Kidney Function Following COVID-19 in Children and Adolescents

Lu Li; Ting Zhou; Yiwen Lu; Jiajie Chen; Yuqing Lei; Qiong Wu; Jonathan Arnold; Michael J Becich; Yuriy Bisyuk; Saul Blecker; Elizabeth Chrischilles; Dimitri A Christakis; Carol Reynolds Geary; Ravi Jhaveri; Leslie Lenert; Mei Liu; Parsa Mirhaji; Hiroki Morizono; Abu S M Mosa; Ali Mirza Onder; Ruby Patel; William E Smoyer; Bradley W Taylor; David A Williams; Bradley P Dixon; Joseph T Flynn; Caroline Gluck; Lyndsay A Harshman; Mark M Mitsnefes; Zubin J Modi; Cynthia G Pan; Hiren P Patel; Priya S Verghese; Christopher B Forrest; Michelle R Denburg; Yong Chen

doi:10.1001/jamanetworkopen.2025.4129

. 2025 Apr 11;8(4):e254129. doi: 10.1001/jamanetworkopen.2025.4129

Kidney Function Following COVID-19 in Children and Adolescents

Lu Li ^1,², Ting Zhou ¹, Yiwen Lu ^1,², Jiajie Chen ¹, Yuqing Lei ¹, Qiong Wu ^1,³, Jonathan Arnold ⁴, Michael J Becich ⁵, Yuriy Bisyuk ⁶, Saul Blecker ⁷, Elizabeth Chrischilles ⁸, Dimitri A Christakis ⁹, Carol Reynolds Geary ¹⁰, Ravi Jhaveri ¹¹, Leslie Lenert ¹², Mei Liu ¹³, Parsa Mirhaji ¹⁴, Hiroki Morizono ¹⁵, Abu S M Mosa ¹⁶, Ali Mirza Onder ¹⁷, Ruby Patel ¹⁸, William E Smoyer ¹⁹, Bradley W Taylor ²⁰, David A Williams ²¹, Bradley P Dixon ²², Joseph T Flynn ^23,²⁴, Caroline Gluck ²⁵, Lyndsay A Harshman ²⁶, Mark M Mitsnefes ²⁷, Zubin J Modi ^28,²⁹, Cynthia G Pan ³⁰, Hiren P Patel ^31,³², Priya S Verghese ^33,³⁴, Christopher B Forrest ³⁵, Michelle R Denburg ^36,^37,³⁸, Yong Chen ^1,^2,^✉, for the RECOVER Consortium

¹The Center for Health AI and Synthesis of Evidence, University of Pennsylvania, Philadelphia

²The Graduate Group in Applied Mathematics and Computational Science, School of Arts and Sciences, University of Pennsylvania, Philadelphia

³Department of Biostatistics and Health Data Science, University of Pittsburgh, Pittsburgh, Pennsylvania

⁴Division of General Internal Medicine, University of Pittsburgh School of Medicine, Pittsburgh, Pennsylvania

⁵Department of Biomedical Informatics, University of Pittsburgh School of Medicine, Pittsburgh, Pennsylvania

⁶Office of Research, University Medical Center New Orleans, New Orleans, Louisiana

⁷Department of Population Health, NYU (New York University) Grossman School of Medicine, New York, New York

⁸Department of Epidemiology, College of Public Health, University of Iowa, Iowa City

⁹Center for Child Health, Behavior and Development, Seattle Children’s Research Institute, Seattle, Washington

¹⁰Department of Pathology, Microbiology, and Immunology, University of Nebraska Medical Center, Omaha

¹¹Division of Infectious Diseases, Ann & Robert H. Lurie Children’s Hospital of Chicago, Chicago, Illinois

¹²Biomedical Informatics Center, Medical University of South Carolina, Charleston

¹³Department of Health Outcomes and Biomedical Informatics, University of Florida, College of Medicine, Gainesville

¹⁴Albert Einstein College of Medicine, Bronx, New York

¹⁵Center for Genetic Medicine Research, Children’s National Hospital, Washington, DC

¹⁶Department of Biomedical Informatics, Biostatistics and Medical Epidemiology, University of Missouri School of Medicine, Columbia

¹⁷Division of Pediatric Nephrology, Nemours Children’s Hospital, Wilmington, Delaware

¹⁸Division of Pediatric Nephrology, Stanford Medicine Children’s Health, Palo Alto, California

¹⁹Center for Clinical and Translational Research, Nationwide Children’s Hospital, Department of Pediatrics, The Ohio State University, Columbus

²⁰Clinical and Translational Science Institute, The Medical College of Wisconsin, Milwaukee

²¹Department of Anesthesiology, University of Michigan, Ann Arbor

²²Renal Section, Department of Pediatrics, University of Colorado School of Medicine, Aurora

²³Department of Pediatrics, University of Washington, Seattle

²⁴Division of Nephrology, Seattle Children’s Hospital, Seattle, Washington

²⁵Division of Pediatric Nephrology, Nemours Children’s Health, Wilmington, Delaware

²⁶Stead Family Department of Pediatrics, University of Iowa, Iowa City

²⁷Division of Pediatric Nephrology, Department of Pediatrics, Cincinnati Children’s Hospital Medical Center and University of Cincinnati, Cincinnati, Ohio

²⁸Susan B. Meister Child Health Evaluation and Research Center, Department of Pediatrics, University of Michigan, Ann Arbor

²⁹Division of Pediatric Nephrology, Department of Pediatrics, University of Michigan, Ann Arbor

³⁰Department of Pediatrics, Section of Nephrology, Medical College of Wisconsin, Milwaukee

³¹Section of Nephrology and Hypertension, Nationwide Children’s Hospital, Columbus, Ohio

³²Department of Pediatrics, Ohio State University College of Medicine

³³Department of Pediatrics, Division of Nephrology, Ann & Robert H Lurie Children’s Hospital, Chicago, Illinois

³⁴Department of Pediatrics, Northwestern University, Feinberg School of Medicine, Chicago, Illinois

³⁵Applied Clinical Research Center, Department of Pediatrics, Children’s Hospital of Philadelphia, Philadelphia, Pennsylvania

³⁶Division of Pediatric Nephrology, Children’s Hospital of Philadelphia, Philadelphia, Pennsylvania

³⁷Department of Pediatrics, Perelman School of Medicine at the University of Pennsylvania, Philadelphia

³⁸Department of Biostatistics, Epidemiology and Informatics, Perelman School of Medicine at the University of Pennsylvania, Philadelphia

Accepted for Publication: January 27, 2025.

Published: April 11, 2025. doi:10.1001/jamanetworkopen.2025.4129

Correction: This article was corrected on June 30, 2025, to fix errors in Table 2.

^✉

Corresponding Author: Yong Chen, PhD, University of Pennsylvania, 423 Guardian Dr, Blockley Hall 602, Philadelphia, PA 19104 (ychen123@pennmedicine.upenn.edu).

Author Contributions: Dr Y. Chen had full access to all of the data in the study and takes responsibility for the integrity of the data and the accuracy of the data analysis.

Concept and design: Li, Zhou, J. Chen, Wu, Smoyer, Gluck, Verghese, Forrest, Denburg, Y. Chen.

Acquisition, analysis, or interpretation of data: Li, Zhou, Lu, J. Chen, Lei, Wu, Arnold, Becich, Bisyuk, Blecker, Chrischilles, Christakis, Reynolds Geary, Jhaveri, Lenert, Liu, Mirhaji, Morizono, Mosa, Onder, R. Patel, Taylor, Williams, Dixon, Flynn, Gluck, Harshman, Mitsnefes, Modi, Pan, H. Patel, Forrest, Denburg, Y. Chen.

Drafting of the manuscript: Li, Lu, Lenert, Y. Chen.

Critical review of the manuscript for important intellectual content: Li, Zhou, J. Chen, Lei, Wu, Arnold, Becich, Bisyuk, Blecker, Chrischilles, Christakis, Reynolds Geary, Jhaveri, Liu, Mirhaji, Morizono, Mosa, Onder, R. Patel, Smoyer, Taylor, Williams, Dixon, Flynn, Gluck, Harshman, Mitsnefes, Modi, Pan, H. Patel, Verghese, Forrest, Denburg, Y. Chen.

Statistical analysis: Li, Zhou, Lu, J. Chen, Lei, Wu, Y. Chen.

Obtained funding: Jhaveri, Williams, Forrest, Y. Chen.

Administrative, technical, or material support: Arnold, Becich, Bisyuk, Chrischilles, Lenert, Mirhaji, Morizono, Mosa, Onder, Taylor, Williams, Dixon, Forrest, Y. Chen.

Supervision: Jhaveri, Onder, R. Patel, Smoyer, Taylor, Williams, Verghese, Forrest, Denburg, Y. Chen.

Conflict of Interest Disclosures: Dr Arnold reported receiving grant support from Pfizer Inc and Amgen Inc outside the submitted work. Dr Blecker reported ownership of Vineland Dialysis outside the submitted work. Dr Reynolds Geary reported receiving grant support from the Patient-Centered Outcomes Research Institute (PCORI) outside the submitted work. Dr Jhaveri reported receiving personal fees from AstraZeneca, CSL Seqirus, Sanofi SA, and Gilead Sciences Inc, grant support from GSK, and an editorial stipend from the Pediatric Infectious Diseases Society outside the submitted work and having a patent for UpToDate with royalties paid. Dr Liu reported receiving grant support from the University of Florida during the conduct of the study. Dr Mosa reported receiving grant support from PCORI, the Missouri Department of Health and Senior Services, and the National Institutes of Health (NIH) outside the submitted work. Dr Dixon reported receiving personal fees from Apellis Pharmaceuticals Inc, Novartis AG, Alexion AstraZeneca Rare Disease, Arrowhead Pharmaceuticals Inc, and Calliditas Therapeutics AB outside the submitted work. Dr Flynn reported receiving personal fees from UpToDate and an editorial stipend from International Pediatric Nephrology Association outside the submitted work. Dr Harshman reported receiving personal fees from Upsher-Smith Laboratories LLC outside the submitted work. Dr Modi reported receiving grant support from Phase V, Boehringer Ingelheim, and Travere Therapeutics Inc outside the submitted work. No other disclosures were reported. Dr Y. Chen reported receiving personal fees from Merck & Co Inc outside the submitted work.

Funding/Support: This research was funded by agreement OTA OT2HL161847-01 from the NIH as part of the Researching COVID to Enhance Recovery (RECOVER) research initiative.

Role of the Funder/Sponsor: The sponsor had no role in the design and conduct of the study; collection, management, analysis, and interpretation of the data; preparation, review, or approval of the manuscript; and decision to submit the manuscript for publication.

Group Information: Members of the RECOVER Consortium appear in Supplement 2.

Disclaimer: This content is solely the responsibility of the authors and does not necessarily represent the official views of the RECOVER Initiative, the NIH, or other funders.

Data Sharing Statement: See Supplement 3.

Additional Contributions: We thank the National Community Engagement Group, all patients, caregivers, and community representatives, and all the participants enrolled in the RECOVER initiative. In addition, we thank patient representatives Max Hornig, BA, and Leyna Aragon, MS, RECOVER patient, caregiver, or community advocate representatives, for their helpful comments and suggestions. They received financial compensation for their participation as patient representatives under their contractual agreements with RECOVER.

Additional Information: This study is part of the NIH RECOVER initiative, which seeks to understand, treat, and prevent the postacute sequelae of SARS-CoV-2 infection (PASC).

^✉

Corresponding author.

PMCID: PMC11992607 PMID: 40214993

Key Points

Question

Is SARS-CoV-2 infection associated with an increased risk of adverse kidney outcomes in children and adolescents, particularly among those with preexisting kidney disease or acute kidney injury during the acute phase?

Findings

In this cohort study including 1 900 146 pediatric patients with and without COVID-19, infection was associated with a higher incidence of new-onset chronic kidney disease and worsening kidney function, especially among those with preexisting kidney disease or acute kidney injury.

Meaning

These findings underscore the need for vigilant monitoring and management of kidney health in pediatric patients following SARS-CoV-2 infection.

Abstract

Importance

It remains unclear whether children and adolescents with SARS-CoV-2 infection are at heightened risk for long-term kidney complications.

Objective

To investigate whether SARS-CoV-2 infection is associated with an increased risk of postacute kidney outcomes among pediatric patients, including those with preexisting kidney disease or acute kidney injury (AKI).

Design, Setting, and Participants

This retrospective cohort study used data from 19 health institutions in the National Institutes of Health Researching COVID to Enhance Recovery (RECOVER) initiative from March 1, 2020, to May 1, 2023 (follow-up ≤2 years completed December 1, 2024; index date cutoff, December 1, 2022). Participants included children and adolescents (aged <21 years) with at least 1 baseline visit (24 months to 7 days before the index date) and at least 1 follow-up visit (28 to 179 days after the index date).

Exposures

SARS-CoV-2 infection, determined by positive laboratory test results (polymerase chain reaction, antigen, or serologic) or relevant clinical diagnoses. A comparison group included children with documented negative test results and no history of SARS-CoV-2 infection.

Main Outcomes and Measures

Outcomes included new-onset chronic kidney disease (CKD) stage 2 or higher or CKD stage 3 or higher among those without preexisting CKD; composite kidney events (≥50% decline in estimated glomerular filtration rate [eGFR], eGFR ≤15 mL/min/1.73 m², dialysis, transplant, or end-stage kidney disease diagnosis), and at least 30%, 40%, or 50% eGFR decline among those with preexisting CKD or acute-phase AKI. Hazard ratios (HRs) were estimated using Cox proportional hazards regression models with propensity score stratification.

Results

Among 1 900 146 pediatric patients (487 378 with and 1 412 768 without COVID-19), 969 937 (51.0%) were male, the mean (SD) age was 8.2 (6.2) years, and a range of comorbidities was represented. SARS-CoV-2 infection was associated with higher risk of new-onset CKD stage 2 or higher (HR, 1.17; 95% CI, 1.12-1.22) and CKD stage 3 or higher (HR, 1.35; 95% CI, 1.13-1.62). In those with preexisting CKD, COVID-19 was associated with an increased risk of composite kidney events (HR, 1.15; 95% CI, 1.04-1.27) at 28 to 179 days. Children with acute-phase AKI had elevated HRs (1.29; 95% CI, 1.21-1.38) at 90 to 179 days for composite outcomes.

Conclusions and Relevance

In this large US cohort study of children and adolescents, SARS-CoV-2 infection was associated with a higher risk of adverse postacute kidney outcomes, particularly among those with preexisting CKD or AKI, suggesting the need for vigilant long-term monitoring.

This cohort study investigates the association of SARS-CoV-2 infection with risk of postacute adverse kidney outcomes among children and adolescents.

Introduction

Research has shed light on the postacute sequelae of SARS-CoV-2 (PASC) infection, commonly referred to as long COVID or post–COVID-19 condition.^1,2,3 The National Institutes of Health and the Centers for Disease Control and Prevention define PASC as new, returning, or ongoing health problems present at least 4 weeks after infection.⁴ While initially recognized predominantly among adults, the emergence of PASC has raised questions about its outcomes in the pediatric population. In the US, PASC has affected 5% to 10% of children, which is comparable to the incidence among adults (6.9%).^5,6 However, there are important differences in the presentation and outcomes of acute SARS-CoV-2 infection between children and adults. Children can have different symptoms compared with adults and tend to have a milder disease course, with a lower risk of hospitalization and death, particularly among children without preexisting conditions.^7,8,9 Given these differences in acute infection, as well as the differences in prevalence between children and adults, the characteristics of PASC require further study in children.

One notable study by Bowe et al¹⁰ used national health databases from the US Department of Veterans Affairs and reported that after the first 30 days post infection, individuals with COVID-19 exhibited increased risks of several adverse kidney outcomes, including acute kidney injury (AKI); declines in estimated glomerular filtration rate (eGFR) of at least 30%, at least 40%, and at least 50% from baseline; kidney replacement therapy; and major adverse kidney events, defined as a composite of at least 50% eGFR decline, kidney replacement therapy, or all-cause mortality.¹⁰ Conversely, studies focusing on children and adolescents have been limited by short duration of follow-up, sample size (mostly <100 patients), and a narrow selection of outcomes: AKI, mortality, and multisystem inflammatory syndrome in children.^{11,12,13,14,15}

This report aims to bridge these gaps in knowledge by examining a set of postacute kidney outcomes among children and adolescents after SARS-CoV-2 infection. To assess the association of SARS-CoV-2 infection with preexisting kidney injury in pediatric patients, we stratified all analyses on the presence of preexisting chronic kidney disease (CKD) and AKI experienced during the acute phase of the infection. Our objective was to assess the risks of postacute kidney manifestations of SARS-CoV-2 infection in the pediatric population, in the hope of informing future care strategies for those affected by PASC. Postacute kidney manifestations of PASC may include persistent or progressive kidney dysfunction, which aligns with our focus on evaluating postacute kidney outcomes following COVID-19. We hypothesized that children and adolescents with COVID-19 would exhibit higher risks of adverse kidney outcomes compared with those without COVID-19, particularly among those with preexisting CKD or who developed AKI during the acute phase.

Methods

Data Sources

This study is part of the National Institutes of Health Researching COVID to Enhance Recovery (RECOVER) Initiative, which aims to learn about the long-term effects of COVID-19. This study was approved by the University of Pennsylvania’s institutional review board, with a waiver of informed consent for the use of deidentified data. It follows the Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) reporting guideline for cohort studies. We included 19 health institutions listed in eAppendix 1 in Supplement 1.

Cohort Construction

We conducted a retrospective study spanning from March 1, 2020, to May 1, 2023, with a cohort entry date cutoff of December 1, 2022 (179 days before the end of the study period). The index date for these patients was defined as the first indication of SARS-CoV-2 infection (ie, the date of the first positive COVID-19 test result or diagnosis). We included patients younger than 21 years who had at least 1 visit within 24 months to 7 days prior to the index date (defined as the baseline period) and at least 1 visit within 28 to 179 days after the index date (defined as the follow-up period). For COVID-19–positive patients, we included those who had positive findings of polymerase chain reaction, serologic, or antigen tests, diagnosis of COVID-19, or diagnosis of PASC. For COVID-19–negative patients, we included patients who had no documented SARS-CoV-2 infection and had at least 1 negative COVID-19 test result within the same study period. A random negative test was chosen as the index date for COVID-19–negative patients. Details of study variables can be found in eAppendix 2 in Supplement 1. The selection of participants for the COVID-19–positive and COVID-19–negative patient groups is summarized in Figure 1.

Figure 1. — AKI indicates acute kidney injury; CKD, chronic kidney disease; MISC, multisystem inflammatory syndrome in children; PASC, postacute sequelae of SARS-CoV-2; and RECOVER, Researching COVID to Enhance Recovery.

^aIncludes polymerase chain reaction, antigen, and serologic testing.

^bIndicates 24 months to 7 days before the index date.

^cIndicates 28 to 179 days after the index date.

Patients with either a diagnosis of multisystem inflammatory syndrome in children or evidence of end-stage kidney disease (ESKD) prior to 28 days after the index date were excluded, where ESKD was defined as having kidney dialysis, kidney transplant, diagnosis of ESKD by International Statistical Classification of Diseases, Tenth Revision codes, or any eGFR of 15 mL/min/1.73 m² or less. This exclusion facilitates a more focused analysis on the direct impacts of SARS-CoV-2 in kidney health in the pediatric population.^15,16 We conduct a sensitivity analysis in which we do not exclude patients with kidney dialysis during the acute phase for the AKI group (eAppendix 11 in Supplement 1), and a sensitivity analysis for CDK subgroup without excluding patients with ESKD during baseline (eAppendix 13 in Supplement 1).

Kidney Disease Status and Outcome Definitions

Onset date for CKD stage 2 and higher was defined as the date of the second eGFR of the earliest pair of eGFR values less than 90 mL/min/1.73 m², separated by at least 90 days, without an intervening eGFR 90 mL/min/1.73 m² or greater. Onset date for CKD stage 3 and higher was defined as the date of the second eGFR of the earliest pair of eGFR values less than 60 mL/min/1.73 m², separated by at least 90 days, without an intervening eGFR 90 mL/min/1.73 m² or greater. Additionally, we included 2 variations to the above definitions by either requiring the eGFR values to never return back to greater than 90 mL/min/1.73 m² (for CKD stage 2 or higher and CKD stage 3 or higher) or 60 mL/min/1.73 m² (for CKD stage 3 or higher), or requiring most eGFR values never return to above 90 or 60 mL/min/1.73 m², where most is defined as greater than 50%. The adjusted hazard ratios (HRs) for outcomes using varied definitions of CKD stage 2 or higher and CKD stage 3 or higher are given in eAppendix 15 in Supplement 1. Note that for the definition of CKD outcomes, we require the date of the first eGFR of the pair to be 28 days after the infection. AKI was defined as having a serum creatinine measurement within 28 days after the index date that was 0.3 mg/dL (to convert to μmol/L, multiply by 88.4) or 50% greater than baseline, where baseline was defined as the closest value within 90 days before index date, and if this was not available, established age and sex reference values were used.¹⁷ We performed a sensitivity analysis using the lowest creatinine measurement within 90 days before the index date as the baseline (eAppendix 12 in Supplement 1). We used the U25 serum creatinine–based equations¹⁸ to estimate eGFR, due to limited availability of serum cystatin C data. Age was computed at the date of the serum creatinine measurement and the closest height within 180 days of the date of the serum creatinine measurement was used.

For patients without CKD stage 2 or higher in the 24 months before the SARS-CoV-2 infection, we examined the outcomes of new onset of CKD stage 2 or higher or CKD stage 3 or higher within 28 to 729 days after SARS-CoV-2 infection. For patients with preexisting CKD in the 24 months before the SARS-CoV-2 infection, we examined a composite outcome including therapeutic interventions (long-term kidney dialysis, kidney transplant, eGFR decline of at least 50%, ESKD diagnosis, or eGFR 15 mL/min/1.73 m² or less within 28 to 179 days and within 180 to 729 days after SARS-CoV-2 infection). We also looked at eGFR decline of at least 30%, 40%, and 50% from within 28 to 179 days and within 180 to 729 days after SARS-CoV-2 infection. For patients with AKI during the acute phase (within 28 days) of SARS-CoV-2 infection, we examined the same sets of outcomes as with patients in the other 2 strata and focused on ascertainment of these outcomes within 90 to 179 days and within 180 to 729 days.

Covariates

We examined a comprehensive set of 138 patient characteristics as potential confounders. These included patient age at cohort entry; sex (female or male); electronic health record (EHR)–derived race and ethnicity (combined Asian American and Native Hawaiian or Other Pacific Islander, Hispanic, non-Hispanic Black, non-Hispanic White, multiracial, or other [including no information, refuse to answer, or unknown from EHR concept source values]); month and year of cohort entry (from March 1, 2020, to May 1, 2023); site index for cohort entry; obesity defined using the 95th percentile or greater of body mass index for age and sex; a chronic condition indicator as defined by the Pediatric Medical Complexity Algorithm¹⁹ (consisting of no chronic condition, noncomplex chronic condition, or complex chronic condition); a list of preexisting chronic conditions; the number of inpatient, outpatient, and emergency department visits; the number of unique medications or prescriptions (0, 1, 2, or ≥3) at baseline; the number of negative test results during the baseline period (grouped as 0, 1, 2, or ≥3); the number of vaccine doses before cohort entry date (0, 1, or ≥2); and interval since the last immunization date (no vaccine, <4 months, or ≥4 months). Race and ethnicity were included in the analysis because they are potential confounders in this study.

Statistical Analysis

We calculated the incidence of postacute kidney outcomes in both COVID-19–positive and COVID-19–negative cohorts stratified by preexisting kidney health status. To quantify the risks of postacute kidney manifestations of SARS-CoV-2 infection, we used the HR as the comparative measure, derived from Cox proportional hazards regression models.

To eliminate potential measured confounders, we used a propensity score stratification technique with the covariates detailed in the Covariates section. To handle the large number of covariates, we used L1-penalized logistic regression. To mitigate aggregation bias and account for potential clustering due to site-specific variations, we stratified by propensity scores, incorporating site as a covariate in the propensity score model. After performing the stratification, we assessed the standardized mean difference between each covariate value for COVID-19–positive and COVID-19–negative patients, with a difference of 0.1 or less indicating an acceptable balance.^20,21 The clinical equipoise before and after stratification and standardized mean difference of covariates before and after stratification for the primary analysis appear in eAppendix 3 in Supplement 1.

Results

Cohort Identification

Among 1 900 146 pediatric patients, a total of 487 378 with COVID-19 and 1 412 768 without COVID-19 in the RECOVER database were included to evaluate the risks of postacute kidney manifestations of SARS-CoV-2 infection. Of these patients, 930 209 (49.0%) were female and 969 937 (51.0%) were male; mean (SD) age was 8.2 (6.2) years. By race and ethnicity, 91 628 patients (4.8%) were Asian American or Native Hawaiian or Other Pacific Islander; 399 307 (21.0%), Hispanic; 328 002 (17.3%), non-Hispanic Black; 852 723 (44.9%), non-Hispanic White; 43 790 (2.3%), multiracial; and 184 696 (9.7%), other or unknown. Baseline comorbidities by COVID-19 status and preexisting kidney health status are presented in Table 1. Site information and detailed breakdown of age distribution are in eAppendix 14 in Supplement 1.

Table 1. Baseline Characteristics of Patients.

Characteristic	Patient group, No. (%)^a
	COVID-19 negative				COVID-19 positive
	No AKI or CKD (n = 1 383 464)	CKD (n = 14 999)	AKI (n = 14 305)	Overall (n = 1 412 768)	No AKI or CKD (n = 477 031)	CKD (n = 6483)	AKI (n = 3864)	Overall (n = 487 378)
Age at cohort entry, y
Mean (SD)	7.9 (6.1)	12.8 (5.8)	8.6 (7.0)	8.0 (6.1)	8.7 (6.3)	13.6 (5.7)	10.4 (7.0)	8.8 (6.4)
Median (IQR)	7.0 (2.0-13.0)	15.0 (8.0-17.0)	8.0 (1.0-15.0)	7.0 (2.0-13.0)	8.0 (3.0-14.0)	16.0 (10.0-18.0)	12.0 (3.0-17.0)	9.0 (3.0-14.0)
Sex
Female	671 071 (48.5)	8963 (59.8)	6477 (45.3)	686 511 (48.6)	237 969 (49.9)	4052 (62.5)	1677 (43.4)	243 698 (50.0)
Male	712 393 (51.5)	6036 (40.2)	7828 (54.7)	726 257 (51.4)	239 062 (50.1)	2431 (37.5)	2187 (56.6)	243 680 (50.0)
Race and ethnicity
Asian American and Native Hawaiian or Other Pacific Islander	67 455 (4.9)	554 (3.7)	624 (4.4)	68 633 (4.9)	22 661 (4.8)	193 (3.0)	141 (3.6)	22 995 (4.7)
Hispanic	285 725 (20.7)	2234 (14.9)	2673 (18.7)	290 632 (20.6)	106 979 (22.4)	969 (14.9)	727 (18.8)	108 675 (22.3)
Non-Hispanic Black	234 968 (17.0)	3058 (20.4)	4045 (28.3)	242 071 (17.1)	83 295 (17.5)	1478 (22.8)	1158 (30.0)	85 931 (17.6)
Non-Hispanic White	625 621 (45.2)	8091 (53.9)	5725 (40.0)	639 437 (45.3)	208 246 (43.7)	3478 (53.6)	1562 (40.4)	213 286 (43.8)
Multiracial	33 778 (2.4)	252 (1.7)	164 (1.1)	34 194 (2.4)	9479 (2.0)	79 (1.2)	38 (1.0)	9596 (2.0)
Other or unknown^b	135 917 (9.8)	810 (5.4)	1074 (7.5)	137 801 (9.8)	46 371 (9.7)	286 (4.4)	238 (6.2)	46 895 (9.6)
Cohort entry period
March to May 2020	25 471 (1.8)	594 (4.0)	436 (3.0)	26 501 (1.9)	4778 (1.0)	96 (1.5)	114 (3.0)	4988 (1.0)
March to May 2021	137 964 (10.0)	1497 (10.0)	1534 (10.7)	140 995 (10.0)	28 730 (6.0)	448 (6.9)	280 (7.2)	29 458 (6.0)
March to May 2022	114 323 (8.3)	1110 (7.4)	1401 (9.8)	116 834 (8.3)	36 985 (7.8)	509 (7.9)	337 (8.7)	37 81 (7.8%)
June to August 2020	96 457 (7.0)	1731 (11.5)	938 (6.6)	99 126 (7.0)	17 368 (3.6)	248 (3.8)	169 (4.4)	17 785 (3.6)
June to August 2021	135 823 (9.8)	1431 (9.5)	1477 (10.3)	138 731 (9.8)	26 162 (5.5)	409 (6.3)	268 (6.9)	26 839 (5.5)
June to August 2022	83 688 (6.0)	958 (6.4)	1336 (9.3)	85 982 (6.1)	51 659 (10.8)	757 (11.7)	456 (11.8)	52 872 (10.8)
September to November 2020	140 935 (10.2)	1798 (12.0)	1506 (10.5)	144 239 (10.2)	32 030 (6.7)	408 (6.3)	224 (5.8)	32 662 (6.7)
September to November 2021	217 656 (15.7)	1645 (11.0)	1556 (10.9)	220 857 (15.6)	49 458 (10.4)	630 (9.7)	409 (10.6)	50 497 (10.4)
September to November 2022	132 831 (9.6)	1216 (8.1)	1393 (9.7)	135 440 (9.6)	26 934 (5.6)	422 (6.5)	272 (7.0)	27 628 (5.7)
December 2020 to February 2021	135 978 (9.8)	1673 (11.2)	1341 (9.4)	138 992 (9.8)	51 601 (10.8)	665 (10.3)	356 (9.2)	52 622 (10.8)
December 2021 to February 2022	162 338 (11.7)	1346 (9.0)	1387 (9.7)	165 071 (11.7)	151 326 (31.7)	1891 (29.2)	979 (25.3)	154 196 (31.6)
Obesity
Absent	722 415 (52.2)	7439 (49.6)	7852 (54.9)	737 706 (52.2)	214 869 (45.0)	2723 (42.0)	1910 (49.4)	219 502 (45.0)
Present	497 849 (36.0)	7541 (50.3)	4836 (33.8)	510 226 (36.1)	206 568 (43.3)	3759 (58.0)	1567 (40.6)	211 894 (43.5)
Unknown	163 200 (11.8)	19 (0.1)	1617 (11.3)	164 836 (11.7)	55 594 (11.7)	1 (0.02)	387 (10.0)	55 982 (11.5)
Chronic disease status
No chronic condition	1 006 146 (72.7)	2840 (18.9)	6272 (43.8)	1 015 258 (71.9)	351 288 (73.6)	1283 (19.8)	1641 (42.5)	354 212 (72.7)
Noncomplex chronic condition	220 119 (15.9)	3280 (21.9)	2400 (16.8)	225 799 (16.0)	75 835 (15.9)	1403 (21.6)	585 (15.1)	77 823 (16.0)
Complex chronic condition comorbidities	157 199 (11.4)	8879 (59.2)	5633 (39.4)	171 711 (12.2)	49 908 (10.5)	3797 (58.6)	1638 (42.4)	55 343 (11.4)
No. of tests
0	1 049 258 (75.8)	9026 (60.2)	9148 (63.9)	1 067 432 (75.6)	291 958 (61.2)	2415 (37.3)	1916 (49.6)	296 289 (60.8)
1	218 747 (15.8)	2818 (18.8)	2534 (17.7)	224 099 (15.9)	101 336 (21.2)	1459 (22.5)	709 (18.3)	103 504 (21.2)
2	66 084 (4.8)	1316 (8.8)	1059 (7.4)	68 459 (4.8)	41 027 (8.6)	844 (13.0)	360 (9.3)	42 231 (8.7)
≥3	49 375 (3.6)	1839 (12.3)	1564 (10.9)	52 778 (3.7)	42 710 (9.0)	1765 (27.2)	879 (22.7)	45 354 (9.3)
No. of vaccine doses
0	1 248 073 (90.2)	12 690 (84.6)	13 165 (92.0)	1 273 928 (90.2)	416 466 (87.3)	5189 (80.0)	3399 (88.0)	425 054 (87.2)
1	25 661 (1.9)	417 (2.8)	260 (1.8)	26 338 (1.9)	12 185 (2.6)	288 (4.4)	135 (3.5)	12 608 (2.6)
≥2	109 730 (7.9)	1892 (12.6)	880 (6.2)	112 502 (8.0)	48 380 (10.1)	1006 (15.5)	330 (8.5)	49 716 (10.2)
No. of drugs
0	379 837 (27.5)	355 (2.4)	2029 (14.2)	382 221 (27.1)	117 622 (24.7)	124 (1.9)	529 (13.7)	118 275 (24.3)
1	173 275 (12.5)	393 (2.6)	1040 (7.3)	174 708 (12.4)	59 593 (12.5)	182 (2.8)	258 (6.7)	60 033 (12.3)
2	136 222 (9.8)	490 (3.3)	898 (6.3)	137 610 (9.7)	49 144 (10.3)	181 (2.8)	228 (5.9)	49 553 (10.2)
≥3	694 130 (50.2)	13 761 (91.7)	10 338 (72.3)	718 229 (50.8)	250 672 (52.5)	5996 (92.5)	2849 (73.7)	259 517 (53.2)

Open in a new tab

Abbreviations: AKI, acute kidney injury; CKD, chronic kidney disease.

^{^a}

AKI indicates occurring during acute phase of COVID-19 infection; CKD, stage 2 or higher.

^{^b}

Includes no information, refused to answer, or unknown from electronic health record concept source values.

Incidence and Risk of Postacute Kidney Outcomes

Table 2 presents the incidence of individual and composite postacute kidney outcomes in the COVID-19–positive cohort compared with the COVID-19–negative cohort, stratified by preexisting kidney health status. Notably, for kidney outcomes within the postacute phase, the incidence among COVID-19–positive patients was higher than that among COVID-19–negative patients for all outcomes across all 3 strata.

Table 2. Rate of Individual and Composite Kidney Outcomes.

Outcome by preexisting kidney health status^a	Rate, person-years, No. (%) of total follow-up time
Outcome by preexisting kidney health status^a	COVID-19 positive	COVID-19 negative
AKI
Composite (days 90-179)	206 (11.03)	477 (6.86)
eGFR decline of ≥50% (days 90-179)	88 (4.67)	191 (2.73)
eGFR decline of ≥40% (days 90-179)	129 (6.87)	312 (4.47)
eGFR decline of ≥30% (days 90-179)	203 (10.87)	477 (6.86)
Composite (days 180-729)	370 (6.74)	796 (3.66)
eGFR decline of ≥50% (days 180-729)	162 (2.88)	308 (1.39)
eGFR decline of ≥40% (days 180-729)	256 (4.60)	516 (2.35)
eGFR decline of ≥30% (days 180-729)	365 (6.64)	796 (3.66)
CKD stage 2 or higher (days 28-729)	194 (3.48)	505 (2.31)
CKD stage 2 or higher (majority not returned to 90 mL/min/1.73 m²) (days 28-729)	175 (3.13)	442 (2.02)
CKD stage 2 or higher (not returned to 90 mL/min/1.73 m²) (days 28-729)	159 (2.83)	399 (1.82)
CKD stage 3 or higher (days 28-729)	62 (1.09)	117 (0.53)
CKD stage 3 or higher (majority not returned to 90 mL/min/1.73 m²) (days 28-729)	53 (0.93)	93 (0.42)
CKD stage 3 or higher (not returned to 90 mL/min/1.73 m²) (days 28-729)	59 (1.04)	104 (0.47)
CKD stage 3 or higher (not returned to 60 mL/min/1.73 m²) (days 28-729)	50 (0.88)	87 (0.39)
CKD
Composite outcome (days 28-729)	905 (30.27)	1746 (24.94)
eGFR decline of ≥50% (days 28-729)	191 (6.10)	405 (5.58)
eGFR decline of ≥40% (days 28-729)	484 (15.77)	957 (13.40)
eGFR decline of ≥30% (days 28-729)	894 (30.02)	1746 (25.07)
Composite outcome (days 180-729)	1167 (13.16)	2516 (11.04)
eGFR decline of ≥50% (days 180-729)	246 (2.60)	575 (2.38)
eGFR decline of ≥40% (days 180-729)	615 (6.69)	1345 (5.69)
eGFR decline of ≥30% (days 180-729)	1159 (13.06)	2516 (11.04)
No AKI or CKD
CKD stage 2 or higher (days 28-729)	1569 (0.22)	3900 (0.18)
CKD stage 2 or higher (majority not returned to ≥90 mL/min/1.73 m²) (days 28-729)	1354 (0.19)	3265 (0.15)
CKD stage 2 or higher (not returned to 90 mL/min/1.73 m²) (days 28-729)	1250 (0.18)	2909 (0.13)
CKD stage 3 or higher (days 28-729)	132 (0.02)	309 (0.01)
CKD stage 3 or higher (majority not returned to ≥90 mL/min/1.73 m²) (days 28-729)	98 (0.01)	224 (0.01)
CKD stage 3 or higher (not returned to 90 mL/min/1.73 m²) (days 28-729)	111 (0.02)	271 (0.01)
CKD stage 3 or higher (not returned to 60 mL/min/1.73 m²) (days 28-729)	88 (0.01)	200 (0.01)

Open in a new tab

Abbreviations: AKI, acute kidney injury; CKD, chronic kidney disease.

^{^a}

AKI indicates occurring during acute phase of COVID-19 infection.

Figure 2 shows the risks of postacute kidney manifestations of SARS-CoV-2 infection, stratified by preexisting kidney health status. For patients without preexisting CKD, our findings indicate increased risks in several postacute kidney outcomes following SARS-CoV-2 infection. The risk of new-onset CKD stage 2 or higher between days 28 and 729 was increased with an HR of 1.17 (95% CI, 1.12-1.22), and the HR for CKD stage 2 or higher with eGFR never returning to 90 mL/min/1.73 m² or greater was 1.20 (95% CI, 1.13-1.28). For the outcome of CKD stage 3 or higher during days 28 to 729, the HR was 1.35 (95% CI, 1.13-1.62); for CKD stage 3 or higher without return of eGFR to 60 mL/min/1.73 m² or greater, the HR was 1.35 (95% CI, 1.15-1.59).

For patients with preexisting CKD, we observed increased risks of post–SARS-CoV-2 infection in several outcomes. Specifically, there was an increased risk of the composite kidney outcome between days 28 and 179, with an HR of 1.15 (95% CI, 1.04-1.27), as well as an HR of 1.14 (95% CI, 1.06-1.22) for days 180 to 729. Additionally, an increase in risk was found for an eGFR decline of at least 30% between days 28 and 179, with an HR of 1.14 (95% CI, 1.03-1.25); for an eGFR decline of at least 30% between days 180 and 729, the HR was 1.13 (95% CI, 1.05-1.20). These findings indicate a heightened risk for kidney function decline in individuals with preexisting CKD following COVID-19 infection.

For patients who experienced AKI during the acute phase of SARS-CoV-2 infection, the study results indicate increased risks during the postacute phases. The HR for the composite kidney outcome was 1.29 (95% CI, 1.21-1.38) for days 90 to 179 and 1.33 (95% CI, 1.21-1.47) for days 180 to 729. There was an increased risk for an eGFR decline of at least 50% in both the earlier postacute phase (HR, 1.47; 95% CI, 1.06-2.03) and the later postacute phase (HR, 1.42; 95% CI, 1.31-1.55). There was an increased risk for an eGFR decline of at least 40% in both the earlier postacute phase (HR, 1.24; 95% CI, 1.10-1.41) and the later postacute phase (HR 1.41; 95% CI, 1.21-1.63). Additionally, an increased risk was observed for an eGFR decline of at least 30% at an HR of 1.27 (95% CI, 1.20-1.36) for days 28 to 179 and remained high at 1.31 (95% CI, 1.20-1.43) for days 180 to 729. These findings highlight a sustained increased risk for adverse kidney outcomes in patients with AKI after COVID-19.

To address residual confounding, we conducted sensitivity analyses to stratify patients by age (eAppendix 10 in Supplement 1), sex (eAppendix 5 in Supplement 1), race and ethnicity (eAppendix 6 in Supplement 1), hospitalization status (eAppendix 8 in Supplement 1), obesity defined using 95th percentile or greater for age and sex (eAppendix 7 in Supplement 1), dominant variant periods (eAppendix 4 in Supplement 1), and COVID infection severity levels (eAppendix 9 in Supplement 1). Our findings remained consistent and robust.

Discussion

Principal Findings

In this population-based study, using a cohort of 1 900 146 patients younger than 21 years in the US, our results found an increase in the risk of various kidney outcomes associated with COVID-19 infection. This heightened risk includes a new onset of mild-to-moderate CKD during the postacute phase of the infection. For patients with preexisting CKD and patients who experienced AKI during the acute phase, we observed an increased risk of a composite outcome of at least 50% eGFR decline, eGFR of 15 mL/min/1.73 m² or less, dialysis, kidney transplant, or ESKD diagnosis.

Comparison With Other Studies

Our findings align with prior research indicating that COVID-19 infection elevates the risk of kidney outcomes.^{7,11,12,13,14,22} Many of these earlier studies were limited by insufficient sample sizes for precise estimations and restricted their risk assessments to specific outcomes, such as AKI, and time frames.^{7,11,12,13,14} Our results are also consistent with a study that used the US Department of Veterans Affairs national health care databases (n = 1 726 683) to examine the risk of adverse kidney outcomes in the postacute phase following infection.¹⁰ Bowe et al¹⁰ observed a significantly higher risk of adverse kidney outcomes among COVID-19–infected individuals, including eGFR decline of at least 30% (adjusted HR [AHR], 1.25; 95% CI, 1.14-1.37), at least 40% (AHR, 1.44; 95% CI, 1.37-1.51), and at least 50% (AHR, 1.62; 95% CI, 1.51-1.74) and ESKD (AHR, 2.96; 95% CI, 2.49-3.51). Our study uniquely focused on children and adolescents, extending the evaluation of risk into the chronic phase beyond the postacute period. We also included additional outcomes of new-onset CKD. In addition, we stratified the patients based on their preexisting kidney function status to examine the association of SARS-CoV-2 infection with adverse kidney outcomes.

Interpretation

The precise mechanisms underlying the observed associations in our study remain unclear. One plausible explanation could be attributed to the direct impact of COVID-19 on the kidneys, evidenced by the persistence of SARS-CoV-2 in tissues and prolonged virus shedding.^23,24 Concurrently, the chronic inflammation induced by COVID-19 infection might adversely affect hemodynamic stability, potentially leading to kidney injury.²⁵ An alternative explanation may lie in the therapeutic interventions used to manage severe COVID-19 cases,²⁵ as well as the broader economic and social conditions resulting from the pandemic.^26,27 Further investigations are warranted to elucidate the intricate pathways through which these factors interplay, contributing to the observed associations in our study.

Limitations

Our study has certain limitations. First, while we successfully achieved a balanced distribution of baseline covariates through propensity score stratification, the propensity scores were constructed using only the variables accessible within our study databases. Nevertheless, it is important to highlight that our findings remained consistent and robust through sensitivity analyses aimed at addressing residual confounding. Patients were stratified by age, sex, race and ethnicity, hospitalization status, obesity defined using 95th percentile or greater for age and sex, dominant variant periods, and COVID infection severity levels.

Second, misclassification might exist for both AKI and CKD outcomes. For AKI, if no baseline information was available, we could potentially classify someone with underlying CKD as having AKI. For long-term outcomes, we could potentially capture multiple episodes of AKI as CKD. However, our various definitions of CKD tried to mitigate this possibility.

A third potential limitation is that it is difficult to ascertain from this study whether the increased risk associated with COVID-19 infection in the group with preexisting CKD is inherently due to the COVID-19 infection itself or whether the increased risk reflects a more general risk that patients with preexisting CKD who become ill may see a negative impact on eGFR. However, the findings in the AKI group and the groups with no AKI or CKD raise the possibility that there is an inherent risk in the COVID-19 infection itself.

Fourth, patients with positive home testing results (ie, with antigen testing available in 2021 and 2022) that would not be accessible or visible in the EHR could inadvertently be incorporated into the COVID-19–negative control group. However, this would also serve to bias toward the null hypothesis and would only strength the conclusion of the increased risk of CKD from PASC. However, patients with hospital-based testing may have been more ill from COVID-19 than those patients with positive home testing results, and this could also be a potential bias or limitation of these data.

Last, future studies could adopt dynamic exposure designs, such as matching exposed cases with initially uninfected individuals who may later contract COVID-19. Additionally, they could evaluate the cumulative impact of recurrent infections on kidney function (eAppendix 16 in Supplement 1).

Conclusions

This cohort study of more than 1.9 million US children and adolescents, leveraging data from 19 health institutions in US, represents, to our knowledge, one of the most comprehensive investigations into the long-term kidney outcomes of SARS-CoV-2 infection in pediatric populations. Results of this study suggest that SARS-CoV-2 infection is associated with an increased risk of adverse kidney outcomes, including new-onset CKD and worsening kidney function, particularly among children with preexisting CKD or acute-phase AKI, underscoring the importance of long-term monitoring for kidney health in children and adolescents affected by COVID-19.

Supplement 1.

eAppendix 1. Data and Methods Description

eAppendix 2. Study Variable Specifications

eAppendix 3. Patient Characteristic Balance Between Groups in Primary Analysis

eAppendix 4. Sensitivity Analysis for Subvariants

eAppendix 5. Sensitivity Analysis for Sex

eAppendix 6. Sensitivity Analysis for Race and Ethnicity

eAppendix 7. Sensitivity Analysis for Subgroups With and Without Obesity

eAppendix 8. Sensitivity Analysis for Subgroups With Different Hospitalization Status

eAppendix 9. Sensitivity Analysis for Subgroups With Different Levels of COVID-19 Severity

eAppendix 10. Sensitivity Analysis for Subgroups With Different Age Group

eAppendix 11. Sensitivity Analysis for AKI Subgroup Without Excluding Patients With Dialysis During Acute Phase

eAppendix 12. Sensitivity Analysis for AKI Subgroup Using the Lowest Creatinine Measurement Within 90 Days Before the Index Date as the Baseline

eAppendix 13. Sensitivity Analysis for CKD Subgroup Without Excluding Patients With ESKD During Baseline

eAppendix 14. More Detailed Version of Table 1 Including Site Information and Detailed Breakdown of Age Distribution

eAppendix 15. More Detailed Version of Figure 1, Including Variations of Definitions of CKD Stage 2 or Higher and CKD Stage 3 or Higher

eAppendix 16. Recurrent COVID-19 Infections and Outcomes

jamanetwopen-e254129-s001.pdf^{(26.6MB, pdf)}

Supplement 2.

Nonauthor Collaborators. The RECOVER Consortium

jamanetwopen-e254129-s002.pdf^{(138.1KB, pdf)}

Supplement 3.

Data Sharing Statement

jamanetwopen-e254129-s003.pdf^{(13KB, pdf)}

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