Improving outcomes in atherosclerotic renovascular disease: importance of clinical presentation and multi-disciplinary review.

BACKGROUND AND OBJECTIVES: Atherosclerotic renal artery stenosis may cause hypertension, chronic kidney disease and heart failure, but large randomized control trials to date have shown no major additional benefit of renal revascularization over optimal medical management. However, these trials did not consider outcomes specifically in relation to clinical presentations. Given that atherosclerotic renal artery stenosis is a heterogenous condition, measures of success likely differ according to the clinical presentation. Our retrospective study objectives were to determine the effects of revascularization when applied to specific clinical presentations and after careful multi-disciplinary team review. METHODS: All patients presenting to our centre and its referring hospitals with radiological findings of at least one renal artery stenosis > 50% between January 2015 and January 2020 were reviewed at the renovascular multi-disciplinary team meeting with revascularization considered in accordance with international guidelines, notably for patients with anatomically significant renal artery stenosis, adequately sized kidney and presentations with any of; deteriorating kidney function, heart failure syndrome, or uncontrollable hypertension. Optimal medical management was recommended for all patients which included lipid lowering agents, anti-platelets and anti-hypertensives targeting blood pressure ≤ 130/80 mmHg. The effect of revascularization was assessed according to the clinical presentation; blood pressure and number of agents in those with renovascular hypertension, delta glomerular filtration rate in those with ischaemic nephropathy and heart failure re-admissions in those with heart failure syndromes. RESULTS: During this 5-year period, 127 patients with stenosis ≥ 50% were considered by the multidisciplinary team, with 57 undergoing revascularization (17 primarily for severe hypertension, 25 deteriorating kidney function, 6 heart failure syndrome and 9 for very severe anatomical stenosis). Seventy-nine percent of all revascularized patients had a positive outcome specific to their clinical presentation, with 82% of those with severe hypertension improving blood pressure control, 72% with progressive ischaemic nephropathy having attenuated GFR decline, and no further heart failure admissions in those with heart failure. Seventy-eight percent of patients revascularized for high grade stenosis alone had better blood pressure control with 55% also manifesting renal functional benefits. CONCLUSIONS: Multi-disciplinary team discussion successfully identified a group of patients more likely to benefit from revascularization based on 3 key factors: clinical presentation, severity of the renal artery lesion and the state of the kidney beyond the stenotic lesion. In this way, a large proportion of patients can clinically improve after revascularization if their outcomes are considered according to the nature of their clinical presentation.

Estimating blue mussel (Mytilus edulis) connectivity and settlement capacity in mid-latitude fjord regions.

The mussel industry faces challenges such as low and inconsistent levels of larvae settlement and poor-quality spat, leading to variable production. However, mussel farming remains a vital sustainable and environmentally responsible method for producing protein, fostering ecological responsibility in the aquaculture sector. We investigate the population connectivity and larval dispersion of blue mussels (Mytilus edulis) in Scottish waters, as a case study, using a multidisciplinary approach that combined genetic data and particle modelling. This research allows us to develop a thorough understanding of blue mussel population dynamics in mid-latitude fjord regions, to infer gene-flow patterns, and to estimate population divergence. Our findings reveal a primary south-to-north particle transport direction and the presence of five genetic clusters. We discover a significant and continuous genetic material exchange among populations within the study area, with our biophysical model's outcomes aligning with our genetic observations. Additionally, our model reveals a robust connection between the southwest coast and the rest of the west coast. This study will guide the preservation of mussel farming regions, ensuring sustainable populations that contribute to marine ecosystem health and resilience.

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.

Improving outpatient clinic experience: the future of chronic kidney disease care and associated multimorbidity.

BACKGROUND: Chronic kidney disease (CKD) is estimated to affect more than 2.5 million adults in England, and this is expected to rise to 4.2 million by 2036 (1). Population-level digital healthcare systems have the potential to enable earlier detection of CKD providing an opportunity to introduce interventions that attenuate progression and reduce the risk of end-stage kidney disease (ESKD) and cardiovascular diseases (CVD). Services that can support patients with CKD, CVD, and diabetes mellitus (DM) have the potential to reduce fragmented clinical care and optimise pharmaceutical management. METHODS AND RESULTS: The Salford renal service has established an outpatient improvement programme which aims to address these issues via two projects. Firstly, the development of a CKD dashboard that can stratify patients by their kidney failure risk equation (KFRE) risk. High-risk patients would be invited to attend an outpatient clinic if appropriate. Specialist advice and guidance would be offered to primary care providers looking after patients with medium risk. Patients with lower risk would continue with standard care via their primary care provider unless there was another indication for a nephrology referral. The CKD dashboard identified 11546 patients (4.4% of the total adult population in Salford) with T2DM and CKD. The second project is the establishment of the Metabolic CardioRenal (MRC) clinic. It provided care for 209 patients in the first 8 months of its establishment with a total of 450 patient visits. Initial analysis showed clustering of cardiorenal metabolic diseases with 85% having CKD stages 3 and 4 and 73.2% having DM. In addition, patients had a significant burden of CVD with 50.2% having hypertension and 47.8% having heart failure. CONCLUSION: There is a pressing need to create new outpatient models of care to tackle the rising epidemic of cardio-renal metabolic diseases. This model of service has potential benefits at both organisational and patient levels including improving patient management via risk stratification, increased care capacity and reduction of variation of care. Patients will benefit from earlier intervention, appropriate referral for care, reduction in CKD-related complications, and reduction in hospital visits and cardiovascular events. In addition, this combined digital and patient-facing model of care will allow rapid translation of advances in cardio-renal metabolic diseases into clinical practice.

Predicting acute clinical deterioration with interpretable machine learning to support emergency care decision making.

The emergency department (ED) is a fast-paced environment responsible for large volumes of patients with varied disease acuity. Operational pressures on EDs are increasing, which creates the imperative to efficiently identify patients at imminent risk of acute deterioration. The aim of this study is to systematically compare the performance of machine learning algorithms based on logistic regression, gradient boosted decision trees, and support vector machines for predicting imminent clinical deterioration for patients based on cross-sectional patient data extracted from electronic patient records (EPR) at the point of entry to the hospital. We apply state-of-the-art machine learning methods to predict early patient deterioration, based on their first recorded vital signs, observations, laboratory results, and other predictors documented in the EPR. Clinical deterioration in this study is measured by in-hospital mortality and/or admission to critical care. We build on prior work by incorporating interpretable machine learning and fairness-aware modelling, and use a dataset comprising 118, 886 unplanned admissions to Salford Royal Hospital, UK, to systematically compare model variations for predicting mortality and critical care utilisation within 24 hours of admission. We compare model performance to the National Early Warning Score 2 (NEWS2) and yield up to a 0.366 increase in average precision, up to a [Formula: see text] reduction in daily alert rate, and a median 0.599 reduction in differential bias amplification across the protected demographics of age and sex. We use Shapely Additive exPlanations to justify the models' outputs, verify that the captured data associations align with domain knowledge, and pair predictions with the causal context of each patient's most influential characteristics. Introducing our modelling to clinical practice has the potential to reduce alert fatigue and identify high-risk patients with a lower NEWS2 that might be missed currently, but further work is needed to trial the models in clinical practice. We encourage future research to follow a systematised approach to data-driven risk modelling to obtain clinically applicable support tools.

The estimation of glomerular filtration in acute and critical illness: Challenges and opportunities.

Recent events have made it apparent that the creatinine based estimating equations for glomerular filtration have their flaws. Some flaws have been known for some time; others have prompted radical modification of the equations themselves. These issues persist in part owing to the behaviour of the creatinine molecule itself, particularly in acute and critical illness. There are significant implications for patient treatment decisions, including drug and fluid therapies and choice of imaging modality (contrast vs. non-contrast CT scan for example). An alternative biomarker, Cystatin C, has been used with some success both alone and in combination with creatinine to help improve the accuracy of particular estimating equations. Problems remain in certain circumstances and costs may limit the more widespread use of the alternative assay. This review will explore both the historical and more recent evidence for glomerular filtration estimation, including options to directly measure glomerular filtration (rather than estimate), perhaps the holy grail for both Biochemistry and Nephrology.

An Artificial Neural Network for Nasogastric Tube Position Decision Support.

Purpose: To develop and validate a deep learning model for detection of nasogastric tube (NGT) malposition on chest radiographs and assess model impact as a clinical decision support tool for junior physicians to help determine whether feeding can be safely performed in patients (feed/do not feed). Materials and Methods: A neural network ensemble was pretrained on 1 132 142 retrospectively collected (June 2007-August 2019) frontal chest radiographs and further fine-tuned on 7081 chest radiographs labeled by three radiologists. Clinical relevance was assessed on an independent set of 335 images. Five junior emergency medicine physicians assessed chest radiographs and made feed/do not feed decisions without and with artificial intelligence (AI)-generated NGT malposition probabilities placed above chest radiographs. Decisions from the radiologists served as ground truths. Model performance was evaluated using receiver operating characteristic analysis. Agreement between junior physician and radiologist decision was determined using the Cohen κ coefficient. Results: In the testing set, the ensemble achieved area under the receiver operating characteristic curve values of 0.82 (95% CI: 0.78, 0.86), 0.77 (95% CI: 0.71, 0.83), and 0.98 (95% CI: 0.96, 1.00) for satisfactory, malpositioned, and bronchial positions, respectively. In the clinical evaluation set, mean interreader agreement for feed/do not feed decisions among junior physicians was 0.65 ± 0.03 (SD) and 0.77 ± 0.13 without and with AI support, respectively. Mean agreement between junior physicians and radiologists was 0.53 ± 0.05 (unaided) and 0.65 ± 0.09 (AI-aided). Conclusion: A simple classifier for NGT malposition may help junior physicians determine the safety of feeding in patients with NGTs.Keywords: Neural Networks, Feature Detection, Supervised Learning, Machine Learning Supplemental material is available for this article. Published under a CC BY 4.0 license.

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.

Antihypertensive prescribing patterns in non-dialysis dependent chronic kidney disease: Findings from the Salford Kidney Study.

BACKGROUND: Hypertension is commonly observed in patients living with chronic kidney disease (CKD). Finding an optimal treatment regime remains challenging due to the complex bidirectional cause-and-effect relationship between hypertension and CKD. There remains variability in antihypertensive treatment practices. AIM: To analyze data from the Salford Kidney Study database in relation to antihypertensive prescribing patterns amongst CKD patients. METHODS: The Salford Kidney Study is an ongoing prospective study that has been recruiting CKD patients since 2002. All patients are followed up annually, and their medical records including the list of medications are updated until they reach study endpoints [starting on renal replacement therapy or reaching estimated glomerular filtration rate (eGFR) expressed as mL/min/1.73 m2 ≤ 10 mL/min/1.73 m2, or the last follow-up date, or data lock on December 31, 2021, or death]. Data on antihypertensive prescription practices in correspondence to baseline eGFR, urine albumin-creatinine ratio, primary CKD aetiology, and cardiovascular disease were evaluated. Associations between patients who were prescribed three or more antihypertensive agents and their clinical outcomes were studied by Cox regression analysis. Kaplan-Meier analysis demonstrated differences in survival probabilities. RESULTS: Three thousand two hundred and thirty non-dialysis-dependent CKD patients with data collected between October 2002 and December 2019 were included. The median age was 65 years. A greater proportion of patients were taking three or more antihypertensive agents with advancing CKD stages (53% of eGFR ≤ 15 mL/min/1.73 m2 vs 26% of eGFR ≥ 60 mL/min/1.73 m2, P < 0.001). An increased number of patients receiving more classes of antihypertensive agents was observed as the urine albumin-creatinine ratio category increased (category A3: 62% vs category A1: 40%, P < 0.001), with the upward trends particularly noticeable in the number of individuals prescribed renin angiotensin system blockers. The prescription of three or more antihypertensive agents was associated with all-cause mortality, independent of blood pressure control (hazard ratio: 1.15; 95% confidence interval: 1.04-1.27, P = 0.006). Kaplan-Meier analysis illustrated significant differences in survival outcomes between patients with three or more and those with less than three antihypertensive agents prescribed (log-rank, P < 0.001). CONCLUSION: Antihypertensive prescribing patterns in the Salford Kidney Study based on CKD stage were consistent with expectations from the current United Kingdom National Institute of Health and Care Excellence guideline algorithm. Outcomes were poorer in patients with poor blood pressure control despite being on multiple antihypertensive agents. Continued research is required to bridge remaining variations in hypertension treatment practices worldwide.

Experience of a Bespoke Hyperkalaemia Clinic to Facilitate Prescribing of Renin-Angiotensin-Aldosterone System Inhibitors in Patients with Heart Failure with Reduced Ejection Fraction.

BACKGROUND: Renin-angiotensin-aldosterone system inhibitors (RAASi) improve prognosis in patients with heart failure with reduced ejection fraction (HFrEF), but suboptimal dosing or discontinuation of these medications often occurs due to RAASi-associated hyperkalaemia. We established a nephrology-led hyperkalaemia clinic to oversee prescribing of patiromer, an oral potassium binder, to facilitate RAASi optimization. METHODS: The clinic was established in July 2019 at a nephrology tertiary centre in the UK. Patients with HFrEF who were unable to increase RAASi dosage due to hyperkalaemia were referred to the clinic, where all patients commenced patiromer 8.4 g daily. RAASi adjustments were deferred to the referring teams. Study outcomes included the percentage of patients who achieved a RAASi dose increase and the proportion of patients with normokalaemia at follow-up. Outcomes were evaluated until 1 May 2021. RESULTS: A total of 34 patients were reviewed in the clinic between July 2019 and December 2020. Mean age was 71.6 years (±10.6 years), 56% had diabetes, and 71% had chronic kidney disease stages 3a-5; mean estimated glomerular filtration rate was 56 mL/min/1.73 m2 (±21 mL/min/1.73 m2). During follow-up, 13 patients discontinued patiromer (6 of whom did so due to gastrointestinal side effects) and were discharged; 2 patients died from non-hyperkalaemia-related illness; one switched to an alternative potassium binder. Over a mean follow-up of 13.4 months (±5.8 months), 17 of the 20 patients (85%) who continued with a potassium binder achieved a RAASi dose increase, with 4 patients (20%) receiving maximal dosages. This was attained by achieving normokalaemia during follow-up. No patients required magnesium supplementation. Of the 19 patients on patiromer, 12 continued this therapy for more than 12 months and 4 received it safely for 20 months. DISCUSSION/CONCLUSION: Patiromer prescribing in a nephrology-led hyperkalaemia clinic facilitated RAASi up-titration in patients with HFrEF by controlling potassium levels.

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.

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.

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.

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.

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.

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.

MAIP: a web service for predicting blood-stage malaria inhibitors.

Malaria is a disease affecting hundreds of millions of people across the world, mainly in developing countries and especially in sub-Saharan Africa. It is the cause of hundreds of thousands of deaths each year and there is an ever-present need to identify and develop effective new therapies to tackle the disease and overcome increasing drug resistance. Here, we extend a previous study in which a number of partners collaborated to develop a consensus in silico model that can be used to identify novel molecules that may have antimalarial properties. The performance of machine learning methods generally improves with the number of data points available for training. One practical challenge in building large training sets is that the data are often proprietary and cannot be straightforwardly integrated. Here, this was addressed by sharing QSAR models, each built on a private data set. We describe the development of an open-source software platform for creating such models, a comprehensive evaluation of methods to create a single consensus model and a web platform called MAIP available at https://www.ebi.ac.uk/chembl/maip/ . MAIP is freely available for the wider community to make large-scale predictions of potential malaria inhibiting compounds. This project also highlights some of the practical challenges in reproducing published computational methods and the opportunities that open-source software can offer to the community.

Hydrogen and methane breath test results are negatively associated with IBS and may reflect transit time in post-surgical patients.

BACKGROUND: Contention surrounds hydrogen and methane breath tests as putative measures of small intestinal bacterial overgrowth. We aimed to explore the clinical characteristics associated with positive and negative results to help clarify their role. METHODS: 525 glucose hydrogen/methane breath tests completed over 3 years were analyzed to look for positively and negatively associated predictive factors. Characteristics such as height and weight and underlying medical conditions, medications, and surgical history were collated. KEY RESULTS: There were 85 and 42 positive hydrogen and methane tests, respectively. Patients with irritable bowel syndrome (IBS) (HR = 0.17, p = 0.004) and those with a higher body mass index (HR = 0.93, p = 0.004) were significantly less likely to have a positive test. Patients who underwent the test post-surgically were significantly more likely to have a positive test (HR = 2.76, p = 0.001). A sub-analysis of post-surgical patients by type and region of surgical resection demonstrated that none were statistically more likely than the next to have a positive test. However, for the surgical group as a whole the number of motility-depressing drugs taken (such as opioids) was associated with a significantly decreased likelihood of a positive test (HR = 0.752, p = 0.045). CONCLUSION: Our data suggest that patients with a diagnosis of IBS are statistically less likely to have a positive test and it is of limited utility in this group. Post-surgical patients are more likely to have a positive test, possibly secondary to fast transit rather than bacterial overgrowth, as suggested by a significantly negative association with motility-suppressing drugs in this sub-group.