Clinical utility of an artificial intelligence radiomics-based tool for risk stratification of pulmonary nodules.

Background: Clinical utility data on pulmonary nodule (PN) risk stratification biomarkers are lacking. We aimed to determine the incremental predictive value and clinical utility of using an artificial intelligence (AI) radiomics-based computer-aided diagnosis (CAD) tool in addition to routine clinical information to risk stratify PNs among real-world patients.

Methods: We performed a retrospective cohort study of patients with PNs who underwent lung biopsy.

Hypertension and cardiomyopathy associated with chronic kidney disease: epidemiology, pathogenesis and treatment considerations.

Chronic kidney disease (CKD) is a complex condition with a prevalence of 10-15% worldwide. An inverse-graded relationship exists between cardiovascular events and mortality with kidney function which is independent of age, sex, and other risk factors. The proportion of deaths due to heart failure and sudden cardiac death increase with progression of chronic kidney disease with relatively fewer deaths from atheromatous, vasculo-occlusive processes.

Artificial Intelligence Tool for Assessment of Indeterminate Pulmonary Nodules Detected with CT.

Background Limited data are available regarding whether computer-aided diagnosis (CAD) improves assessment of malignancy risk in indeterminate pulmonary nodules (IPNs). Purpose To evaluate the effect of an artificial intelligence-based CAD tool on clinician IPN diagnostic performance and agreement for both malignancy risk categories and management recommendations. Materials and Methods This was a retrospective multireader multicase study performed in June and July 2020 on chest CT studies of IPNs.

The contribution of human factors and ergonomics to the design and delivery of safe future healthcare.

Human factors and ergonomics (HF/E) is concerned with the design of work and work systems. There is an increasing appreciation of the value that HF/E can bring to enhancing the quality and safety of care, but the professionalisation of HF/E in healthcare is still in its infancy. In this paper, we set out a vision for HF/E in healthcare based on the work of the Chartered Institute of Ergonomics and Human Factors (CIEHF), which is the professional body for HF/E in the UK.

Failure to rescue following emergency surgery: A FRAM analysis of the management of the deteriorating patient.

Background: Failure to rescue (FTR) denotes mortality from post-operative complications after surgery with curative intent. High-volume, low-mortality units have similar complication rates to others, but have lower FTR rates. Effective response to the deteriorating post-operative patient is therefore critical to reducing surgical mortality.

Changes in left ventricular structure and function associated with renal transplantation: a systematic review and meta-analysis.

Aims: This study aimed to examine if the cardiac changes associated with uraemic cardiomyopathy are reversed by renal transplantation.

Methods And Results: MEDLINE, Embase, OpenGrey, and the Cochrane Library databases were searched from 1950 to March 2020. The primary outcome measure was left ventricular mass index.

Clinical prediction of genotypes in hypertrophic cardiomyopathy: A systematic review.

Introduction: Hypertrophic cardiomyopathy (HCM) is the most common inherited cardiac condition and the most common cause of sudden cardiac death (SCD) in patients below the age of 35. Genetic testing is a vital part of HCM diagnostics, yet correlation with clinical phenotypes remains complex. Identifying clinical predictors of informative genetic testing may prevent unnecessary investigations and improve cost-effectiveness of services.

Coronary microvascular dysfunction is associated with degree of anaemia in end-stage renal disease.

Background: Coronary microvascular dysfunction (CMD) is common in end-stage renal disease (ESRD) and is an adverse prognostic marker. Coronary flow velocity reserve (CFVR) is a measure of coronary microvascular function and can be assessed using Doppler echocardiography. Reduced CFVR in ESRD has been attributed to factors such as diabetes, hypertension and left ventricular hypertrophy.

Acute kidney injury is more common in men than women after accounting for socioeconomic status, ethnicity, alcohol intake and smoking history.

Background: The association of several comorbidities, including diabetes mellitus, hypertension, cardiovascular disease, heart failure and chronic kidney or liver disease, with acute kidney injury (AKI) is well established. Evidence on the effect of sex and socioeconomic factors are scarce. This study was designed to examine the association of sex and socioeconomic factors with AKI and AKI-related mortality and further to evaluate the additional relationship with other possible risk factors for AKI occurrence.

The utility of a convolutional neural network (CNN) model score for cancer risk in indeterminate small solid pulmonary nodules, compared to clinical practice according to British Thoracic Society guidelines.

Purpose: To determine how implementation of an artificial intelligence nodule algorithm, the Lung Cancer Prediction Convolutional Neural Network (LCP-CNN), at the point of incidental nodule detection would have influenced further investigation and management using a series of threshold scores at both the benign and malignant end of the spectrum.

Method: An observational retrospective study was performed in the assessment of nodules between 5-15 mm (158 benign, 32 malignant) detected on CT scans, which were performed as part of routine practice. The LCP-CNN was applied to the baseline CT scan producing a percentage score, and subsequent imaging and management determined for each threshold group.

Lung cancer prediction by Deep Learning to identify benign lung nodules.

Introduction: Deep Learning has been proposed as promising tool to classify malignant nodules. Our aim was to retrospectively validate our Lung Cancer Prediction Convolutional Neural Network (LCP-CNN), which was trained on US screening data, on an independent dataset of indeterminate nodules in an European multicentre trial, to rule out benign nodules maintaining a high lung cancer sensitivity.

Methods: The LCP-CNN has been trained to generate a malignancy score for each nodule using CT data from the U.

Cardiovascular Effects of Unilateral Nephrectomy in Living Kidney Donors at 5 Years.

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The effect of admission and pre-admission serum creatinine as baseline to assess incidence and outcomes of acute kidney injury in acute medical admissions.

Background: Acute kidney injury (AKI) in hospital-admitted patients is a common complication associated with increased mortality. The diagnosis of AKI relies on the ascertainment of peak increase in serum creatinine (SCr). This study evaluated the incidence of AKI using the increase from mean 7-365 days pre-admission (AKIpre) and admission (AKIadm) SCr levels, and examined the associations of AKI and changes in SCr levels with all-cause mortality.

Evaluation of a novel deep learning-based classifier for perifissural nodules.

Objectives: To evaluate the performance of a novel convolutional neural network (CNN) for the classification of typical perifissural nodules (PFN).

Methods: Chest CT data from two centers in the UK and The Netherlands (1668 unique nodules, 1260 individuals) were collected. Pulmonary nodules were classified into subtypes, including "typical PFNs" on-site, and were reviewed by a central clinician.

Synthetic band-structure engineering in polariton crystals with non-Hermitian topological phases.

Synthetic crystal lattices provide ideal environments for simulating and exploring the band structure of solid-state materials in clean and controlled experimental settings. Physical realisations have, so far, dominantly focused on implementing irreversible patterning of the system, or interference techniques such as optical lattices of cold atoms. Here, we realise reprogrammable synthetic band-structure engineering in an all optical exciton-polariton lattice.

Changes in Blood Pressure and Arterial Hemodynamics following Living Kidney Donation.

Background And Objectives: The Effect of a Reduction in GFR after Nephrectomy on Arterial Stiffness and Central Hemodynamics (EARNEST) study was a multicenter, prospective, controlled study designed to investigate the associations of an isolated reduction in kidney function on BP and arterial hemodynamics.

Design, Setting, Participants, & Measurements: Prospective living kidney donors and healthy controls who fulfilled criteria for donation were recruited from centers with expertise in vascular research. Participants underwent office and ambulatory BP measurement, assessment of arterial stiffness, and biochemical tests at baseline and 12 months.

Coronary flow velocity reserve and inflammatory markers in living kidney donors.

Background: Coronary microvascular dysfunction is prevalent in chronic kidney disease (CKD), and may contribute to the development of myocardial dysfunction in CKD. Coronary flow velocity reserve (CFVR) is a marker of coronary microvascular function and falls with increasing CKD stage. Living kidney donors have renal function consistent with early stage CKD and concern has been raised about their cardiovascular risk.

Human factors/ergonomics to support the design and testing of rapidly manufactured ventilators in the UK during the COVID-19 pandemic.

Background: This paper describes a rapid response project from the Chartered Institute of Ergonomics & Human Factors (CIEHF) to support the design, development, usability testing and operation of new ventilators as part of the UK response during the COVID-19 pandemic.

Method: A five-step approach was taken to (1) assess the COVID-19 situation and decide to formulate a response; (2) mobilise and coordinate Human Factors/Ergonomics (HFE) specialists; (3) ideate, with HFE specialists collaborating to identify, analyse the issues and opportunities, and develop strategies, plans and processes; (4) generate outputs and solutions; and (5) respond to the COVID-19 situation via targeted support and guidance.

Results: The response for the rapidly manufactured ventilator systems (RMVS) has been used to influence both strategy and practice to address concerns about changing safety standards and the detailed design procedure with RMVS manufacturers.

Assessing the Accuracy of a Deep Learning Method to Risk Stratify Indeterminate Pulmonary Nodules.

The management of indeterminate pulmonary nodules (IPNs) remains challenging, resulting in invasive procedures and delays in diagnosis and treatment. Strategies to decrease the rate of unnecessary invasive procedures and optimize surveillance regimens are needed. To develop and validate a deep learning method to improve the management of IPNs.

Clinical Potential of Targeting Fibroblast Growth Factor-23 and αKlotho in the Treatment of Uremic Cardiomyopathy.

Chronic kidney disease is highly prevalent, affecting 10% to 15% of the adult population worldwide and is associated with increased cardiovascular morbidity and mortality. As chronic kidney disease worsens, a unique cardiovascular phenotype develops characterized by heart muscle disease, increased arterial stiffness, atherosclerosis, and hypertension. Cardiovascular risk is multifaceted, but most cardiovascular deaths in patients with advanced chronic kidney disease are caused by heart failure and sudden cardiac death.

Anticoagulant strategies for the patient with chronic kidney disease.

Chronic kidney disease (CKD) is a global health problem affecting up to 14% of the adult population in developed countries. On the basis of current guidelines, patients with CKD will often fulfil criteria for both short-term and long-term anticoagulation. Paradoxically, patients with CKD are not only at a higher risk of thrombosis, they are also at increased risk of bleeding.

External validation of a convolutional neural network artificial intelligence tool to predict malignancy in pulmonary nodules.

Background: Estimation of the risk of malignancy in pulmonary nodules detected by CT is central in clinical management. The use of artificial intelligence (AI) offers an opportunity to improve risk prediction. Here we compare the performance of an AI algorithm, the lung cancer prediction convolutional neural network (LCP-CNN), with that of the Brock University model, recommended in UK guidelines.