bbSelect - An Open-Source Tool for Performing a 3D Pharmacophore-Driven Diverse Selection of R-Groups.

The design of compounds during hit-to-lead often seeks to explore a vector from a core scaffold to form additional interactions with the target protein. A rational approach to this is to probe the region of a protein accessed by a vector with a systematic placement of pharmacophore features in 3D, particularly when bound structures are not available. Herein, we present bbSelect, an open-source tool built to map the placements of pharmacophore features in 3D Euclidean space from a library of R-groups, employing partitioning to drive a diverse and systematic selection to a user-defined size. An evaluation of bbSelect against established methods exemplified the superiority of bbSelect in its ability to perform diverse selections, achieving high levels of pharmacophore feature placement coverage with selection sizes of a fraction of the total set and without the introduction of excess complexity. bbSelect also reports visualizations and rationale to enable users to understand and interrogate results. This provides a tool for the drug discovery community to guide their hit-to-lead activities.

MELLODDY: Cross-pharma Federated Learning at Unprecedented Scale Unlocks Benefits in QSAR without Compromising Proprietary Information.

Federated multipartner machine learning has been touted as an appealing and efficient method to increase the effective training data volume and thereby the predictivity of models, particularly when the generation of training data is resource-intensive. In the landmark MELLODDY project, indeed, each of ten pharmaceutical companies realized aggregated improvements on its own classification or regression models through federated learning. To this end, they leveraged a novel implementation extending multitask learning across partners, on a platform audited for privacy and security. The experiments involved an unprecedented cross-pharma data set of 2.6+ billion confidential experimental activity data points, documenting 21+ million physical small molecules and 40+ thousand assays in on-target and secondary pharmacodynamics and pharmacokinetics. Appropriate complementary metrics were developed to evaluate the predictive performance in the federated setting. In addition to predictive performance increases in labeled space, the results point toward an extended applicability domain in federated learning. Increases in collective training data volume, including by means of auxiliary data resulting from single concentration high-throughput and imaging assays, continued to boost predictive performance, albeit with a saturating return. Markedly higher improvements were observed for the pharmacokinetics and safety panel assay-based task subsets.

Factors associated with a history of acute traumatic cycling injuries in 60 941 cycling race entrants in South Africa: SAFER study XLII.

BACKGROUND: Information on acute traumatic cycling injuries (ATCIs) in the 12 months prior to entry in a cycling race and the predisposing factors have not been well-researched. OBJECTIVE: Determine factors associated with a history of ATCIs sustained in the previous 12 months by race entrants of a 109 km cycling race. METHODS: Descriptive, cross-sectional study on 60 941 Cape Town Cycle Tour race entrants from 2016 to 2020. Data on a history of ATCIs sustained in the previous 12 months were obtained through an online pre-race medical screening questionnaire (mandatory in 2016, and voluntary in 2017-2020). Factors investigated were demographics, cycling/training history and history of chronic disease, collapse, cramping, allergies and regular chronic prescription medication usage. We calculated the prevalence ratio (PR) for reporting a history of an ATCI in the previous 12 months for each category (multiple regression model). RESULTS: Factors associated with an increased PR for a history of ATCIs gathered from race entrants (34% of the total entrants) were: increased years of participation in distance cycling events >2 hours (PR=1.05 per 5 years of distance cycling, p<0.0001), increased weekly average training/racing distance of a cyclist in the past 12 months (PR=1.11 per 50 km increase in weekly cycling). Other factors were: increased number of chronic diseases reported (PR=1.53, per two additional chronic diseases reported, p<0.0001), history of collapse (PR=1.75, p=0.0005), history of cramping (PR=1.65, p<0.0001) and history of allergies (PR=1.49, p<0.0001). CONCLUSIONS: Subgroups of recreational cyclists at higher risk for ATCIs were identified. This information could assist in developing and implementing future strategies to mitigate ATCIs.

Balancing acute medical management of acute kidney injury and hyperkalaemia versus medicines optimisation for long-term Cardio-Renal-Metabolic (CaReMe) diseases: a narrative review.

Cardio-Renal-Metabolic (CaReMe) diseases, in the form of heart failure, chronic kidney disease and diabetes mellitus, justify prescription of multiple prognostically beneficial medications, specifically renin-angiotensin system inhibitors, mineralocorticoid receptor antagonists, and sodium-glucose co-transporter-2 inhibitors. Use of these medications is complicated by association with adverse effects, particularly acute kidney injury and hyperkalaemia. Balancing risk and benefit is a common dilemma in acute medicine, with increasingly frequent and complex treatment decisions. Physicians should contemplate adjustments to medications within the context of not just acute illness but also long-term benefit. In the setting of hyperkalaemia, potassium-binding medications can be utilised. At hospital discharge optimisation of therapy can be achieved through clear safety netting advice, scheduled biochemical follow-up, and planned clinical review.

A whole healthcare system mortality review of the second wave COVID-19 pandemic response, were lessons learned?

We previously reported a study of features of emergency healthcare response to COVID-19 that could be modified to mitigate against future excess deaths. Here we determined what themes persisted in later waves. This was an expert panel review of all components of care delivered to COVID-19 patients who died (primary and secondary care, community services, NHS 111 and 999, COVID oximetry at home, virtual wards). 174 deaths were included. 5% were deemed >50% avoidable, 75% included avoidability themes. Contact with primary care remains mostly via telephone, creating diagnostic risk. Patient decision to avoid healthcare contact was common. Recommendations include: better utilisation of home monitoring in future pandemics; improved avoidance of nosocomial spread; patients be encouraged to seek medical advice earlier.

Atherosclerotic Renovascular Disease: A KDIGO (Kidney Disease: Improving Global Outcomes) Controversies Conference.

The diagnosis and management of atherosclerotic renovascular disease (ARVD) is complex and controversial. Despite evidence from the ASTRAL (2009) and CORAL (2013) randomized controlled trials showing that percutaneous renal artery revascularization did not improve major outcomes compared with best medical therapy alone over 3-5 years, several areas of uncertainty remain. Medical therapy, including statin and antihypertensive medications, has evolved in recent years, and the use of renin-angiotensin-aldosterone system blockers is now considered the primary means to treat hypertension in the setting of ARVD. However, the criteria to identify kidneys with renal artery stenosis that have potentially salvageable function are evolving. There are also data suggesting that certain high-risk populations with specific clinical manifestations may benefit from revascularization. Here, we provide an overview of the epidemiology, diagnosis, and treatment of ARVD based on consensus recommendations from a panel of physician experts who attended the recent KDIGO (Kidney Disease: Improving Global Outcomes) Controversies Conference on central and peripheral arterial diseases in chronic kidney disease. Most focus is provided for contentious issues, and we also outline aspects of investigation and management of ARVD that require further research.

When and why direct transmission models can be used for environmentally persistent pathogens.

Variants of the susceptible-infected-removed (SIR) model of Kermack & McKendrick (1927) enjoy wide application in epidemiology, offering simple yet powerful inferential and predictive tools in the study of diverse infectious diseases across human, animal and plant populations. Direct transmission models (DTM) are a subset of these that treat the processes of disease transmission as comprising a series of discrete instantaneous events. Infections transmitted indirectly by persistent environmental pathogens, however, are examples where a DTM description might fail and are perhaps better described by models that comprise explicit environmental transmission routes, so-called environmental transmission models (ETM). In this paper we discuss the stochastic susceptible-exposed-infected-removed (SEIR) DTM and susceptible-exposed-infected-removed-pathogen (SEIR-P) ETM and we show that the former is the timescale separation limit of the latter, with ETM host-disease dynamics increasingly resembling those of a DTM when the pathogen's characteristic timescale is shortened, relative to that of the host population. Using graphical posterior predictive checks (GPPC), we investigate the validity of the SEIR model when fitted to simulated SEIR-P host infection and removal times. Such analyses demonstrate how, in many cases, the SEIR model is robust to departure from direct transmission. Finally, we present a case study of white spot disease (WSD) in penaeid shrimp with rates of environmental transmission and pathogen decay (SEIR-P model parameters) estimated using published results of experiments. Using SEIR and SEIR-P simulations of a hypothetical WSD outbreak management scenario, we demonstrate how relative shortening of the pathogen timescale comes about in practice. With atttempts to remove diseased shrimp from the population every 24h, we see SEIR and SEIR-P model outputs closely conincide. However, when removals are 6-hourly, the two models' mean outputs diverge, with distinct predictions of outbreak size and duration.

Ensemble Simulations and Experimental Free Energy Distributions: Evaluation and Characterization of Isoxazole Amides as SMYD3 Inhibitors.

Optimization of binding affinities for ligands to their target protein is a primary objective in rational drug discovery. Herein, we report on a collaborative study that evaluates various compounds designed to bind to the SET and MYND domain-containing protein 3 (SMYD3). SMYD3 is a histone methyltransferase and plays an important role in transcriptional regulation in cell proliferation, cell cycle, and human carcinogenesis. Experimental measurements using the scintillation proximity assay show that the distributions of binding free energies from a large number of independent measurements exhibit non-normal properties. We use ESMACS (enhanced sampling of molecular dynamics with approximation of continuum solvent) and TIES (thermodynamic integration with enhanced sampling) protocols to predict the binding free energies and to provide a detailed chemical insight into the nature of ligand-protein binding. Our results show that the 1-trajectory ESMACS protocol works well for the set of ligands studied here. Although one unexplained outlier exists, we obtain excellent statistical ranking across the set of compounds from the ESMACS protocol and good agreement between calculations and experiments for the relative binding free energies from the TIES protocol. ESMACS and TIES are again found to be powerful protocols for the accurate comparison of the binding free energies.

Managing acute presentations of atheromatous renal artery stenosis.

BACKGROUND: Atherosclerotic renovascular disease (ARVD) often follows an asymptomatic chronic course which may be undetected for many years. However, there are certain critical acute presentations associated with ARVD and these require a high index of suspicion for underlying high-grade RAS (renal artery stenosis) to improve patient outcomes. These acute presentations, which include decompensated heart failure syndromes, accelerated hypertension, rapidly declining renal function, and acute kidney injury (AKI), are usually associated with bilateral high-grade RAS (> 70% stenosis), or high-grade RAS in a solitary functioning kidney in which case the contralateral kidney is supplied by a vessel demonstrating renal artery occlusion (RAO). These presentations are typically underrepresented in large, randomized control trials which to date have been largely negative in terms of the conferred benefit of revascularization. CASE PRESENTATION: Here we describe 9 individual patients with 3 classical presentations including accelerated phase hypertension, heart failure syndromes, AKI and a fourth category of patients who suffered recurrent presentations. We describe their response to renal revascularization. The predominant presentation was that consistent with ischaemic nephropathy all of whom had a positive outcome with revascularization. CONCLUSION: A high index of suspicion is required for the diagnosis of RAS in these instances so that timely revascularization can be undertaken to restore or preserve renal function and reduce the incidence of hospital admissions for heart failure syndromes.

Community- versus hospital-acquired acute kidney injury in hospitalised COVID-19 patients.

BACKGROUND: Acute kidney injury (AKI) is a recognised complication of coronavirus disease 2019 (COVID-19), yet the reported incidence varies widely and the associated risk factors are poorly understood. METHODS: Data was collected on all adult patients who returned a positive COVID-19 swab while hospitalised at a large UK teaching hospital between 1st March 2020 and 3rd June 2020. Patients were stratified into community- and hospital-acquired AKI based on the timing of AKI onset. RESULTS: Out of the 448 eligible patients with COVID-19, 118 (26.3 %) recorded an AKI during their admission. Significant independent risk factors for community-acquired AKI were chronic kidney disease (CKD), diabetes, clinical frailty score and admission C-reactive protein (CRP), systolic blood pressure and respiratory rate. Similar risk factors were significant for hospital-acquired AKI including CKD and trough systolic blood pressure, peak heart rate, peak CRP and trough lymphocytes during admission. In addition, invasive mechanical ventilation was the most significant risk factor for hospital-acquired AKI (adjusted odds ratio 9.1, p < 0.0001) while atrial fibrillation conferred a protective effect (adjusted odds ratio 0.29, p < 0.0209). Mortality was significantly higher for patients who had an AKI compared to those who didn't have an AKI (54.3 % vs. 29.4 % respectively, p < 0.0001). On Cox regression, hospital-acquired AKI was significantly associated with mortality (adjusted hazard ratio 4.64, p < 0.0001) while community-acquired AKI was not. CONCLUSIONS: AKI occurred in over a quarter of our hospitalised COVID-19 patients. Community- and hospital-acquired AKI have many shared risk factors which appear to converge on a pre-renal mechanism of injury. Hospital- but not community acquired AKI was a significant risk factor for death.

A randomised controlled trial to examine the effects of cinacalcet on bone and cardiovascular parameters in haemodialysis patients with advanced secondary hyperparathyroidism.

BACKGROUND: Secondary hyperparathyroidism may lead to increased cardiovascular risk. The use of cinacalcet may improve bone and cardiovascular health with improved parathormone (PTH) and phosphate control. METHODS: This is an open-label prospective randomised controlled trial to compare progression of cardiovascular and chronic kidney disease mineral and bone disorder (CKD-MBD) parameters. Patients were randomised to receive cinacalcet alongside standard therapy or standard therapy alone. Thirty-six haemodialysis patients who had > 90 days on dialysis, iPTH > 300 pg/mL, calcium > 2.1 mmol/L and age 18-75 years were included. Following randomization, all 36 patients underwent an intensive 12-week period of bone disease management aiming for iPTH 150-300 pg/mL. The primary outcome was change in vascular calcification using CT agatston score. Secondary outcomes included pulse wave velocity (PWV), left ventricular mass index (LVMI), carotid intima-media thickness (CIMT), augmentation index (Aix) and bone measurements. The above measurements were obtained at baseline and 12 months. RESULTS: There was no evidence of a group difference in the progression of calcification (median change (IQR) cinacalcet: 488 (0 to1539); standard therapy: 563 (50 to 1214)). In a post hoc analysis combining groups there was a mean (SD) phosphate reduction of 0.3 mmol/L (0.7) and median (IQR) iPTH reduction of 380 pg/mL (- 754, 120). Regression of LVMI and CIMT was seen (P = 0.03 and P = 0.001) and was significantly associated with change of phosphate on multi-factorial analyses. CONCLUSIONS: With a policy of intense CKD-MBD parameter control, no significant benefit in bone and cardiovascular markers was seen with the addition of cinacalcet to standard therapy over one year. Tight control of hyperphosphataemia and secondary hyperparathyroidism may lead to a reduction in LVMI and CIMT but this needs further investigation. Although the sample size was small, meticulous trial supervision resulted in very few protocol deviations with therapy.

Search for relevant subsets of binary predictors in high dimensional regression for discovering the lead molecule.

One of the main problems that the drug discovery research field confronts is to identify small molecules, modulators of protein function, which are likely to be therapeutically useful. Common practices rely on the screening of vast libraries of small molecules (often 1-2 million molecules) in order to identify a molecule, known as a lead molecule, which specifically inhibits or activates the protein function. To search for the lead molecule, we investigate the molecular structure, which generally consists of an extremely large number of fragments. Presence or absence of particular fragments, or groups of fragments, can strongly affect molecular properties. We study the relationship between molecular properties and its fragment composition by building a regression model, in which predictors, represented by binary variables indicating the presence or absence of fragments, are grouped in subsets and a bi-level penalization term is introduced for the high dimensionality of the problem. We evaluate the performance of this model in two simulation studies, comparing different penalization terms and different clustering techniques to derive the best predictor subsets structure. Both studies are characterized by small sets of data relative to the number of predictors under consideration. From the results of these simulation studies, we show that our approach can generate models able to identify key features and provide accurate predictions. The good performance of these models is then exhibited with real data about the MMP-12 enzyme.

Consequences of the emergency response to COVID-19: a whole health care system review in a single city in the United Kingdom.

BACKGROUND: The response to the COVID-19 pandemic in the United Kingdom included large scale changes to healthcare delivery, without fully understanding the potential for unexpected effects caused by these changes. The aim was "to ascertain the characteristics of patients, uncertainty over diagnosis, or features of the emergency response to the pandemic that could be modified to mitigate against future excess deaths". METHODS: Review of the entire pathway of care of patients whose death was registered in Salford during the 8 week period of the first wave (primary care, secondary care, 111 and 999 calls) in order to create a single record of healthcare prior to death. An expert panel judged avoidability of death against the National Mortality Case Record Review Programme scale. The panel identified themes using a structured judgement review format. RESULTS: There were 522 deaths including 197 in hospital, and 190 in care homes. 51% of patients were female, 81% Caucasian, age 79 ± 9 years. Dementia was present in 35%, COVID-19 was cause of death in 44%. Healthcare contact prior to death was most frequently with primary care (81% of patients). Forty-six patients (9%) had healthcare appointments cancelled (median 1 cancellation, range 1-9). Fewer than half of NHS 111 calls were answered during this period. 18% of deaths contained themes consistent with some degree of avoidability. In people aged ≥75 years who lived at home this was 53%, in care home residents 29% and in patients with learning disability 44% (n = 9). Common themes were; delays in patients presenting to care providers (10%), delays in testing (17%), avoidable exposure to COVID-19 (26%), delays in provider response (5%), and sub-optimal care (11%). For avoidability scores of 2 or 3 (indicating more than 50% chance of avoidability), 44% of cases had > 2 themes. CONCLUSIONS: The initial emergency response had unforeseen consequences resulting in late presentation, sub-optimal assessments, and delays in receiving care. Death in more vulnerable groups was more likely to display avoidability themes.

Guidelines for Recurrent Neural Network Transfer Learning-Based Molecular Generation of Focused Libraries.

Deep learning approaches have become popular in recent years in the field of de novo molecular design. While a variety of different methods are available, it is still a challenge to assess and compare their performance. A particularly promising approach for automated drug design is to use recurrent neural networks (RNNs) as SMILES generators and train them with the learning procedure called "transfer learning". This involves first training the initial model on a large generic data set of molecules to learn the general syntax of SMILES, followed by fine-tuning on a smaller set of molecules, coming from, e.g., a lead optimization program. To create a well-performing transfer learning application which can be automated, it is important to understand how the size of the second data set affects the training process. In addition, extensive postfiltering using similarity metrics of the molecules generated after transfer learning should be avoided, as it can introduce new biases toward the selection of drug candidates. Here, we present results from the application of a gated recurrent unit cell (GRU)-RNN to transfer learning on data sets of varying sizes and complexity. Analysis of the results has allowed us to provide some general guidelines for transfer learning. In particular, we show that data set sizes containing at least 190 molecules are needed for effective GRU-RNN-based molecular generation using transfer learning. The methods presented here should be applicable generally to the benchmarking of other deep learning methodologies for molecule generation.

BRADSHAW: a system for automated molecular design.

This paper introduces BRADSHAW (Biological Response Analysis and Design System using an Heterogenous, Automated Workflow), a system for automated molecular design which integrates methods for chemical structure generation, experimental design, active learning and cheminformatics tools. The simple user interface is designed to facilitate access to large scale automated design whilst minimising software development required to introduce new algorithms, a critical requirement in what is a very fast moving field. The system embodies a philosophy of automation, best practice, experimental design and the use of both traditional cheminformatics and modern machine learning algorithms.

Correction to: BRADSHAW: a system for automated molecular design.

The original version of this article unfortunately contained some mistakes in the references.

Predictive factors of rapid linear renal progression and mortality in patients with chronic kidney disease.

BACKGROUND: Risk factors predictive of rapid linear chronic kidney disease (CKD) progression and its associations with end-stage renal disease (ESRD) and mortality requires further exploration, particularly as patients with linear estimated glomerular filtration rate (eGFR) trajectory represent a clear paradigm for understanding true CKD progression. METHODS: A linear regression slope was applied to all outpatient eGFR values for patients in the Salford Kidney Study who had ≥2 years follow-up, ≥4 eGFR values and baseline CKD stages 3a-4. An eGFR slope (ΔeGFR) of ≤ - 4 ml/min/1.73m2/yr defined rapid progressors, whereas - 0.5 to + 0.5 ml/min/1.73m2/yr defined stable patients. Binary logistic regression was utilised to explore variables associated with rapid progression and Cox proportional hazards model to determine predictors for mortality prior to ESRD. RESULTS: There were 157 rapid progressors (median ΔeGFR - 5.93 ml/min/1.73m2/yr) and 179 stable patients (median ΔeGFR - 0.03 ml/min/1.73m2/yr). Over 5 years, rapid progressors had an annual rate of mortality or ESRD of 47 per 100 patients compared with 6 per 100 stable patients. Factors associated with rapid progression included younger age, female gender, higher diastolic pressure, higher total cholesterol:high density lipoprotein ratio, lower albumin, lower haemoglobin and a urine protein:creatinine ratio of > 50 g/mol. The latter three factors were also predictive of mortality prior to ESRD, along with older age, smoking, peripheral vascular disease and heart failure. CONCLUSIONS: There is a heterogenous interplay of risk factors associated with rapid linear CKD progression and mortality in patients with CKD. Furthermore, rapid progressors have high rates of adverse outcomes and require close specialist monitoring.

Safely reducing haemodialysis frequency during the COVID-19 pandemic.

BACKGROUND: Patients undergoing haemodialysis (HD) are at higher risk of developing worse outcomes if they contract COVID-19. In our renal service we reduced HD frequency from thrice to twice-weekly in selected patients with the primary aim of reducing COVID 19 exposure and transmission between HD patients. METHODS: Dialysis unit nephrologists identified 166 suitable patients (38.4% of our HD population) to temporarily convert to twice-weekly haemodialysis immediately prior to the peak of the COVID-19 pandemic in our area. Changes in pre-dialysis weight, systolic blood pressure (SBP) and biochemistry were recorded weekly throughout the 4-week project. Hyperkalaemic patients (serum potassium > 6.0 mmol/L) were treated with a potassium binder, sodium bicarbonate and received responsive dietary advice. RESULTS: There were 12 deaths (5 due to COVID-19) in the HD population, 6 of which were in the twice weekly HD group; no deaths were definitively associated with change of dialysis protocol. A further 19 patients were either hospitalised and/or developed COVID-19 and thus transferred back to thrice weekly dialysis as per protocol. 113 (68.1%) were still receiving twice-weekly HD by the end of the 4-week project. Indications for transfer back to thrice weekly were; fluid overload (19), persistent hyperkalaemia (4), patient request (4) and compliance (1). There were statistically significant increases in SBP and pre-dialysis potassium during the project. CONCLUSIONS: Short term conversion of a large but selected HD population to twice-weekly dialysis sessions was possible and safe. This approach could help mitigate COVID-19 transmission amongst dialysis patients in centres with similar organisational pressures.

Non-alcoholic fatty liver disease and clinical outcomes in chronic kidney disease.

BACKGROUND: Non-alcoholic fatty liver disease (NAFLD) is an independent risk factor associated with cardiovascular disease (CVD) and incidence of chronic kidney disease (CKD). NAFLD is threatening to become a major public health problem in association with the metabolic syndrome. The association of NAFLD with outcomes in patients with advanced CKD has not been evaluated. In this study, the prevalence of NAFLD and its impact on cardiovascular and renal outcomes and mortality were determined in a large secondary care CKD cohort. METHODS: The study was conducted on 1148 CKD patients within a cohort of 3061 CKD patients, who had undergone ultrasound imaging of the liver over a 15-year period. A propensity-matched population from within the cohort was also included. Cox regression analysis was used to study the association of NAFLD with cardiovascular events, end-stage renal disease and mortality and linear regression analysis for CKD progression. RESULTS: The prevalence of NAFLD was 17.9%. The median duration of follow-up after scanning was 5.4 years, with a median estimated glomerular filtration rate (eGFR) of 33.5 mL/min/1.73 m2 in this population. NAFLD proved to be a strong independent risk factor for cardiovascular events [hazard ratio (HR) 2.03; 95% confidence interval (CI) 1.33-3.13; P < 0.01] but it was not associated with all-cause mortality (HR 0.79; 95% CI 0.58-1.08; P = 0.14) or CKD progression (P = 0.09 for rate of decline of eGFR slope). Patients with CKD are known to have high cardiovascular risk; the propensity-matched analysis showed that NAFLD increased this cardiovascular risk (HR 2.00; CI 1.10-3.66; P < 0.05). CONCLUSIONS: NAFLD has a strong independent association with cardiovascular events, even in an advanced CKD cohort with high comorbidity. The implication is that routine screening for NAFLD may be warranted in CKD populations to enable targeted interventions for CVD prevention in higher risk patients.

The potential of electrocardiography for cardiac risk prediction in chronic and end-stage kidney disease.

Cardiovascular mortality is very high in chronic and end-stage kidney disease (ESKD). However, risk stratification data are lacking. Sudden cardiac deaths are among the most common cardiovascular causes of death in these populations. As a result, many studies have assessed the prognostic potential of various electrocardiographic parameters in the renal population. Recent data from studies of implantable loop recordings in haemodialysis patients from five different countries have shed light on a pre-eminent bradyarrhythmic risk of mortality. Importantly, heart block addressed by permanent pacing system was detected in a proportion of patients during the prolonged recording periods. Standard electrocardiogram is inexpensive, non-invasive and easily accessible. Hence, risk prediction models using this simple investigation tool could easily translate into clinical practice. We believe that electrocardiographic assessment is currently under-valued in renal populations. For this review, we identified studies from the preceding 10 years that assessed the use of conventional and novel electrocardiographic biomarkers as risk predictors in chronic and ESKD. The review indicates that conventional electrocardiographic markers are not reliable for risk stratification in the renal populations. Novel parameters have shown promising results in smaller studies, but further validation in larger populations is required.