Risk of COVID-19 breakthrough infection and hospitalization in individuals with comorbidities.

BACKGROUND: The successful development of multiple COVID-19 vaccines has led to a global vaccination effort to reduce severe COVID-19 infection and mortality. However, the effectiveness of the COVID-19 vaccines wane over time leading to breakthrough infections where vaccinated individuals experience a COVID-19 infection. Here we estimate the risks of breakthrough infection and subsequent hospitalization in individuals with common comorbidities who had completed an initial vaccination series. METHODS: Our study population included vaccinated patients between January 1, 2021 to March 31, 2022 who are present in the Truveta patient population. Models were developed to describe 1) time from completing primary vaccination series till breakthrough infection; and 2) if a patient was hospitalized within 14 days of breakthrough infection. We adjusted for age, race, ethnicity, sex, and year-month of vaccination. RESULTS: Of 1,218,630 patients in the Truveta Platform who had completed an initial vaccination sequence between January 1, 2021 and March 31, 2022, 2.85, 3.42, 2.75, and 2.88 percent of patients with CKD, chronic lung disease, diabetes, or are in an immunocompromised state experienced breakthrough infection, respectively, compared to 1.46 percent of the population without any of these four comorbidities. We found an increased risk of breakthrough infection and subsequent hospitalization in individuals with any of the four comorbidities when compared to individuals without these four comorbidities. CONCLUSIONS: Vaccinated individuals with any of the studied comorbidities experienced an increased risk of breakthrough COVID-19 infection and subsequent hospitalizations compared to the people without any of the studied comorbidities. Individuals with immunocompromising conditions and chronic lung disease were most at risk of breakthrough infection, while people with CKD were most at risk of hospitalization following breakthrough infection. Patients with multiple comorbidities have an even greater risk of breakthrough infection or hospitalization compared to patients with none of the studied comorbidities. Individuals with common comorbidities should remain vigilant against infection even if vaccinated.

Racial inequality in COVID-treatment and in-hospital length of stay in the US over time.

Introduction: Demonstrated health inequalities persist in the United States. SARS-CoV-2 (COVID) has been no exception, with access to treatment and hospitalization differing across race or ethnic groups. Here, we aim to assess differences in treatment with remdesivir and hospital length of stay across the four waves of the pandemic. Materials and methods: Using a subset of the Truveta data, we examine the odds ratio (OR) of in-hospital remdesivir treatment and risk ratio (RR) of in-hospital length of stay between Black or African American (Black) to White patients. We adjusted for confounding factors, such as age, sex, and comorbidity status. Results: There were statistically significant lower rates of remdesivir treatment and longer in-hospital length of stay comparing Black patients to White patients early in the pandemic (OR for treatment: 0.88, 95% confidence interval [CI]: 0.80, 0.96; RR for length of stay: 1.17, CI: 1.06, 1.21). Rates became close to parity between groups as the pandemic progressed. Conclusion: While inpatient remdesivir treatment rates increased and length of stay decreased over the beginning course of the pandemic, there are still inequalities in patient care.

Effect of Androgen-Androgen Receptor Directed Therapy on COVID-19 Outcome in Prostate Cancer Patients.

TMPRSS2 is utilized by SARS-CoV-2 for cellular entry. Androgen-Androgen receptor directed therapy (A/ARDT) downregulates expression of TMPRSS2. We hypothesized A/ARDT might protect prostate cancer (PCa) patients from poor COVID-19 outcome. A retrospective analysis of PCa patients with COVID-19 infection was performed. 146 PCa cases were identified, 17% were on A/ARDT. Hospitalization rates were same 52% (OR = 0.99, 0.41-2.24). Mean hospitalization was 9.2 (Range: 1-25) and 14.9 (Range: 2-47) days in A/ARDT and non-A/ARDT groups, respectively. While definitive conclusions cannot be made regarding outcome differences between groups due to lack of statistical significance, these data generate hypothesis that A/ARDT might shorten hospitalization stay.

A Comparison Study of Coronavirus Disease 2019 Outcomes in Hospitalized Kidney Transplant Recipients.

Background: Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) can infect any human host, but kidney transplant recipients (KTR) are considered more susceptible on the basis of previous experience with other viral infections. We evaluated rates of hospital complications between SARS-CoV-2-positive KTR and comparator groups. Methods: We extracted data from the electronic health record on patients who were hospitalized with SARS-CoV-2, testing at six hospitals from March 4 through September 9, 2020. We compared outcomes between SARS-CoV-2-positive KTR and controls: SARS-CoV-2-positive non-KTR, SARS-CoV-2-negative KTR, and SARS-CoV-2-negative non-KTR. Results: Of 31,540 inpatients, 3213 tested positive for SARS-CoV-2. There were 32 SARS-CoV-2-positive and 224 SARS-CoV-2-negative KTR. SARS-CoV-2-positive KTR had higher ferritin levels (1412; interquartile range, 748-1749 versus 553; interquartile range, 256-1035; P<0.01) compared with SARS-CoV-2-positive non-KTR. SARS-CoV-2-positive KTR had higher rates of ventilation (34% versus 14%, P<0.01; versus 9%, P<0.01; versus 5%, P<0.01), vasopressor use (41% versus 16%, P<0.01; versus 17%, P<0.01; versus 12%, P<0.01), and AKI (47% versus 15%, P<0.01; versus 23%, P<0.01; versus 10%, P<0.01) compared with SARS-CoV-2-positive non-KTR, SARS-CoV-2-negative KTR, and SARS-CoV-2-negative non-KTR, respectively. SARS-CoV-2-positive KTR continued to have increased odds of ventilation, vasopressor use, and AKI compared with SARS-CoV-2-positive non-KTR independent of Elixhauser score, Black race, and baseline eGFR. Mortality was not significantly different between SARS-CoV-2-positive KTR and non-KTR, but there was a notable trend toward higher mortality in SARS-CoV-2-positive KTR (25% versus 16%, P=0.15, respectively). Conclusions: Hospitalized SARS-CoV-2-positive KTR had a high rate of mortality and hospital complications, such as requiring ventilation, vasopressor use, and AKI. Additionally, they had higher odds of hospital complications compared with SARS-CoV-2-positive non-KTR after adjusting for Elixhauser score, Black race, and baseline eGFR. Future studies with larger sample size of KTR are needed to validate our findings. Podcast: This article contains a podcast at https://dts.podtrac.com/redirect.mp3/www.asn-online.org/media/podcast/K360/2021_03_25_KID0005652020.mp3.

Association of AKI-D with Urinary Findings and Baseline eGFR in Hospitalized COVID-19 Patients.

Background: AKI is common in patients hospitalized with coronavirus disease 2019 (COVID-19). Risk factors for AKI requiring dialysis (AKI-D) are not fully understood. We aimed to identify risk factors associated with AKI-D and AKI not requiring dialysis (AKI-ND). Methods: We reviewed electronic health records of 3186 patients aged ≥18 years old who were hospitalized with COVID-19 across six hospitals. Patient characteristics, urinalysis findings, and inflammatory markers were analyzed for association with in-hospital AKI status (AKI-D, AKI-ND, or no AKI), and we subsequently evaluated mortality. Results: After adjustment for multiple covariates, higher baseline eGFR was associated with 30% lower odds of AKI-D and 11% lower odds of AKI-ND (for AKI-D, OR, 0.70; 95% CI, 0.64 to 0.77; for AKI-ND, OR, 0.89; 95% CI, 0.85 to 0.92). Patients with obesity and those who were Latino had increased odds of AKI-D, whereas patients with congestive heart failure or diabetes with complications had increased odds of AKI-ND. Females had lower odds of in-hospital AKI (for AKI-D, OR, 0.28; 95% CI, 0.17 to 0.46; for AKI-ND, OR, 0.83; 95% CI, 0.70 to 0.99). After adjustment for covariates and baseline eGFR, 1-4+ protein on initial urinalysis was associated with a nine-fold increase in odds of AKI-D (OR, 9.00; 95% CI, 2.16 to 37.38) and more than two-fold higher odds of AKI-ND (OR, 2.28; 95% CI, 1.66 to 3.13). Findings of 1-3+ blood and trace glucose on initial urinalysis were also associated with increased odds of both AKI-D and AKI-ND. AKI-D and AKI-ND were associated with in-hospital death (for AKI-D, OR, 2.64; 95% CI, 1.13 to 6.17; for AKI-ND, OR, 2.44; 95% CI, 1.77 to 3.35). Conclusions: Active urine sediments, even after adjustment for baseline kidney function, and reduced baseline eGFR are significantly associated with increased odds of AKI-D and AKI-ND. In-hospital AKI was associated with in-hospital death. These findings may help prognosticate patients hospitalized with COVID-19.

Association of renalase with clinical outcomes in hospitalized patients with COVID-19.

Renalase is a secreted flavoprotein with anti-inflammatory and pro-cell survival properties. COVID-19 is associated with disordered inflammation and apoptosis. We hypothesized that blood renalase levels would correspond to severe COVID-19 and survival. In this retrospective cohort study, clinicopathologic data and blood samples were collected from hospitalized COVID-19 subjects (March-June 2020) at a single institution tertiary hospital. Plasma renalase and cytokine levels were measured and clinical data abstracted from health records. Of 3,450 COVID-19 patients, 458 patients were enrolled. Patients were excluded if <18 years, or opted out of research. The primary composite outcome was intubation or death within 180 days. Secondary outcomes included mortality alone, intensive care unit admission, use of vasopressors, and CPR. Enrolled patients had mean age 64 years (SD±17), were 53% males, and 48% non-whites. Mean renalase levels was 14,108·4 ng/ml (SD±8,137 ng/ml). Compared to patients with high renalase, those with low renalase (< 8,922 ng/ml) were more likely to present with hypoxia, increased ICU admission (54% vs. 33%, p < 0.001), and cardiopulmonary resuscitation (10% vs. 4%, p = 0·023). In Cox proportional hazard model, every 1000 ng/ml increase in renalase decreased the risk of death or intubation by 5% (HR 0·95; 95% CI 0·91-0·98) and increased survival alone by 6% (HR 0·95; CI 0·90-0·98), after adjusting for socio-demographics, initial disease severity, comorbidities and inflammation. Patients with high renalase-low IL-6 levels had the best survival compared to other groups (p = 0·04). Renalase was independently associated with reduced intubation and mortality in hospitalized COVID-19 patients. Future studies should assess the pathophysiological relevance of renalase in COVID-19 disease.

Multiscale PHATE identifies multimodal signatures of COVID-19.

As the biomedical community produces datasets that are increasingly complex and high dimensional, there is a need for more sophisticated computational tools to extract biological insights. We present Multiscale PHATE, a method that sweeps through all levels of data granularity to learn abstracted biological features directly predictive of disease outcome. Built on a coarse-graining process called diffusion condensation, Multiscale PHATE learns a data topology that can be analyzed at coarse resolutions for high-level summarizations of data and at fine resolutions for detailed representations of subsets. We apply Multiscale PHATE to a coronavirus disease 2019 (COVID-19) dataset with 54 million cells from 168 hospitalized patients and find that patients who die show CD16hiCD66blo neutrophil and IFN-γ+ granzyme B+ Th17 cell responses. We also show that population groupings from Multiscale PHATE directly fed into a classifier predict disease outcome more accurately than naive featurizations of the data. Multiscale PHATE is broadly generalizable to different data types, including flow cytometry, single-cell RNA sequencing (scRNA-seq), single-cell sequencing assay for transposase-accessible chromatin (scATAC-seq), and clinical variables.

Prognostic Significance of Urinary Biomarkers in Patients Hospitalized With COVID-19.

RATIONALE & OBJECTIVE: Acute kidney injury (AKI) is common in patients with coronavirus disease 2019 (COVID-19) and associated with poor outcomes. Urinary biomarkers have been associated with adverse kidney outcomes in other settings and may provide additional prognostic information in patients with COVID-19. We investigated the association between urinary biomarkers and adverse kidney outcomes among patients hospitalized with COVID-19. STUDY DESIGN: Prospective cohort study. SETTING & PARTICIPANTS: Patients hospitalized with COVID-19 (n=153) at 2 academic medical centers between April and June 2020. EXPOSURE: 19 urinary biomarkers of injury, inflammation, and repair. OUTCOME: Composite of KDIGO (Kidney Disease: Improving Global Outcomes) stage 3 AKI, requirement for dialysis, or death within 60 days of hospital admission. We also compared various kidney biomarker levels in the setting of COVID-19 versus other common AKI settings. ANALYTICAL APPROACH: Time-varying Cox proportional hazards regression to associate biomarker level with composite outcome. RESULTS: Out of 153 patients, 24 (15.7%) experienced the primary outcome. Twofold higher levels of neutrophil gelatinase-associated lipocalin (NGAL) (HR, 1.34 [95% CI, 1.14-1.57]), monocyte chemoattractant protein (MCP-1) (HR, 1.42 [95% CI, 1.09-1.84]), and kidney injury molecule 1 (KIM-1) (HR, 2.03 [95% CI, 1.38-2.99]) were associated with highest risk of sustaining primary composite outcome. Higher epidermal growth factor (EGF) levels were associated with a lower risk of the primary outcome (HR, 0.61 [95% CI, 0.47-0.79]). Individual biomarkers provided moderate discrimination and biomarker combinations improved discrimination for the primary outcome. The degree of kidney injury by biomarker level in COVID-19 was comparable to other settings of clinical AKI. There was evidence of subclinical AKI in COVID-19 patients based on elevated injury biomarker level in patients without clinical AKI defined by serum creatinine. LIMITATIONS: Small sample size with low number of composite outcome events. CONCLUSIONS: Urinary biomarkers are associated with adverse kidney outcomes in patients hospitalized with COVID-19 and may provide valuable information to monitor kidney disease progression and recovery.

Prior Stroke and Age Predict Acute Ischemic Stroke Among Hospitalized COVID-19 Patients: A Derivation and Validation Study.

Objectives: Our objective was to identify characteristics associated with having an acute ischemic stroke (AIS) among hospitalized COVID-19 patients and the subset of these patients with a neurologic symptom. Materials and Methods: Our derivation cohort consisted of COVID-19 patients admitted to Yale-New Haven Health between January 3, 2020 and August 28, 2020 with and without AIS. We also studied a sub-cohort of hospitalized COVID-19 patients demonstrating a neurologic symptom with and without an AIS. Demographic, clinical, and laboratory results were compared between AIS and non-AIS patients in the full COVID-19 cohort and in the sub-cohort of COVID-19 patients with a neurologic symptom. Multivariable logistic regression models were built to predict ischemic stroke risk in these two COVID-19 cohorts. These 2 models were externally validated in COVID-19 patients hospitalized at a major health system in New York. We then compared the distribution of the resulting predictors in a non-COVID ischemic stroke control cohort. Results: A total of 1,827 patients were included in the derivation cohort (AIS N = 44; no AIS N = 1,783). Among all hospitalized COVID-19 patients, history of prior stroke and platelet count ≥ 200 × 1,000/µL at hospital presentation were independent predictors of AIS (derivation AUC 0.89, validation AUC 0.82), irrespective of COVID-19 severity. Among hospitalized COVID-19 patients with a neurologic symptom (N = 827), the risk of AIS was significantly higher among patients with a history of prior stroke and age <60 (derivation AUC 0.83, validation AUC 0.81). Notably, in a non-COVID ischemic stroke control cohort (N = 168), AIS patients were significantly older and less likely to have had a prior stroke, demonstrating the uniqueness of AIS patients with COVID-19. Conclusions: Hospitalized COVID-19 patients who demonstrate a neurologic symptom and have either a history of prior stroke or are of younger age are at higher risk of ischemic stroke.

Peripheral Artery Disease and COVID-19 Outcomes: Insights from the Yale DOM-CovX Registry.

Both COVID-19 infection and peripheral arterial disease (PAD) cause hypercoagulability in patients, and it remains unknown whether PAD predisposes patients to experience worse outcomes when infected with SARS-CoV-2. The Yale DOM-CovX Registry consecutively enrolled inpatients for SARS-CoV-2 between March 1, 2020, and November 10, 2020. Adjusted logistic regression models examined associations between PAD and mortality, stroke, myocardial infarction (MI), and major adverse cardiovascular events (MACE, all endpoints combined). Of the 3830 patients were admitted with SARS-CoV-2, 50.5% were female, mean age was 63.1 ± 18.4 years, 50.7% were minority race, and 18.3% (n = 693) had PAD. PAD was independently associated with increased mortality (OR = 1.45, 95% CI 1.11-1.88) and MACE (OR = 1.48, 95% CI 1.16-1.87). PAD was not independently associated with stroke (P = 0.06) and MI (P = 0.22). Patients with PAD have a >40% odds of mortality and MACE when admitted with a SARS-CoV-2, independent of known risk factors.

A distinct association of inflammatory molecules with outcomes of COVID-19 in younger versus older adults.

Aging can alter immunity affecting host defense. COVID-19 has the most devastating clinical outcomes in older adults, raising the implication of immune aging in determining its severity and mortality. We investigated biological predictors for clinical outcomes in a dataset of 13,642 ambulatory and hospitalized adult COVID-19 patients, including younger (age < 65, n = 566) and older (age ≥ 65, n = 717) subjects, with in-depth analyses of inflammatory molecules, cytokines and comorbidities. Disease severity and mortality in younger and older adults were associated with discrete immune mechanisms, including predominant T cell activation in younger adults, as measured by increased soluble IL-2 receptor alpha, and increased IL-10 in older adults although both groups also had shared inflammatory processes, including acute phase reactants, contributing to clinical outcomes. These observations suggest that progression to severe disease and death in COVID-19 may proceed by different immunologic mechanisms in younger versus older subjects and introduce the possibility of age-based immune directed therapies.

The Impact of Baseline A1C and Admission Glucose on Mortality among Patients with Diabetes Hospitalized with COVID-19

We sought to determine the associations between hemoglobin A1c (A1c) and admission glucose with in-hospital mortality among patients with diabetes mellitus (DM) hospitalized with COVID-19. Adults hospitalized between 3/5/20 and 12/1/20 in a Connecticut health care system were included if they had prior DM diagnosis, an in-hospital A1c, and a positive RT-PCR nasopharyngeal swab for SARS-CoV-2. A1c was stratified into <7%, 7-<9%, and ≥9%. Both bivariate and multi-variable adjusted logistic regression analyses were performed to determine the association of A1c categories and admission glucose >200 mg/dL with mortality (in-hospital death or transition to hospice) and with intensive care unit (ICU) use. Models were adjusted for demographics and 8 relevant comorbidities. Among 733 patients (median age 67 years [interquartile range, 56-77], 48.3% female, 43.11% White, 35.47% Black, 24.97% Hispanic, 1.64% Asian), 31.7% had A1c <7%, 40.5% 7-<9%, 27.8% ≥9%, and 38.1% admission glucose >200 mg/dL. During hospitalization, 111 (15.1%) patients died or transitioned to hospice and 230 (31.4%) required ICU care. In 2 multi-variable adjusted analyses, neither A1c category nor high admission glucose were significantly associated with mortality (A1c 7-<9%: OR 0.89, 95% CI 0.53-1.49;A1c >9% OR 1.3, CI 0.72-2.35 compared with A1c <7%;glucose >200 OR 1.34, CI 0.72-2.35) or ICU care (A1c 7-<9% OR 1.30, 95% CI 0.88-1.93;A1c ≥9% OR 1.35, CI 0.86-2.1 compared with A1c <7%;glucose >200 OR 1.26, CI 0.9-1.78). Age (per year OR 1.06, CI 1.04-1.08), male sex (OR 1.78, CI 1.14-2.81), obesity (OR 1.85, CI 1.16-2.96) and CKD (OR 1.90, CI 1.19-3.03) were significantly associated with mortality. Only female sex (OR 0.67, CI 0.48-0.93) was significantly associated with ICU care. In our retrospective study of hospitalized patients with DM, neither A1c nor admission glucose were prognostic of COVID-19 mortality or ICU care. In those with DM, male sex, obesity and CKD predicted worse outcomes.

Challenges in interpreting cytokine data in COVID-19 affect patient care and management.

Challenges in using cytokine data are limiting Coronavirus Disease 2019 (COVID-19) patient management and comparison among different disease contexts. We suggest mitigation strategies to improve the accuracy of cytokine data, as we learn from experience gained during the COVID-19 pandemic.

Generating hard-to-obtain information from easy-to-obtain information: Applications in drug discovery and clinical inference.

Often when biological entities are measured in multiple ways, there are distinct categories of information: some information is easy-to-obtain information (EI) and can be gathered on virtually every subject of interest, while other information is hard-to-obtain information (HI) and can only be gathered on some. We propose building a model to make probabilistic predictions of HI using EI. Our feature mapping GAN (FMGAN), based on the conditional GAN framework, uses an embedding network to process conditions as part of the conditional GAN training to create manifold structure when it is not readily present in the conditions. We experiment on generating RNA sequencing of cell lines perturbed with a drug conditioned on the drug's chemical structure and generating FACS data from clinical monitoring variables on a cohort of COVID-19 patients, effectively describing their immune response in great detail.

Predicting patients with false negative SARS-CoV-2 testing at hospital admission: A retrospective multi-center study.

IMPORTANCE: False negative SARS-CoV-2 tests can lead to spread of infection in the inpatient setting to other patients and healthcare workers. However, the population of patients with COVID who are admitted with false negative testing is unstudied. OBJECTIVE: To characterize and develop a model to predict true SARS-CoV-2 infection among patients who initially test negative for COVID by PCR. DESIGN: Retrospective cohort study. SETTING: Five hospitals within the Yale New Haven Health System between 3/10/2020 and 9/1/2020. PARTICIPANTS: Adult patients who received diagnostic testing for SARS-CoV-2 virus within the first 96 hours of hospitalization. EXPOSURE: We developed a logistic regression model from readily available electronic health record data to predict SARS-CoV-2 positivity in patients who were positive for COVID and those who were negative and never retested. MAIN OUTCOMES AND MEASURES: This model was applied to patients testing negative for SARS-CoV-2 who were retested within the first 96 hours of hospitalization. We evaluated the ability of the model to discriminate between patients who would subsequently retest negative and those who would subsequently retest positive. RESULTS: We included 31,459 hospitalized adult patients; 2,666 of these patients tested positive for COVID and 3,511 initially tested negative for COVID and were retested. Of the patients who were retested, 61 (1.7%) had a subsequent positive COVID test. The model showed that higher age, vital sign abnormalities, and lower white blood cell count served as strong predictors for COVID positivity in these patients. The model had moderate performance to predict which patients would retest positive with a test set area under the receiver-operator characteristic (ROC) of 0.76 (95% CI 0.70-0.83). Using a cutpoint for our risk prediction model at the 90th percentile for probability, we were able to capture 35/61 (57%) of the patients who would retest positive. This cutpoint amounts to a number-needed-to-retest range between 15 and 77 patients. CONCLUSION AND RELEVANCE: We show that a pragmatic model can predict which patients should be retested for COVID. Further research is required to determine if this risk model can be applied prospectively in hospitalized patients to prevent the spread of SARS-CoV-2 infections.

Assessment of Acute Kidney Injury and Longitudinal Kidney Function After Hospital Discharge Among Patients With and Without COVID-19.

Importance: Acute kidney injury (AKI) occurs in up to half of patients hospitalized with coronavirus disease 2019 (COVID-19). The longitudinal effects of COVID-19-associated AKI on kidney function remain unknown. Objective: To compare the rate of change in estimated glomerular filtration rate (eGFR) after hospital discharge between patients with and without COVID-19 who experienced in-hospital AKI. Design, Setting, and Participants: A retrospective cohort study was conducted at 5 hospitals in Connecticut and Rhode Island from March 10 to August 31, 2020. Patients who were tested for COVID-19 and developed AKI were screened, and those who survived past discharge, did not require dialysis within 3 days of discharge, and had at least 1 outpatient creatinine level measurement following discharge were included. Exposures: Diagnosis of COVID-19. Main Outcomes and Measures: Mixed-effects models were used to assess the association between COVID-19-associated AKI and eGFR slope after discharge. The secondary outcome was the time to AKI recovery for the subgroup of patients whose kidney function had not returned to the baseline level by discharge. Results: A total of 182 patients with COVID-19-associated AKI and 1430 patients with AKI not associated with COVID-19 were included. The population included 813 women (50.4%); median age was 69.7 years (interquartile range, 58.9-78.9 years). Patients with COVID-19-associated AKI were more likely to be Black (73 [40.1%] vs 225 [15.7%]) or Hispanic (40 [22%] vs 126 [8.8%]) and had fewer comorbidities than those without COVID-19 but similar rates of preexisting chronic kidney disease and hypertension. Patients with COVID-19-associated AKI had a greater decrease in eGFR in the unadjusted model (-11.3; 95% CI, -22.1 to -0.4 mL/min/1.73 m2/y; P = .04) and after adjusting for baseline comorbidities (-12.4; 95% CI, -23.7 to -1.2 mL/min/1.73 m2/y; P = .03). In the fully adjusted model controlling for comorbidities, peak creatinine level, and in-hospital dialysis requirement, the eGFR slope difference persisted (-14.0; 95% CI, -25.1 to -2.9 mL/min/1.73 m2/y; P = .01). In the subgroup of patients who had not achieved AKI recovery by discharge (n = 319), COVID-19-associated AKI was associated with decreased kidney recovery during outpatient follow-up (adjusted hazard ratio, 0.57; 95% CI, 0.35-0.92). Conclusions and Relevance: In this cohort study of US patients who experienced in-hospital AKI, COVID-19-associated AKI was associated with a greater rate of eGFR decrease after discharge compared with AKI in patients without COVID-19, independent of underlying comorbidities or AKI severity. This eGFR trajectory may reinforce the importance of monitoring kidney function after AKI and studying interventions to limit kidney disease after COVID-19-associated AKI.