Increased prevalence of ECG markers for sudden cardiac arrest in refractory epilepsy.

BACKGROUND AND AIM: People with epilepsy are at increased risk of sudden cardiac arrest (SCA) due to ECG-confirmed ventricular tachycardia/fibrillation, as seen in a community-based study. We aimed to determine whether ECG-risk markers of SCA are more prevalent in people with epilepsy. METHODS: In a cross-sectional, retrospective study, we analysed the ECG recordings of 185 people with refractory epilepsy and 178 controls without epilepsy. Data on epilepsy characteristics, cardiac comorbidity, and drug use were collected, and general ECG variables (heart rate (HR), PQ and QRS intervals) assessed. We analysed ECGs for three markers of SCA risk: severe QTc prolongation (male >450 ms, female >470 ms), Brugada ECG pattern, and early repolarisation pattern (ERP). Multivariate regression models were used to analyse differences between groups, and to identify associated clinical and epilepsy-related characteristics. RESULTS: People with epilepsy had higher HR (71 vs 62 bpm, p<0.001) and a longer PQ interval (162.8 vs 152.6 ms, p=0.001). Severe QTc prolongation and ERP were more prevalent in people with epilepsy (QTc prolongation: 5% vs 0%; p=0.002; ERP: 34% vs 13%, p<0.001), while the Brugada ECG pattern was equally frequent in both groups (2% vs 1%, p>0.999). After adjustment for covariates, epilepsy remained associated with ERP (ORadj 2.4, 95% CI 1.1 to 5.5) and severe QTc prolongation (ORadj 9.9, 95% CI 1.1 to 1317.7). CONCLUSIONS: ERP and severe QTc prolongation appear to be more prevalent in people with refractory epilepsy. Future studies must determine whether this contributes to increased SCA risk in people with epilepsy

A micro differential viscosity detector for polymer separation system

In this paper we present the first micromachined viscosity detector suitable for coupling to conventional, commercially available polymer separation systems. The μ-viscometer (viscochip) has a reduced dead volume compared to conventional viscometers. It is shown that this results in better chromatographic resolution

A differential viscosity detector for use in miniaturized chemical separation systems

Abstract—In this paper, we present a micromachined differential viscosity detector suitable for integration into an on-chip hydro-dynamic chromatography system. The general design, however, is applicable to any liquid chromatography system that is used for separation of polymers. The micromachined part of the detector consists of a fluidic Wheatstone bridge and a low hydraulic capaci-tance pressure sensor of which the pressure sensing is based on op-tical detection of a membrane deflection. The stand-alone sensor shows a resolution in specific viscosity of 3 10 3, in which spe-cific viscosity is defined as the increase in viscosity by a sample, relative to the baseline viscosity of a solvent. [0947] Index Terms—Microfluidics, viscometer, viscosity detection

SCN5A Mutations in Brugada Syndrome Are Associated with Increased Cardiac Dimensions and Reduced Contractility

BACKGROUND: The cardiac sodium channel (Na(v)1.5) controls cardiac excitability. Accordingly, SCN5A mutations that result in loss-of-function of Na(v)1.5 are associated with various inherited arrhythmia syndromes that revolve around reduced cardiac excitability, most notably Brugada syndrome (BrS). Experimental studies have indicated that Na(v)1.5 interacts with the cytoskeleton and may also be involved in maintaining structural integrity of the heart. We aimed to determine whether clinical evidence may be obtained that Na(v)1.5 is involved in maintaining cardiac structural integrity. METHODS: Using cardiac magnetic resonance (CMR) imaging, we compared right ventricular (RV) and left ventricular (LV) dimensions and ejection fractions between 40 BrS patients with SCN5A mutations (SCN5a-mut-positive) and 98 BrS patients without SCN5A mutations (SCN5a-mut-negative). We also studied 18 age/sex-matched healthy volunteers. RESULTS: SCN5a-mut-positive patients had significantly larger end-diastolic and end-systolic RV and LV volumes, and lower LV ejection fractions, than SCN5a-mut-negative patients or volunteers. CONCLUSIONS: Loss-of-function SCN5A mutations are associated with dilatation and impairment in contractile function of both ventricles that can be detected by CMR analysis

Identification of risk factors associated with prolonged hospital stay following primary knee replacement surgery: a retrospective, longitudinal observational study

Objectives To identify risk factors associated with prolonged length of hospital stay and staying in hospital longer than medically necessary following primary knee replacement surgery. Design Retrospective, longitudinal observational study. Setting Elective knee replacement surgeries between 2016 and 2019 were identified using routinely collected data from an NHS Trust in England. Participants There were 2295 knee replacement patients with complete data included in analysis. The mean age was 68 (SD 11) and 60% were female. Outcome measures We assessed a binary length of stay outcome (>7 days), a continuous length of stay outcome (≤30 days) and a binary measure of whether patients remained in hospital when they were medically fit for discharge. Results The mean length of stay was 5.0 days (SD 3.9), 15.4% of patients were in hospital for >7 days and 7.1% remained in hospital when they were medically fit for discharge. Longer length of stay was associated with older age (b=0.08, 95% CI 0.07 to 0.09), female sex (b=0.36, 95% CI 0.06 to 0.67), high deprivation (b=0.98, 95% CI 0.47 to 1.48) and more comorbidities (b=2.48, 95% CI 0.15 to 4.81). Remaining in hospital beyond being medically fit for discharge was associated with older age (OR=1.07, 95% CI 1.05 to 1.09), female sex (OR=1.71, 95% CI 1.19 to 2.47) and high deprivation (OR=2.27, 95% CI 1.27 to 4.06). Conclusions The regression models could be used to identify which patients are likely to occupy hospital beds for longer. This could be helpful in scheduling operations to aid hospital efficiency by planning these patients’ operations for when the hospital is less busy

Development and application of simulation modelling for orthopaedic elective resource planning in England

Objectives This study aimed to develop a simulation model to support orthopaedic elective capacity planning. Methods An open-source, generalisable discrete-event simulation was developed, including a web-based application. The model used anonymised patient records between 2016 and 2019 of elective orthopaedic procedures from a National Health Service (NHS) Trust in England. In this paper, it is used to investigate scenarios including resourcing (beds and theatres) and productivity (lengths of stay, delayed discharges and theatre activity) to support planning for meeting new NHS targets aimed at reducing elective orthopaedic surgical backlogs in a proposed ring-fenced orthopaedic surgical facility. The simulation is interactive and intended for use by health service planners and clinicians. Results A higher number of beds (65–70) than the proposed number (40 beds) will be required if lengths of stay and delayed discharge rates remain unchanged. Reducing lengths of stay in line with national benchmarks reduces bed utilisation to an estimated 60%, allowing for additional theatre activity such as weekend working. Further, reducing the proportion of patients with a delayed discharge by 75% reduces bed utilisation to below 40%, even with weekend working. A range of other scenarios can also be investigated directly by NHS planners using the interactive web app. Conclusions The simulation model is intended to support capacity planning of orthopaedic elective services by identifying a balance of capacity across theatres and beds and predicting the impact of productivity measures on capacity requirements. It is applicable beyond the study site and can be adapted for other specialties

Discovery of predictors of sudden cardiac arrest in diabetes: rationale and outline of the RESCUED (REcognition of Sudden Cardiac arrest vUlnErability in Diabetes) project

Introduction Early recognition of individuals with increased risk of sudden cardiac arrest (SCA) remains challenging. SCA research so far has used data from cardiologist care, but missed most SCA victims, since they were only in general practitioner (GP) care prior to SCA. Studying individuals with type 2 diabetes (T2D) in GP care may help solve this problem, as they have increased risk for SCA, and rich clinical datasets, since they regularly visit their GP for check-up measurements. This information can be further enriched with extensive genetic and metabolic information. Aim To describe the study protocol of the REcognition of Sudden Cardiac arrest vUlnErability in Diabetes (RESCUED) project, which aims at identifying clinical, genetic and metabolic factors contributing to SCA risk in individuals with T2D, and to develop a prognostic model for the risk of SCA. Methods The RESCUED project combines data from dedicated SCA and T2D cohorts, and GP data, from the same region in the Netherlands. Clinical data, genetic data (common and rare variant analysis) and metabolic data (metabolomics) will be analysed (using classical analysis techniques and machine learning methods) and combined into a prognostic model for risk of SCA. Conclusion The RESCUED project is designed to increase our ability at early recognition of elevated SCA risk through an innovative strategy of focusing on GP data and a multidimensional methodology including clinical, genetic and metabolic analyses.Molecular Epidemiolog