Personalised recommendations for hospitalised patients with Acute Kidney Injury using a Kidney Action Team (KAT-AKI): protocol and early data of a randomised controlled trial.

INTRODUCTION: Although studies have examined the utility of clinical decision support tools in improving acute kidney injury (AKI) outcomes, no study has evaluated the effect of real-time, personalised AKI recommendations. This study aims to assess the impact of individualised AKI-specific recommendations delivered by trained clinicians and pharmacists immediately after AKI detection in hospitalised patients. METHODS AND ANALYSIS: KAT-AKI is a multicentre randomised investigator-blinded trial being conducted across eight hospitals at two major US hospital systems planning to enrol 4000 patients over 3 years (between 1 November 2021 and 1 November 2024). A real-time electronic AKI alert system informs a dedicated team composed of a physician and pharmacist who independently review the chart in real time, screen for eligibility and provide combined recommendations across the following domains: diagnostics, volume, potassium, acid-base and medications. Recommendations are delivered to the primary team in the alert arm or logged for future analysis in the usual care arm. The planned primary outcome is a composite of AKI progression, dialysis and mortality within 14 days from randomisation. A key secondary outcome is the percentage of recommendations implemented by the primary team within 24 hours from randomisation. The study has enrolled 500 individuals over 8.5 months. Two-thirds were on a medical floor at the time of the alert and 17.8% were in an intensive care unit. Virtually all participants were recommended for at least one diagnostic intervention. More than half (51.6%) had recommendations to discontinue or dose-adjust a medication. The median time from AKI alert to randomisation was 28 (IQR 15.8-51.5) min. ETHICS AND DISSEMINATION: The study was approved by the ethics committee of each study site (Yale University and Johns Hopkins institutional review board (IRB) and a central IRB (BRANY, Biomedical Research Alliance of New York). We are committed to open dissemination of the data through clinicaltrials.gov and sharing of data on an open repository as well as publication in a peer-reviewed journal on completion. TRIAL REGISTRATION NUMBER: NCT04040296.

Relationship between COVID-19 care and burnout among postgraduate clinical residents in Japan: a nationwide cross-sectional study.

OBJECTIVE: The relationship between the care of patients with COVID-19 and mental health among resident physicians in Japan is imperative for ensuring appropriate care of patients with COVID-19 and should be clarified. We herein assessed the relationship between the care of patients with COVID-19 and mental health among postgraduate year 1 (PGY-1) and PGY-2 resident physicians and factors associated with mental health. DESIGN: This nationwide cross-sectional study analysed data obtained using the clinical training environment self-reported questionnaire. SETTING: An observational study across Japan among resident physicians (PGY-1 and PGY-2) from 583 teaching hospitals. PARTICIPANTS: Examinees who took the general medicine in-training examination of academic year 2020. PRIMARY AND SECONDARY OUTCOME MEASURES: The Patient Health Questionnaire and Mini-Z 2.0 were used to assess mental health, and experience of caring for patients with COVID-19 was divided into three groups (none, 1-10 and ≥11). The prevalence of mental conditions in the three groups was compared using the 'modified' Poisson generalised estimating equations by adjusting for prefecture-level, hospital-level and resident-level variables. RESULTS: Of the 5976 participants analysed, 50.9% were PGY-1. The prevalence of burnout was 21.4%. Moreover, 47.0% of all resident physicians had no experience in the care of patients with COVID-19. The well-experienced group accounted for only 7.9% of the total participants. A positive association was found between the number of caring patients with COVID-19 and burnout (prevalence ratio 1.25; 95% CI 1.02 to 1.53). Moreover, the shortage of personal protective equipment was identified as a major contributor to burnout (prevalence ratio 1.60; 95% CI 1.36 to 1.88). CONCLUSIONS: Resident physicians who experienced more care of patients with COVID-19 had slightly greater burnout prevalence than those who did not. Approximately half of resident physicians did not participate in the care of patients with COVID-19, which posed a challenge from an educational perspective.

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.

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.

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.

A neutrophil activation signature predicts critical illness and mortality in COVID-19.

Pathologic immune hyperactivation is emerging as a key feature of critical illness in COVID-19, but the mechanisms involved remain poorly understood. We carried out proteomic profiling of plasma from cross-sectional and longitudinal cohorts of hospitalized patients with COVID-19 and analyzed clinical data from our health system database of more than 3300 patients. Using a machine learning algorithm, we identified a prominent signature of neutrophil activation, including resistin, lipocalin-2, hepatocyte growth factor, interleukin-8, and granulocyte colony-stimulating factor, which were the strongest predictors of critical illness. Evidence of neutrophil activation was present on the first day of hospitalization in patients who would only later require transfer to the intensive care unit, thus preceding the onset of critical illness and predicting increased mortality. In the health system database, early elevations in developing and mature neutrophil counts also predicted higher mortality rates. Altogether, these data suggest a central role for neutrophil activation in the pathogenesis of severe COVID-19 and identify molecular markers that distinguish patients at risk of future clinical decompensation.

The Association of COVID-19 With Acute Kidney Injury Independent of Severity of Illness: A Multicenter Cohort Study.

RATIONALE & OBJECTIVE: Although coronavirus disease 2019 (COVID-19) has been associated with acute kidney injury (AKI), it is unclear whether this association is independent of traditional risk factors such as hypotension, nephrotoxin exposure, and inflammation. We tested the independent association of COVID-19 with AKI. STUDY DESIGN: Multicenter, observational, cohort study. SETTING & PARTICIPANTS: Patients admitted to 1 of 6 hospitals within the Yale New Haven Health System between March 10, 2020, and August 31, 2020, with results for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) testing via polymerase chain reaction of a nasopharyngeal sample. EXPOSURE: Positive test for SARS-CoV-2. OUTCOME: AKI by KDIGO (Kidney Disease: Improving Global Outcomes) criteria. ANALYTICAL APPROACH: Evaluated the association of COVID-19 with AKI after controlling for time-invariant factors at admission (eg, demographic characteristics, comorbidities) and time-varying factors updated continuously during hospitalization (eg, vital signs, medications, laboratory results, respiratory failure) using time-updated Cox proportional hazard models. RESULTS: Of the 22,122 patients hospitalized, 2,600 tested positive and 19,522 tested negative for SARS-CoV-2. Compared with patients who tested negative, patients with COVID-19 had more AKI (30.6% vs 18.2%; absolute risk difference, 12.5% [95% CI, 10.6%-14.3%]) and dialysis-requiring AKI (8.5% vs 3.6%) and lower rates of recovery from AKI (58% vs 69.8%). Compared with patients without COVID-19, patients with COVID-19 had higher inflammatory marker levels (C-reactive protein, ferritin) and greater use of vasopressors and diuretic agents. Compared with patients without COVID-19, patients with COVID-19 had a higher rate of AKI in univariable analysis (hazard ratio, 1.84 [95% CI, 1.73-1.95]). In a fully adjusted model controlling for demographic variables, comorbidities, vital signs, medications, and laboratory results, COVID-19 remained associated with a high rate of AKI (adjusted hazard ratio, 1.40 [95% CI, 1.29-1.53]). LIMITATIONS: Possibility of residual confounding. CONCLUSIONS: COVID-19 is associated with high rates of AKI not fully explained by adjustment for known risk factors. This suggests the presence of mechanisms of AKI not accounted for in this analysis, which may include a direct effect of COVID-19 on the kidney or other unmeasured mediators. Future studies should evaluate the possible unique pathways by which COVID-19 may cause AKI.