Career Development Award from the National Institute for Health and Care Research (NIHR301535). The funders had no role in study design, data collection, data analysis, data interpretation, or the writing of this report. He received a travel grant from the European Renal Association. EP has received funding from the UKRI/MRC (MR/W021420/1), NIHR (NIHR200929, NIHR206900), and Bill & Melinda Gates Foundation (OPP1210509). He has received funding as a consultant for Tulane University as part of the ‘Safe in Pregnancy and Childhood Study’, supported by the Safety Platform for Emergency vACcines (SPEAC), Task Force for Global Health, Inc.—The Coalition for Epidemic Preparedness Innovations (CEPI). He received reimbursements for providing input on an expert report for the UK COVID-19 Inquiry. KB is funded by a Wellcome Senior Research Fellowship. JJC has received funding to Karolinska Institutet from AstraZeneca, Boehringer Ingelheim, MSD, Vifor Pharma and NovoNordisk. He has received honoraria from Fresenius Kabi and Laboratorios Columbia. RM is supported by Barts Charity (MGU0504). RC has shares in AstraZeneca unrelated to this work. EH is funded by the National Institute for Health and Care Research. ID has received unrelated research grants from GlaxoSmithKline and AstraZeneca. He holds shares in GlaxoSmithKline. BMacK is employed by NHS England working on medicines policy and clinical lead for primary care medicines data. All past declarations can be seen at https://www.whopaysthisdoctor.org/doctor/491/active. AM is a senior clincal researcher at the University of Oxford in the Bennett Institute, which is funded by contracts and grants obtained from the Bennett Foundation, Wellcome Trust, NIHR Oxford Biomedical Research Centre, NIHR Applied Research Collaboration Oxford and Thames Valley, Mohn-Westlake Foundation and NHS England. He has represented the RCGP in the health informatics group and the Profession Advisory Group that advises on access to GP Data for Pandemic Planning and Research (GDPPR); the latter is a paid role. AM is a former employee and interim Chief Medical Officer of NHS Digital (now merged into NHS England, having left NHS Digital in January 2020). SB received consulting fees from Madalena Consulting LLC by direct payment and Respiratory Matters Ltd by direct payment. BGo has received research funding from the Bennett Foundation, the Laura and John Arnold Foundation, the NHS National Institute for Health Research (NIHR), the NIHR School of Primary Care Research, NHS England, the NIHR Oxford Biomedical Research Centre, the Mohn-Westlake Foundation, NIHR Applied Research Collaboration Oxford and Thames Valley, the Wellcome Trust, the Good Thinking Foundation, Health Data Research UK, the Health Foundation, the World Health Organisation, UKRI MRC, Asthma UK, the British Lung Foundation, and the Longitudinal Health and Wellbeing strand of the National Core Studies programme; he has previously been a Non-Executive Director at NHS Digital; he also receives personal income from speaking and writing for lay audiences on the misuse of science. DN has funding from NIHR, MRC and the UK health foundation for work unrelated to COVID-19. She is the chair of the DMEC of the NIHR-funded OPTICAL study (unrelated to this work). She is the UKKA Director of Informatics Research. LT holds an NIHR Professorship (NIHR302405). The funders had no role in study design, data collection, data analysis, data interpretation, or the writing of this report. She has received travel expenses for MHRA expert advisory group meetings. She is an unpaid member of three trial steering committees (NIHR funded).

Figures

Fig. 1
Fig. 1
Study design.
Fig. 2
Fig. 2
Study population flowchart; adults aged 18+ years, counts rounded to nearest 5. eGFR = estimated glomerular filtration rate, IMD = index of multiple deprivation. Initial extractions from OpenSAFELY platform excluded individuals without valid age, sex, region and IMD.
Fig. 3
Fig. 3
Fully-adjusted hazard ratio and adjusted rate difference estimates for kidney failure (i.e., incident dialysis, kidney transplantation or estimated glomerular filtration rate (eGFR) < 15 ml/min/1.73 m2), 50% reduction in eGFR, and death after COVID-19 compared to an age-, sex- and sustainability and transformation partnership region-matched cohort, overall and by COVID-19 hospitalisation status by specific follow-up periods (in days since index date, i.e., 28 days after first COVID-19 infection record) (Table S4). Models adjusted for ethnicity, deprivation, rural or urban, body mass index, smoking status, baseline eGFR (with “no baseline eGFR measurement” treated as a categorical variable), previous acute kidney injury, cardiovascular diseases, diabetes mellitus, hypertension, immunosuppressive diseases, non-haematological cancer, general practice consultations in the previous year, hospital admissions in the previous five years and COVID-19 vaccination status. Fully-adjusted hazard ratio and adjusted rate difference on log scale. CI = confidence interval.
Fig. 4
Fig. 4
Fully-adjusted hazard ratio estimates for kidney failure (i.e., incident dialysis, kidney transplantation or estimated glomerular filtration rate (eGFR) < 15 ml/min/1.73 m2), stratified by potential effect modifiers, for COVID-19 compared to an age-, sex- and sustainability and transformation partnership region-matched cohort (Table S8). Models adjusted for ethnicity, deprivation, rural or urban, body mass index, smoking status, baseline eGFR (with “no baseline eGFR measurement” treated as a categorical variable), previous acute kidney injury, cardiovascular diseases, diabetes mellitus, hypertension, immunosuppressive diseases, non-haematological cancer, general practice consultations in the previous year, hospital admissions in the previous five years and COVID-19 vaccination status. Age in years. Baseline eGFR in ml/min/1.73 m2. CI = confidence interval. ∗COVID-19 vaccination status and COVID-19 wave restricted to cases up to March 2022 (i.e., the end of universal access to COVID-19 testing).
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