Use of an extended KDIGO definition to diagnose acute kidney injury in patients with COVID-19: A multinational study using the ISARIC-WHO clinical characterisation protocol

Epidemiology of acute kidney injury in the clinical emergency: A prospective cohort study at a high-complexity public university hospital in São Paulo, Brazil

INTRODUCTION

Southern Hemisphere countries have been underrepresented in epidemiological studies on acute kidney injury (AKI). The objectives of this study were to determine the frequency, risk factors, and outcomes of AKI in adult hospitalized patients from the emergency department of a public high-complexity teaching hospital in the city of São Paulo, Brazil.

METHODS

Observational and prospective study. AKI was defined by the KDIGO guidelines (Kidney Disease: Improving Global Outcomes) using only serum creatinine.

RESULTS

Among the 731 patients studied (age: median 61 years, IQR 47-72 years; 55% male), 48% had hypertension and 28% had diabetes as comorbidities. The frequency of AKI was 52.1% (25.9% community-based AKI [C-AKI] and 26.3% hospital-acquired AKI [H-AKI]). Dehydration, hypotension, and edema were found in 29%, 15%, and 15% of participants, respectively, at hospital admission. The in-hospital and 12-month mortality rates of patients with vs. without AKI were 25.2% vs. 11.1% (p<0.001) and 36.7% vs. 12.9% (p<0.001), respectively. The independent risk factors for C-AKI were chronic kidney disease (CKD), chronic liver disease, age, and hospitalization for cardiovascular disease. Those for H-AKI were CKD, heart failure as comorbidities, hypotension, and edema at hospital admission. H-AKI was an independent risk factor for death in the hospital, but not at 12 months. C-AKI was not a risk factor for death.

CONCLUSIONS

AKI occurred in more than half of the admissions to the clinical emergency department of the hospital and was equally distributed between C-AKI and H-AKI. Many patients had correctable risk factors for AKI, such as dehydration and arterial hypotension (44%) at admission. The only independent risk factor for both C-AKI and H-AKI was CKD as comorbidity.

Biomarkers vs Machines: The Race to Predict Acute Kidney Injury

BACKGROUND

Acute kidney injury (AKI) is a serious complication affecting up to 15% of hospitalized patients. Early diagnosis is critical to prevent irreversible kidney damage that could otherwise lead to significant morbidity and mortality. However, AKI is a clinically silent syndrome, and current detection primarily relies on measuring a rise in serum creatinine, an imperfect marker that can be slow to react to developing AKI. Over the past decade, new innovations have emerged in the form of biomarkers and artificial intelligence tools to aid in the early diagnosis and prediction of imminent AKI.

CONTENT

This review summarizes and critically evaluates the latest developments in AKI detection and prediction by emerging biomarkers and artificial intelligence. Main guidelines and studies discussed herein include those evaluating clinical utilitiy of alternate filtration markers such as cystatin C and structural injury markers such as neutrophil gelatinase-associated lipocalin and tissue inhibitor of metalloprotease 2 with insulin-like growth factor binding protein 7 and machine learning algorithms for the detection and prediction of AKI in adult and pediatric populations. Recommendations for clinical practices considering the adoption of these new tools are also provided.

SUMMARY

The race to detect AKI is heating up. Regulatory approval of select biomarkers for clinical use and the emergence of machine learning algorithms that can predict imminent AKI with high accuracy are all promising developments. But the race is far from being won. Future research focusing on clinical outcome studies that demonstrate the utility and validity of implementing these new tools into clinical practice is needed.

Association of body mass index with perioperative blood transfusion and short-term clinical outcomes in patients undergoing isolated coronary artery bypass grafting

BACKGROUND

Few studies have considered outcomes among low body mass index (BMI) cohorts undergoing coronary artery bypass grafting (CABG). This study aims to investigate the effects of low body weight on blood transfusion and perioperative outcomes in patients undergoing isolated CABG.

METHODS

This retrospective study enrolled consecutive cases from a single-center between January 2008 and December 2018. Low body weight/underweight was defined as a BMI < 18.5 kg/m², while normal BMI was defined as 18.5 ≤ BMI < 24.0 kg/m². The primary endpoint was the perioperative red blood cell (RBC) transfusion rate. Secondary endpoints include platelet and plasma transfusion rates, transfusion volume for all blood components, hospital length of stay, and the occurrence of adverse events including prolonged mechanical ventilation, re-intubation, re-operation, acute kidney injury, and 30-day all-cause mortality.

RESULTS

A total of 7,620 patients were included in this study. After 1:1 propensity score matching, 130 pairs were formed, with 61 pairs in the on-pump group and 69 pairs in the off-pump group. Baseline characteristics were comparable between the matched groups. Low body weight independently increased the risk of RBC transfusion (on-pump: OR = 3.837, 95% CI = 1.213-12.144, p = 0.022; off-pump: OR = 3.630, 95% CI = 1.875-5.313, p < 0.001). Moreover, within the on-pump group of the original cohort, BMI of < 18.5 kg/m² was independently correlated with increased risk of re-intubation (OR = 5.365, 95% CI = 1.159 to 24.833, p = 0.032), re-operation (OR = 4.650, 95% CI = 1.019 to 21.210, p = 0.047), and 30-day all-cause mortality (OR = 10.325, 95% CI = 2.011 to 53.020, p = 0.005).

CONCLUSION

BMI < 18.5 kg/m² was identified as an independent risk factor for increased perioperative RBC transfusion rate in patient underwent isolated CABG with or without CPB. Only on-pump underweight patients in the original cohort exhibited an increased risk for re-intubation, re-operation, and 30-day all-cause mortality. Physicians and healthcare systems should consider these findings to improve management for this population.

Factors associated with acute kidney injury (AKI) and mortality in COVID-19 patients in a Sub-Saharan African intensive care unit: a single-center prospective study

INTRODUCTION

Acute kidney injury (AKI) is a complication of severe coronavirus disease 2019 (COVID-19). Kidney damage associated with COVID-19 could take specific features due to environmental and socio-cultural factors. This study evaluates the incidence of AKI, the associated factors, and mortality in COVID-19 patients in a Sub-Saharan African intensive care unit.

METHODS

In a prospective cohort study conducted in the intensive care unit (ICU) of the Centre Médical de Kinshasa (CMK), consecutive patients admitted for COVID-19 were screened for the presence of AKI between 27 March, 2020 and 27 January 2022. AKI was defined according to Kidney Disease Improving Global Outcomes (KDIGO) guidelines. The primary outcome was occurrence of AKI. The secondary outcome was 48 days' mortality and recovery of the renal function at intensive care unit (ICU) discharge. Survival (time-to death) curves were built using the Kaplan Meier methods. Multivariate analyses were performed by logistic regression to identify factors associated with AKI and Cox regression to explore the association between AKI and in-hospital mortality. The significance level of the p-value was set at 0.05.

RESULTS

The median(IQR) sequential organ failure assessment score (SOFA) score and mean age of patients (215) including in our cohort were respectively 3(2-4) and 58.9 ± 14.9 years. The incidence of AKI was 28.4% with stages 1, 2, or 3 AKI accounted for 39.3%, 11.5%, and 49.2%, respectively. Hemodialysis was required in 16 out 215 (7.4%) patients. Dyspnea (adjusted odds ratio (aOR):2.27 [1.1--4.57] p = 0.021), SOFA ≥5 (aOR:3.11[1.29-7.53] p = 0.012), AST/ALT ratio (aOR: 1.53 [1.09-1.79] p = 0.015), N/L ratio (aOR:2.09 [1.09-3.20] p = 0.016), mechanical ventilation (aOR: 3.20 [1.66-10.51] p = 0.005) and Amikacin (aOR: 2.91 [1.37-6.18] p = 0.006) were the main factors associated with AKI. Patients with AKI had a mortality rate of 52.5% and 67.2% of the survivors did not recover kidney function at the end of hospitalization. Adjusted Cox regression analysis revealed that COVID-19-associated AKI was independently associated with in-hospital death (HR:2.96 [1.93-4.65] p = 0.013) compared to non-AKI patients.

CONCLUSIONS

AKI was present in three out of ten COVID-19 patients. The most significant factors associated with AKI were dyspnea, SOFA ≥ 5, AST/ALT and N/L ratio, mechanical ventilation and Amikacin. AKI has been associated with an almost threefold increase in overall mortality and seven out of ten survivors did not recover kidney function after AKI.

Clinical Features and Predictive Nomogram of Acute Kidney Injury in Aging Population Infected with SARS-CoV-2 Omicron Variant

Background

Since little is known about the acute kidney injury (AKI) in aging population infected with SARS-CoV-2 Omicron variant, we investigated the incidence, clinical features, risk factors and mid-term outcomes of AKI in hospitalized geriatric patients with and without COVID-19 and established a prediction model for mortality.

Methods

A real-time data from the Shanghai Ninth People's Hospital information system of inpatients with COVID-19 from 1 April 2022 to 30 June 2022 were extracted. Clinical spectrum, laboratory results, and clinical prognosis were included for the risk analyses. Moreover, Cox and Lasso regression analyses were applied to predict the 90-day death and a nomogram was established.

Results

A total of 1607 SARS-CoV-2 infected patients were enrolled; hypertension was the most common comorbidity, followed by chronic cardiovascular disease, diabetes mellitus, and lung disease. Most of the participants were non-vaccinated and the mean age of patients was 82.6 years old (range, 60-103 years). The AKI incidence was higher in relatively older patients (16.29% vs 3.63% in patients older than 80 years and 60 to 80 years, respectively). Linear regression models identified some variables associated with the incidence of AKI, such as older age, clinical spectrum, D-dimer level, number of comorbidities, baseline eGFR, and antibiotic or corticosteroid treatment. In this cohort, 11 patients died in-hospital and 21 patients died at 90-day follow-up. The predictive nomogram of 90-day death achieved a good C-index of 0.823 by using 5 predictor variables: ICU admission, D-dimer, peak of serum creatinine, rate of serum creatinine decline and white blood cell count (WBC).

Conclusion

Older age, clinical spectrum, D-dimer level, number of comorbidities, baseline eGFR, and antibiotic or corticosteroid treatment are clinical risk factors for the incidence of AKI in geriatric COVID-19 patients. The prediction nomogram achieved an excellent performance at the prediction of 90-day mortality.

Association of Country Income Level With the Characteristics and Outcomes of Critically Ill Patients Hospitalized With Acute Kidney Injury and COVID-19

Introduction

Acute kidney injury (AKI) has been identified as one of the most common and significant problems in hospitalized patients with COVID-19. However, studies examining the relationship between COVID-19 and AKI in low- and low-middle income countries (LLMIC) are lacking. Given that AKI is known to carry a higher mortality rate in these countries, it is important to understand differences in this population.

Methods

This prospective, observational study examines the AKI incidence and characteristics of 32,210 patients with COVID-19 from 49 countries across all income levels who were admitted to an intensive care unit during their hospital stay.

Results

Among patients with COVID-19 admitted to the intensive care unit, AKI incidence was highest in patients in LLMIC, followed by patients in upper-middle income countries (UMIC) and high-income countries (HIC) (53%, 38%, and 30%, respectively), whereas dialysis rates were lowest among patients with AKI from LLMIC and highest among those from HIC (27% vs. 45%). Patients with AKI in LLMIC had the largest proportion of community-acquired AKI (CA-AKI) and highest rate of in-hospital death (79% vs. 54% in HIC and 66% in UMIC). The association between AKI, being from LLMIC and in-hospital death persisted even after adjusting for disease severity.

Conclusions

AKI is a particularly devastating complication of COVID-19 among patients from poorer nations where the gaps in accessibility and quality of healthcare delivery have a major impact on patient outcomes.

Outcomes of COVID-19 patients with acute kidney injury and longitudinal analysis of laboratory markers during the hospital stay: A multi-center retrospective cohort experience from Pakistan

The frequency of acute kidney injury (AKI) in COVID-19 patients can be varied and related to worse outcomes in the disease population. AKI is common among hospitalized patients with COVID-19, particularly the ones needing critical care. This study was conducted in order to determine the outcomes of hospitalized patients with prolonged hospital stays who suffered from COVID-19 associated AKI. It was conducted as a multi-centered, retrospective, cohort study, and including all patients who were diagnosed on COVID-19 PCR. End-stage renal disease patients on hemodialysis were excluded. The cohort included 1069 patients, with 68% males, mean age of 56.21 years, and majority within 50 to 75 years age group (60%). Mean disease onset was 14.43 ± 7.44 days and hospital stay was 7.01 ± 5.78 days. About 62% of patients stayed in intensive care and 18% of them were on invasive ventilation. The mortality rate was 27%. Frequency of AKI was 42%, around 14% of them were resolving during hospital stay and other 28% worsened. The mortality rate was significantly higher with AKI (OR: 4.7, P < .001). Alongside AKI, concomitant liver dysfunction was also significantly contributing to mortality (OR: 2.5), apart from ICU stay (OR: 2.9), invasive ventilation (OR: 9.2), and renal replacement therapy (OR: 2.4). Certain laboratory markers were associated with AKI throughout in-hospital stay.

COVID-19 and Kidney Disease: Progress in Health Inequity From Low-Income Settings

The acute coronavirus disease-2019 (COVID-19) pandemic has had a significant impact on the incidence and prevalence of acute kidney injury and chronic kidney disease globally and in low-income settings. Chronic kidney disease increases the risk of developing COVID-19 and COVID-19 causes acute kidney injury directly or indirectly and is associated with high mortality in severe cases. Outcomes of COVID-19-associated kidney disease were not equitable globally owing to a lack of health infrastructure, challenges in diagnostic testing, and management of COVID-19 in low-income settings. COVID-19 also significantly impacted kidney transplant rates and mortality among kidney transplant recipients. Vaccine availability and uptake remains a significant challenge in low- and lower-middle-income countries compared with high-income countries. In this review, we explore the inequities in low- and lower-middle-income countries and highlight the progress made in the prevention, diagnosis, and management of patients with COVID-19 and kidney disease. We recommend further studies into the challenges, lessons learned, and progress made in the diagnosis, management, and treatment of patients with COVID-19-related kidney diseases and suggest ways to improve the care and management of patients with COVID-19 and kidney disease.

ISARIC-COVID-19 dataset: A Prospective, Standardized, Global Dataset of Patients Hospitalized with COVID-19

The International Severe Acute Respiratory and Emerging Infection Consortium (ISARIC) COVID-19 dataset is one of the largest international databases of prospectively collected clinical data on people hospitalized with COVID-19. This dataset was compiled during the COVID-19 pandemic by a network of hospitals that collect data using the ISARIC-World Health Organization Clinical Characterization Protocol and data tools. The database includes data from more than 705,000 patients, collected in more than 60 countries and 1,500 centres worldwide. Patient data are available from acute hospital admissions with COVID-19 and outpatient follow-ups. The data include signs and symptoms, pre-existing comorbidities, vital signs, chronic and acute treatments, complications, dates of hospitalization and discharge, mortality, viral strains, vaccination status, and other data. Here, we present the dataset characteristics, explain its architecture and how to gain access, and provide tools to facilitate its use.