Risk Prediction for Acute Kidney Injury in Patients Hospitalized With COVID-19

Predictors of Acute Kidney Injury (AKI) among COVID-19 Patients at the US Department of Veterans Affairs: The Important Role of COVID-19 Vaccinations

BACKGROUND

There are knowledge gaps about factors associated with acute kidney injury (AKI) among COVID-19 patients. To examine AKI predictors among COVID-19 patients, a retrospective longitudinal cohort study was conducted between January 2020 and December 2022. Logistic regression models were used to examine predictors of AKI, and survival analysis was performed to examine mortality in COVID-19 patients.

RESULTS

A total of 742,799 veterans diagnosed with COVID-19 were included and 95,573 were hospitalized within 60 days following COVID-19 diagnosis. A total of 45,754 developed AKI and 28,573 AKI patients were hospitalized. Use of vasopressors (OR = 14.73; 95% CL 13.96-15.53), history of AKI (OR = 2.22; CL 2.15-2.29), male gender (OR = 1.90; CL 1.75-2.05), Black race (OR = 1.62; CL 1.57-1.65), and age 65+ (OR = 1.57; CL 1.50-1.63) were associated with AKI. Patients who were vaccinated twice and boosted were least likely to develop AKI (OR = 0.51; CL 0.49-0.53) compared to unvaccinated COVID-19 patients. Patients receiving two doses (OR = 0.77; CL = 0.72-0.81), or a single dose (OR = 0.88; CL = 0.81-0.95) were also less likely to develop AKI compared to the unvaccinated. AKI patients exhibited four times higher mortality compared to those without AKI (HR = 4.35; CL 4.23-4.50). Vaccinated and boosted patients had the lowest mortality risk compared to the unvaccinated (HR = 0.30; CL 0.28-0.31).

CONCLUSION

Use of vasopressors, being unvaccinated, older age, male gender, and Black race were associated with post COVID-19 AKI. Whether COVID-19 vaccination, including boosters, decreases the risk of developing AKI warrants additional studies.

Validation of a predictive model for hospital-acquired acute kidney injury with emergence of SARS-CoV-2 variants

We previously developed and validated a model to predict acute kidney injury (AKI) in hospitalized coronavirus disease 2019 (COVID-19) patients and found that the variables with the highest importance included a history of chronic kidney disease and markers of inflammation. Here, we assessed model performance during periods when COVID-19 cases were attributable almost exclusively to individual variants. Electronic Health Record data were obtained from patients admitted to 19 hospitals. The outcome was hospital-acquired AKI. The model, previously built in an Inception Cohort, was evaluated in Delta and Omicron cohorts using model discrimination and calibration methods. A total of 9104 patients were included, with 5676 in the Inception Cohort, 2461 in the Delta cohort, and 967 in the Omicron cohort. The Delta Cohort was younger with fewer comorbidities, while Omicron patients had lower rates of intensive care compared with the other cohorts. AKI occurred in 13.7% of the Inception Cohort, compared with 13.8% of Delta and 14.4% of Omicron (Omnibus p = 0.84). Compared with the Inception Cohort (area under the curve (AUC): 0.78, 95% confidence interval (CI): 0.76-0.80), the model showed stable discrimination in the Delta (AUC: 0.78, 95% CI: 0.75-0.80, p = 0.89) and Omicron (AUC: 0.74, 95% CI: 0.70-0.79, p = 0.37) cohorts. Estimated calibration index values were 0.02 (95% CI: 0.01-0.07) for Inception, 0.08 (95% CI: 0.05-0.17) for Delta, and 0.12 (95% CI: 0.04-0.47) for Omicron cohorts, p = 0.10 for both Delta and Omicron vs Inception. Our model for predicting hospital-acquired AKI remained accurate in different COVID-19 variants, suggesting that risk factors for AKI have not substantially evolved across variants.

Development of a Risk Score for AKI onset in COVID-19 Patients: COV-AKI Score

PURPOSE

Acute Kidney Injury (AKI) in COVID-19 patients is associated with increased morbidity and mortality. In the present study, we aimed to develop a prognostic score to predict AKI development in these patients.

MATERIALS AND METHODS

This was a retrospective observational study of 2334 COVID 19 patients admitted to 23 different hospitals in Brazil, between January 10th and August 30rd, 2020. The primary outcome of AKI was defined as any increase in serum creatinine (SCr) by 0.3 mg/dL within 48 h or a change in SCr by ≥ 1.5 times of baseline within 1 week, based on Kidney Disease Improving Global Outcomes (KDIGO) guidelines. All patients aged ≥ 18 y/o admitted with confirmed SARS-COV-2 infection were included. Discrimination of variables was calculated by the Receiver Operator Characteristic Curve (ROC curve) utilizing area under curve. Some continuous variables were categorized through ROC curve. The cutoff points were calculated using the value with the best sensitivity and specificity.

RESULTS

A total of 1131 patients with COVID-19 admitted to the ICU were included. Patients mean age was 52 ± 15,8 y/o., with a prevalence of males 60% (n = 678). The risk of AKI was 33% (n = 376), 78% (n = 293) of which did not require dialysis. Overall mortality was 11% (n = 127), while for AKI patients, mortality rate was 21% (n = 80). Variables selected for the logistic regression model and inclusion in the final prognostic score were the following: age, diabetes, ACEis, ARBs, chronic kidney disease and hypertension.

CONCLUSION

AKI development in COVID 19 patients is accurately predicted by common clinical variables, allowing early interventions to attenuate the impact of AKI in these patients.

The Texas Health Resources Clinical Scholars Program: Learning healthcare system workforce development through embedded translational research

Introduction

Texas Health Resources (THR), a large, nonprofit health care system based in the Dallas-Fort Worth area, has collaborated with the University of Texas Southwestern Medical Center (UTSW) to develop and operate a unique, integrated approach for Learning Health System (LHS) workforce development. This training model centers on academic health system faculty members conducting later-stage translational research within a partnering regional care delivery organization.

Methods

The THR Clinical Scholars Program engages early career UTSW faculty members to conduct studies that are likely to have an impact on care delivery at the health system level. Interested candidates submit formal applications to the program. A joint committee comprised of senior research faculty from UTSW and THR clinical leadership reviews proposals with a focus on the shared LHS needs of both institutions-developing high quality research output that can be applied to enhance care delivery. A key prioritization criterion for funding is the degree to which the research addresses a question relevant to THR as a high-volume network with multiple channels for consumers to access care. The program emphasis is on supporting embedded research initiatives using health system data to generate knowledge that will improve the quality and efficiency of care for the patient populations served by the participant organizations.

Results

We discuss specific strategic and tactical components of the THR Clinical Scholars Program including an overview of the academic affiliation agreement between the collaborating organizations, criteria for successful program applications, data sharing, and funding. We also share project summaries from selected clinical scholars as examples of the LHS research done in the program to date.

Conclusion

This experience report provides an implementation framework for other academic health systems interested in adopting similar LHS workforce training models with community partners.