Background: Acute kidney injury (AKI) is common in coronavirus disease 2019 (COVID-19). This study investigated adults hospitalized with COVID-19 and hypothesized that risk factors for AKI would include comorbidities and non-White race. Methods: A prospective multicentre cohort study was performed using patients admitted to 254 UK hospitals with COVID-19 between 17 January 2020 and 5 December 2020. Results: Of 85 687 patients, 2198 (2.6%) received acute kidney replacement therapy (KRT). Of 41 294 patients with biochemistry data, 13 000 (31.5%) had biochemical AKI: 8562 stage 1 (65.9%), 2609 stage 2 (20.1%) and 1829 stage 3 (14.1%). The main risk factors for KRT were chronic kidney disease (CKD) [adjusted odds ratio (aOR) 3.41: 95% confidence interval 3.06–3.81], male sex (aOR 2.43: 2.18–2.71) and Black race (aOR 2.17: 1.79–2.63). The main risk factors for biochemical AKI were admission respiratory rate >30 breaths per minute (aOR 1.68: 1.56–1.81), CKD (aOR 1.66: 1.57–1.76) and Black race (aOR 1.44: 1.28–1.61). There was a gradated rise in the risk of 28-day mortality by increasing severity of AKI: stage 1 aOR 1.58 (1.49–1.67), stage 2 aOR 2.41 (2.20–2.64), stage 3 aOR 3.50 (3.14–3.91) and KRT aOR 3.06 (2.75–3.39). AKI rates peaked in April 2020 and the subsequent fall in rates could not be explained by the use of dexamethasone or remdesivir. Conclusions: AKI is common in adults hospitalized with COVID-19 and it is associated with a heightened risk of mortality. Although the rates of AKI have fallen from the early months of the pandemic, high-risk patients should have their kidney function and fluid status monitored closely.

BACKGROUND: Many studies have explored whether individual plasma protein biomarkers improve cardiovascular disease risk prediction. We sought to investigate the use of a plasma proteomics-based approach in predicting different cardiovascular outcomes. METHODS: Among 51 859 UK Biobank participants (mean age, 56.7 years; 45.5% male) without cardiovascular disease and with proteomics measurements, we examined the primary composite outcome of fatal and nonfatal coronary heart disease, stroke, or heart failure (major adverse cardiovascular events), as well as additional secondary cardiovascular outcomes. An exposome-wide association study was conducted using relative protein concentrations, adjusted for a range of classic, demographic, and lifestyle risk factors. A prediction model using only age, sex, and protein markers (protein model) was developed using a least absolute shrinkage and selection operator–regularized approach (derivation: 80% of cohort) and validated using split-sample testing (20% of cohort). Their performance was assessed by comparing calibration, net reclassification index, and c statistic with the PREVENT (Predicting Risk of CVD Events) risk score. RESULTS: Over a median 13.6 years of follow-up, 4857 participants experienced first major adverse cardiovascular events. After adjustment, the proteins most strongly associated with major adverse cardiovascular events included NT-proBNP (N-terminal pro B-type natriuretic peptide; hazard ratio [HR], 1.68 per SD increase), proADM (pro-adrenomedullin; HR, 1.60), GDF-15 (growth differentiation factor-15; HR, 1.47), WFDC2 (WAP four-disulfide core domain protein 2; HR, 1.46), and IGFBP4 (insulin-like growth factor-binding protein 4; HR, 1.41). In total, 222 separate proteins were predictors of all outcomes of interest in the protein model, and 86 were selected for the primary outcome specifically. In the validation cohort, compared with the PREVENT risk factor model, the protein model improved net reclassification (net reclassification index +0.09), and c statistic (+0.051) for major adverse cardiovascular events. The protein model also improved the prediction of other outcomes, including ASCVD ( c statistic +0.035), myocardial infarction (+0.023), stroke (+0.024), aortic stenosis (+0.015), heart failure (+0.060), abdominal aortic aneurysm (+0.024), and dementia (+0.068). CONCLUSIONS: Measurement of targeted protein biomarkers produced superior prediction of aggregated and disaggregated cardiovascular events. This study represents proof of concept for the application of targeted proteomics in predicting a range of cardiovascular outcomes.

Significance Statement: Reliable prediction tools are needed to personalize treatment in ANCA-associated GN. More than 1500 patients were collated in an international longitudinal study to revise the ANCA kidney risk score. The score showed satisfactory performance, mimicking the original study (Harrell's C=0.779). In the development cohort of 959 patients, no additional parameters aiding the tool were detected, but replacing the GFR with creatinine identified an additional cutoff. The parameter interstitial fibrosis and tubular atrophy was modified to allow wider access, risk points were reweighted, and a fourth risk group was created, improving predictive ability (C=0.831). In the validation, the new model performed similarly well with excellent calibration and discrimination (n=480, C=0.821). The revised score optimizes prognostication for clinical practice and trials. Background: Reliable prediction tools are needed to personalize treatment in ANCA-associated GN. A retrospective international longitudinal cohort was collated to revise the ANCA renal risk score. Methods: The primary end point was ESKD with patients censored at last follow-up. Cox proportional hazards were used to reweight risk factors. Kaplan–Meier curves, Harrell's C statistic, receiver operating characteristics, and calibration plots were used to assess model performance. Results: Of 1591 patients, 1439 were included in the final analyses, 2:1 randomly allocated per center to development and validation cohorts (52% male, median age 64 years). In the development cohort (n=959), the ANCA renal risk score was validated and calibrated, and parameters were reinvestigated modifying interstitial fibrosis and tubular atrophy allowing semiquantitative reporting. An additional cutoff for kidney function (K) was identified, and serum creatinine replaced GFR (K0: 450 µmol/L=11 points). The risk points for the percentage of normal glomeruli (N) and interstitial fibrosis and tubular atrophy (T) were reweighted (N0: >25%=0, N1: 10%–25%=4, N2: <10%=7, T0: none/mild or <25%=0, T1: ≥ mild-moderate or ≥25%=3 points), and four risk groups created: low (0–4 points), moderate (5–11), high (12–18), and very high (21). Discrimination was C=0.831, and the 3-year kidney survival was 96%, 79%, 54%, and 19%, respectively. The revised score performed similarly well in the validation cohort with excellent calibration and discrimination (n=480, C=0.821). Conclusions: The updated score optimizes clinicopathologic prognostication for clinical practice and trials.

Bleeding is a recognized complication of native percutaneous renal biopsy. This study aimed to describe the incidence of major bleeding after biopsy in a single centre over a 15-year period and examine factors associated with major bleeding. We identified consecutive adult patients undergoing ultrasound-guided native renal biopsy in the Glasgow Renal and Transplant Unit from 2000 to 2014. From the electronic patient record, we collected data pertaining to biopsy indication, pre- and post-biopsy laboratory measurements, prescribed medication and diagnosis. Aspirin was routinely continued. We defined major bleeding post-biopsy as the need for blood transfusion, surgical or radiological intervention or death. Binary logistic regression analysis was used to assess factors associated with increased risk of major bleeding. There were 2563 patients who underwent native renal biopsy (1499 elective, 1064 emergency). The average age of patients was 57 (SD 17) years and 57.4% were male. Overall, the rate of major bleeding was 2.2%. In all, 46 patients required transfusion (1.8%), 9 patients underwent embolization (0.4%), no patient required nephrectomy and 1 patient died as a result of a significant late retroperitoneal bleed. Major bleeding was more common in those undergoing emergency compared with elective renal biopsy (3.4 versus 1.1%; P < 0.001). Aspirin was being taken at the time of biopsy in 327 of 1509 patients, with no significant increase in the risk of major bleeding (P = 0.93). Body mass index (BMI) data were available for 546 patients, with no increased risk of major bleeding in 207 patients classified as obese (BMI >30). The risk of major bleeding following native renal biopsy in the modern era is low. Complications are more common when biopsy is conducted as an emergency, which has implications for obtaining informed consent. Our data support the strategy of not stopping aspirin before renal biopsy.

Cancer is the second leading cause of death in people with chronic kidney disease (CKD) after cardiovascular disease. The incidence of CKD in patients with cancer is higher than in the non-cancer population. Across various populations, CKD is associated with an elevated risk of cancer incidence and cancer death compared with people without CKD, although the risks are cancer site-specific. Higher risk of cancer is detectable in mild CKD [estimated glomerular filtration rate (eGFR) 60–89 mL/min/1.73 m²], although this risk is more obvious if sensitive markers of kidney disease are used, such as cystatin C. Independent of eGFR, albuminuria is associated with increased risk of site-specific cancer incidence and death. Here, we explore the potential mechanisms for the increased risk of cancer observed in CKD, including patient factors (shared risks such as cardiometabolic disease, obesity, smoking, diet, lifestyle and environment), disease (genetic, inflammatory and infective) and treatment factors. In particular, we discuss the ways in which renal adverse events associated with conventional chemotherapies and newer systemic anti-cancer therapies (including targeted and immunotherapies) may contribute to worse cancer outcomes in people with CKD. Finally, we review the potential benefits of acknowledging increased risk of cancer in risk prediction tools used for the management of CKD.