Creation and application of virtual patient cohorts of heart models

Patient-specific cardiac models are now being used to guide therapies. The increased use of patient-specific cardiac simulations in clinical care will give rise to the development of virtual cohorts of cardiac models. These cohorts will allow cardiac simulations to capture and quantify inter-patient variability. However, the development of virtual cohorts of cardiac models will require the transformation of cardiac modelling from small numbers of bespoke models to robust and rapid workflows that can create large numbers of models. In this review, we describe the state of the art in virtual cohorts of cardiac models, the process of creating virtual cohorts of cardiac models, and how to generate the individual cohort member models, followed by a discussion of the potential and future applications of virtual cohorts of cardiac models. This article is part of the theme issue 'Uncertainty quantification in cardiac and cardiovascular modelling and simulation'.

Increased resting metabolic rate and lipid oxidation in exercise-trained individuals: evidence for a role of beta-adrenergic stimulation

This study investigated the contribution of beta-adrenergic stimulation to the increase in resting metabolic rate (RMR) and lipid oxidation observed in exercise-trained individuals. Nine trained and eight sedentary men were subjected to two testing sessions, during which these variables were measured before and for 3 h after the oral administration of propranolol or placebo. As expected, RMR and lipid oxidation were significantly higher in the trained subjects before the administration of propranolol and throughout the placebo test in comparison with sedentary controls. A significant decrease in RMR and lipid oxidation was induced by propranolol in the trained subjects, whereas no change was observed in the untrained group, and this effect of propranolol was sufficient to abolish the difference between the two groups at baseline and under the placebo condition. Propranolol also induced a significant reduction in heart rate and systolic blood pressure, but the response was comparable in the two groups. In conclusion, the results of this study show that beta-adrenergic stimulation is involved in the increase in RMR and lipid oxidation observed in highly trained individuals. Moreover, the absence of a training-propranolol interaction effect on heart rate and systolic blood pressure suggests the existence of some dissociation between the metabolic and cardiovascular effects of prolonged exercise training.

Deprivation as an outcome determinant in emergency medical admissions

BACKGROUND

Deprivation in the general population predicts mortality. We have investigated its relevance to an acute medical admission, using a database of all emergency admissions to St James' Hospital, Dublin, over a 10-year period (2002-11).

METHODS

All emergency admissions, based on geocoding of residence, were allocated to a Small Area Health Research Unit division, with a corresponding deprivation index. We then examined this index as a univariate (unadjusted) and independent (adjusted) predictor of 30-day in-hospital mortality.

RESULTS

The 30-day in-hospital mortality, over the 10-year period, was higher for those in the upper half of the deprivation distribution (9.6 vs. 8.6%; P = 0.002). Indeed, there was a stepwise increase in 30-day mortality over the quintiles of deprivation from 7.3% (Quintile 1) to 8.8, 10.0, 10.0 and 9.3%, respectively. Univariate logistic regression of the deprivation indices (quintiles) against outcome showed an increased risk (P = 0.002) of a 30-day death with odds ratios (ORs), respectively (compared with lowest deprivation quintile) of 1.39 [95% confidence intervals (CI) 1.21, 1.58], 1.47 (95% CI 1.29, 1.68), 1.44 (95% CI 1.26, 1.64) and 1.39 (95% CI 1.22, 1.59). The deprivation index was an independent predictor of outcome in a model when adjusted for illness severity and co-morbidity. The fully adjusted OR for a 30-day death was increased by 31% (P = 0.001) for patients in the upper half of the deprivation index distribution (OR 1.35; 95% CI 1.23, 1.48; P < 0.001).

CONCLUSION

Deprivation, independent of co-morbidity or acute illness severity, is an independent predictor of 30-day mortality in acute medical admissions.

Interleukin-6, C-reactive protein, fibrinogen, and risk of recurrence after ischaemic stroke: Systematic review and meta-analysis

BACKGROUND

Recent randomised trials showed benefit for anti-inflammatory therapies in coronary disease but excluded stroke. The prognostic value of blood inflammatory markers after stroke is uncertain and guidelines do not recommend their routine measurement for risk stratification.

METHODS

We performed a systematic review and meta-analysis of studies investigating the association of C-reactive protein (CRP), interleukin-6 (IL-6) and fibrinogen and risk of recurrent stroke or major vascular events (MVEs). We searched EMBASE and Ovid Medline until 10/1/19. Random-effects meta-analysis was performed for studies reporting comparable effect measures.

RESULTS

Of 2,515 reports identified, 39 met eligibility criteria (IL-6, n = 10; CRP, n = 33; fibrinogen, n = 16). An association with recurrent stroke was reported in 12/26 studies (CRP), 2/11 (fibrinogen) and 3/6 (IL-6). On random-effects meta-analysis of comparable studies, CRP was associated with an increased risk of recurrent stroke [pooled hazard ratio (HR) per 1 standard-deviation (SD) increase in loge-CRP (1.14, 95% CI 1.06-1.22, p < 0.01)] and MVEs (pooled HR 1.21, CI 1.10-1.34, p < 0.01). Fibrinogen was also associated with recurrent stroke (HR 1.26, CI 1.07-1.47, p < 0.01) and MVEs (HR 1.31, 95% CI 1.15-1.49, p < 0.01). Trends were identified for IL-6 for recurrent stroke (HR per 1-SD increase 1.17, CI 0.97-1.41, p = 0.10) and MVEs (HR 1.22, CI 0.96-1.55, p = 0.10).

CONCLUSION

Despite evidence suggesting an association between inflammatory markers and post-stroke vascular recurrence, substantial methodological heterogeneity was apparent between studies. Individual-patient pooled analysis and standardisation of methods are needed to determine the prognostic role of blood inflammatory markers and to improve patient selection for randomised trials of inflammatory therapies.

Predicting left ventricular contractile function via Gaussian process emulation in aortic-banded rats

Cardiac contraction is the result of integrated cellular, tissue and organ function. Biophysical in silico cardiac models offer a systematic approach for studying these multi-scale interactions. The computational cost of such models is high, due to their multi-parametric and nonlinear nature. This has so far made it difficult to perform model fitting and prevented global sensitivity analysis (GSA) studies. We propose a machine learning approach based on Gaussian process emulation of model simulations using probabilistic surrogate models, which enables model parameter inference via a Bayesian history matching (HM) technique and GSA on whole-organ mechanics. This framework is applied to model healthy and aortic-banded hypertensive rats, a commonly used animal model of heart failure disease. The obtained probabilistic surrogate models accurately predicted the left ventricular pump function (R² = 0.92 for ejection fraction). The HM technique allowed us to fit both the control and diseased virtual bi-ventricular rat heart models to magnetic resonance imaging and literature data, with model outputs from the constrained parameter space falling within 2 SD of the respective experimental values. The GSA identified Troponin C and cross-bridge kinetics as key parameters in determining both systolic and diastolic ventricular function. This article is part of the theme issue 'Uncertainty quantification in cardiac and cardiovascular modelling and simulation'.

Fitting two human atrial cell models to experimental data using Bayesian history matching

Cardiac cell models are potentially valuable tools for applications such as quantitative safety pharmacology, but have many parameters. Action potentials in real cardiac cells also vary from beat to beat, and from one cell to another. Calibrating cardiac cell models to experimental observations is difficult, because the parameter space is large and high-dimensional. In this study we have demonstrated the use of history matching to calibrate the maximum conductance of ion channels and exchangers in two detailed models of the human atrial action potential against measurements of action potential biomarkers. History matching is an approach developed in other modelling communities, based on constructing fast-running Gaussian process emulators of the model. Emulators were constructed from a small number of model runs (around 10²), and then run many times (>10⁶) at low computational cost, each time with a different set of model parameters. Emulator outputs were compared with experimental biomarkers using an implausibility measure, which took into account experimental variance as well as emulator variance. By repeating this process, the region of non-implausible parameter space was iteratively reduced. Both cardiac cell models were successfully calibrated to experimental datasets, resulting in sets of parameters that could be sampled to produce variable action potentials. However, model parameters did not occupy a small range of values. Instead, the history matching process exposed inputs that can co-vary across a wide range and still be consistent with a particular biomarker. We also found correlations between some biomarkers, indicating a need for better descriptors of action potential shape.

Quantifying atrial anatomy uncertainty from clinical data and its impact on electro-physiology simulation predictions

Patient-specific computational models of structure and function are increasingly being used to diagnose disease and predict how a patient will respond to therapy. Models of anatomy are often derived after segmentation of clinical images or from mapping systems which are affected by image artefacts, resolution and contrast. Quantifying the impact of uncertain anatomy on model predictions is important, as models are increasingly used in clinical practice where decisions need to be made regardless of image quality. We use a Bayesian probabilistic approach to estimate the anatomy and to quantify the uncertainty about the shape of the left atrium derived from Cardiac Magnetic Resonance images. We show that we can quantify uncertain shape, encode uncertainty about the left atrial shape due to imaging artefacts, and quantify the effect of uncertain shape on simulations of left atrial activation times.

Probabilistic Interpolation of Uncertain Local Activation Times on Human Atrial Manifolds

OBJECTIVE

Local activation time (LAT) mapping of the atria is important for targeted treatment of atrial arrhythmias, but current methods do not interpolate on the atrial manifold and neglect uncertainties associated with LAT observations. In this paper, we describe novel methods to, first, quantify uncertainties in LAT arising from bipolar electrogram analysis and assignment of electrode recordings to the anatomical mesh, second, interpolate uncertain LAT measurements directly on left atrial manifolds to obtain complete probabilistic activation maps, and finally, interpolate LAT jointly across both the manifold and different S1-S2 pacing protocols.

METHODS

A modified center of mass approach was used to process bipolar electrograms, yielding a LAT estimate and error distribution from the electrogram morphology. An error distribution for assigning measurements to the anatomical mesh was estimated. Probabilistic LAT maps were produced by interpolating on a left atrial manifold using Gaussian Markov random fields, taking into account observation errors and characterizing LAT predictions by their mean and standard deviation. This approach was extended to interpolate across S1-S2 pacing protocols.

RESULTS

We evaluated our approach using recordings from three patients undergoing atrial ablation. Cross-validation showed consistent and accurate prediction of LAT observations both at different locations on the left atrium and for different S1-S2 intervals.

SIGNIFICANCE

Interpolation of scalar and vector fields across anatomical structures from point measurements is a challenging problem in biomedical engineering, compounded by uncertainties in measurements and meshes. New methods and approaches are required, and in this paper, we have demonstrated an effective method for probabilistic interpolation of uncertain LAT.

Quantifying the effect of uncertainty in input parameters in a simplified bidomain model of partial thickness ischaemia

Reduced blood flow in the coronary arteries can lead to damaged heart tissue (myocardial ischaemia). Although one method for detecting myocardial ischaemia involves changes in the ST segment of the electrocardiogram, the relationship between these changes and subendocardial ischaemia is not fully understood. In this study, we modelled ST-segment epicardial potentials in a slab model of cardiac ventricular tissue, with a central ischaemic region, using the bidomain model, which considers conduction longitudinal, transverse and normal to the cardiac fibres. We systematically quantified the effect of uncertainty on the input parameters, fibre rotation angle, ischaemic depth, blood conductivity and six bidomain conductivities, on outputs that characterise the epicardial potential distribution. We found that three typical types of epicardial potential distributions (one minimum over the central ischaemic region, a tripole of minima, and two minima flanking a central maximum) could all occur for a wide range of ischaemic depths. In addition, the positions of the minima were affected by both the fibre rotation angle and the ischaemic depth, but not by changes in the conductivity values. We also showed that the magnitude of ST depression is affected only by changes in the longitudinal and normal conductivities, but not by the transverse conductivities.

Gaussian process manifold interpolation for probabilistic atrial activation maps and uncertain conduction velocity

In patients with atrial fibrillation, local activation time (LAT) maps are routinely used for characterizing patient pathophysiology. The gradient of LAT maps can be used to calculate conduction velocity (CV), which directly relates to material conductivity and may provide an important measure of atrial substrate properties. Including uncertainty in CV calculations would help with interpreting the reliability of these measurements. Here, we build upon a recent insight into reduced-rank Gaussian processes (GPs) to perform probabilistic interpolation of uncertain LAT directly on human atrial manifolds. Our Gaussian process manifold interpolation (GPMI) method accounts for the topology of the atrium, and allows for calculation of statistics for predicted CV. We demonstrate our method on two clinical cases, and perform validation against a simulated ground truth. CV uncertainty depends on data density, wave propagation direction and CV magnitude. GPMI is suitable for probabilistic interpolation of other uncertain quantities on non-Euclidean manifolds. This article is part of the theme issue 'Uncertainty quantification in cardiac and cardiovascular modelling and simulation'.

Surface roughening in polymer blend thin films by lateral phase separation: a thermodynamic mechanism

We use a phase portrait approach to study the phase equilibria of a symmetric binary polymer blend confined between an attracting wall and a neutral wall. We find multiple solutions for this wall regime where only one solution exists for antisymmetric walls. We also argue that, when one wall is a free surface, roughening of the free surface upon lateral phase separation is expected, since thermodynamics alone implies that the coexisting phases should exist at different heights to minimise energy. We focus on the graphical insight provided by this phase portrait approach.

Inflammatory cytokines, high-sensitivity C-reactive protein, and risk of one-year vascular events, death, and poor functional outcome after stroke and transient ischemic attack

Background

Inflammation driven by pro-inflammatory cytokines is a new therapeutic target in coronary disease. Few data exist on the association of key upstream cytokines and post-stroke recurrence. In a prospective cohort study, we investigated the association between pivotal cytokines, high-sensitivity C-reactive protein (hsCRP) and one-year outcomes.

Methods

BIO-STROKETIA is a multi-center prospective cohort study of non-severe ischemic stroke (modified Rankin score ≤ 3) and transient ischemic attack. Controls were patients with transient symptoms attending transient ischemic attack clinics with non-ischemic final diagnosis. Exclusion criteria were severe stroke, infection, and other pro-inflammatory disease; hsCRP and cytokines (interleukin (IL) 6, IL-1β, IL-8, IL-10, IL-12, interferon-γ (IFN-γ), tumor-necrosis factor-α (TNF-α)) were measured. The primary outcome was one-year recurrent stroke/coronary events (fatal and non-fatal).

Results

In this study, 680 patients (439 stroke, 241 transient ischemic attack) and 68 controls were included. IL-6, IL-1β, IL-8, IFN-γ, TNF-α, and hsCRP were higher in stroke/transient ischemic attack cases (p ≤ 0.01 for all). On multivariable Cox regression, IL-6, IL-8, and hsCRP independently predicted one-year recurrent vascular events (adjusted hazard ratios (aHR) per-quartile increase IL-6 1.31, confidence interval (CI) 1.02–1.68, p = 0.03; IL-8 1.47, CI 1.15–1.89, p = 0.002; hsCRP 1.28, CI 1.01–1.62, p = 0.04). IL-6 (aHR 1.98, CI 1.26–3.14, p = 0.003) and hsCRP (aHR 1.81, CI 1.20–2.74, p = 0.005) independently predicted one-year fatality. IL-6 and hsCRP (adjusted odds ratio per-unit increase 1.02, CI 1.01–1.04) predicted poor functional outcome, with a trend for IL-1β (p = 0.054).

Conclusion

Baseline inflammatory cytokines independently predicted late recurrence, supporting a rationale for randomized trials of anti-inflammatory agents for prevention after stroke and suggesting that targeted therapy to high-risk patients with high baseline inflammation may be beneficial.

Bayesian Calibration of Electrophysiology Models Using Restitution Curve Emulators

Calibration of cardiac electrophysiology models is a fundamental aspect of model personalization for predicting the outcomes of cardiac therapies, simulation testing of device performance for a range of phenotypes, and for fundamental research into cardiac function. Restitution curves provide information on tissue function and can be measured using clinically feasible measurement protocols. We introduce novel "restitution curve emulators" as probabilistic models for performing model exploration, sensitivity analysis, and Bayesian calibration to noisy data. These emulators are built by decomposing restitution curves using principal component analysis and modeling the resulting coordinates with respect to model parameters using Gaussian processes. Restitution curve emulators can be used to study parameter identifiability via sensitivity analysis of restitution curve components and rapid inference of the posterior distribution of model parameters given noisy measurements. Posterior uncertainty about parameters is critical for making predictions from calibrated models, since many parameter settings can be consistent with measured data and yet produce very different model behaviors under conditions not effectively probed by the measurement protocols. Restitution curve emulators are therefore promising probabilistic tools for calibrating electrophysiology models.

Influence of social deprivation, overcrowding and family structure on emergency medical admission rates

BACKGROUND

Patients from deprived backgrounds have a higher in-patient mortality following emergency medical admission.

AIM

To evaluate the influence of Deprivation Index, overcrowding and family structure on hospital admission rates.

DESIGN

Retrospective cohort study.

METHODS

All emergency medical admissions from 2002 to 2013 were evaluated. Based on address, each patient was allocated to an electoral division, whose small area population statistics were available from census data. Patients were categorized by quintile of Deprivation Index, overcrowding and family structure, and these were evaluated against hospital admission rate, calculated as rate/1000 population. Univariate and multivariable risk estimates (Odds Ratios or Incidence Rate Ratios) were calculated, using logistic or zero truncated Poisson regression as appropriate.

RESULTS

There were 66 861 admissions in 36 214 patients over the 12-year study period. Deprivation Index quintile independently predicted the admission rate, with rates of Q1 12.0 (95% CI 11.8-12.2), Q2 19.5 (95% CI 19.3-19.6), Q3 33.7 (95% CI 33.3-34.0), Q4 31.4 (95% CI 31.2-31.6) and Q5 38.1 (95% CI 37.7-38.5). Similarly the proportions of families with children <15 years old, was an independent predictor of the admission rate with rates of Q1 20.8 (95% CI 20.4-21.1), Q2 23.0 (95% CI 22.7-23.3), Q3 32.2 (95% CI 31.9-32.5), Q4 32.4 (95% CI 32.2-32.7) and Q5 37.2 (95% CI 36.6-37.8). The proportion of families with children ≥15-years old was also predictive but quintile of overcrowding was only predictive in the univarate model.

CONCLUSION

Deprivation Index and family structure strongly predict emergency medical hospital admission rates.

Sensitivity and Uncertainty Analysis of Two Human Atrial Cardiac Cell Models Using Gaussian Process Emulators

Biophysically detailed cardiac cell models reconstruct the action potential and calcium dynamics of cardiac myocytes. They aim to capture the biophysics of current flow through ion channels, pumps, and exchangers in the cell membrane, and are highly detailed. However, the relationship between model parameters and model outputs is difficult to establish because the models are both complex and non-linear. The consequences of uncertainty and variability in model parameters are therefore difficult to determine without undertaking large numbers of model evaluations. The aim of the present study was to demonstrate how sensitivity and uncertainty analysis using Gaussian process emulators can be used for a systematic and quantitive analysis of biophysically detailed cardiac cell models. We selected the Courtemanche and Maleckar models of the human atrial action potential for analysis because these models describe a similar set of currents, with different formulations. In our approach Gaussian processes emulate the main features of the action potential and calcium transient. The emulators were trained with a set of design data comprising samples from parameter space and corresponding model outputs, initially obtained from 300 model evaluations. Variance based sensitivity indices were calculated using the emulators, and first order and total effect indices were calculated for each combination of parameter and output. The differences between the first order and total effect indices indicated that the effect of interactions between parameters was small. A second set of emulators were then trained using a new set of design data with a subset of the model parameters with a sensitivity index of more than 0.1 (10%). This second stage analysis enabled comparison of mechanisms in the two models. The second stage sensitivity indices enabled the relationship between the L-type Ca 2+ current and the action potential plateau to be quantified in each model. Our quantitative analysis predicted that changes in maximum conductance of the ultra-rapid K + channel I Kur would have opposite effects on action potential duration in the two models, and this prediction was confirmed by additional simulations. This study has demonstrated that Gaussian process emulators are an effective tool for sensitivity and uncertainty analysis of biophysically detailed cardiac cell models.

Pattern formation in polymer blend thin films: surface roughening couples to phase separation

We introduce a model for thin films of multicomponent fluids that includes lateral and vertical phase separation, preferential component attraction at both surfaces, and surface roughening. We apply our model to thin films of binary polymer blends, and use simulations of different surface-blend interaction regimes to investigate pattern formation. We demonstrate that surface roughening couples to phase separation. For films undergoing lateral phase separation via a transient wetting layer, this results in distinct stages of roughening as the film evolves between different phase equilibria.

Counterregulatory response to insulin-induced hypoglycemia in trained and nontrained humans

The aim of the present series of experiments was to investigate the hormonal counterregulatory response to insulin-induced hypoglycemia in trained and nontrained healthy individuals. Five endurance athletes and six controls were administered intravenous insulin infusion at a rate of 0.15 U/kg/h until plasma glucose reached 50 mg/dL. The mean duration of the infusion in the trained and nontrained subjects corresponded to 18.6 and 26.3 minutes (P less than .01), suggesting that the former were characterized by an increased insulin sensitivity. Plasma glucose levels were similar in the two groups at the end of the insulin infusion, as well as during the postinfusion recovery period. Forty-five minutes after the end of the infusion, plasma glucose levels were not significantly different from the preinfusion levels in the two groups. During this period of glycemia recovery, the increases in plasma glucagon, epinephrine, norepinephrine, and growth hormone were at least 50% lower in the trained than in the nontrained subjects. The increase in heart rate and oxygen uptake during the same period of time was significantly higher in the trained subjects. To determine whether this reduced hormonal response to hypoglycemia was due to reduced insulin levels or to an increased sensitivity to counterregulatory hormones, we investigated the effect of epinephrine on plasma glucose in two other groups of trained and nontrained subjects. In response to a constant epinephrine infusion of 0.01 or 0.1 micrograms/kg fat-free mass (FFM)/min, plasma glucose levels increased similarly in the two groups. In conclusion, these results indicate that trained subjects are characterized by a normal recovery from hypoglycemia despite a reduced response of counterregulatory factors.(ABSTRACT TRUNCATED AT 250 WORDS)

Components of the Risk Instrument for Screening in the Community (RISC) that Correlate with Public Health Nurses' Perception of Risk

BACKGROUND

Functional decline and frailty are common in community-dwelling older adults, leading to an increased risk of adverse outcomes.

OBJECTIVE

To examine the factors that public health nurses perceive to cause risk of three adverse outcomes: institutionalisation, hospitalisation, and death, in older adults, using the Risk Instrument for Screening in the Community (RISC).

DESIGN

A quantitative, correlational, descriptive design was used.

SETTING AND PARTICIPANTS

A sample of 803 community-dwellers, aged over 65 years receiving regular follow-up by public health nurses. Procedure and Measurements: Public health nurses (n=15) scored the RISC and the Clinical Frailty Scale (CFS) on patients in their caseload. We examined and compared correlations between the severity of concern and ability of the caregiver network to manage these concerns with public health nurses' perception of risk of the three defined adverse outcomes.

RESULTS

In total, 782 RISC scores were available. Concern was higher for the medical state domain (686/782,88%) compared with the mental state (306/782,39%) and activities of daily living (595/782,76%) domains. Concern was rated as severe for only a small percentage of patients. Perceived risk of institutionalisation had the strongest correlation with concern over patients mental state,(r=0.53), while risk of hospitalisation,(r=0.53) and death,(r=0.40) correlated most strongly with concern over the medical state. Weaker correlations were found for the other domains and RISC scores. The CFS most strongly correlated with the ADL domain,(r=0.78).

CONCLUSION

Although the prevalence of concern was high, it was mostly rated as mild. Perceived risk of institutionalisation correlated most with concern over the ability of caregiver networks to manage patients' mental state, while risk of hospitalisation and death correlated with patients' medical state. The findings suggest the importance of including an assessment of the caregiver network when examining community-dwelling older adults. Validation of the RISC and public health nurses' ratings are now required.

Social deprivation and the rate of emergency medical admission for older persons

BACKGROUND

Deprivation Status increases the annual admission incidence of emergency medical admissions; the extent to which deprivation influences the admission of older persons is less well known.

AIM

To examine whether deprivation within a hospital catchment area influences emergency medical admissions for the elderly population.

DESIGN

The relationship between Deprivation Status, Dependency Ratio (population proportion of non-working age (<15 or ≥65 years) and age for all emergency admissions (82 368 episodes of 44 628 patients), over a 13-year period, were examined and ranked by quintile.

METHODS

Univariate and multi-variable risk estimates (incidence rate ratios) were calculated, using truncated Poisson regression.

RESULTS

The Dependency Ratio and the Deprivation index independently predicted the annual incidence rate of medical emergencies; however, when calculated for older persons, the corresponding incidence rate ratios showed a falling trend with increasing Deprivation Status-Q2 0.51 (95% confidence interval [CI]: 0.50, 0.52), Q3 0.59 (95% CI: 0.58, 0.60), Q4 0.51 (95% CI: 0.50, 0.52) and Q5 0.37 (95% CI: 0.36, 0.38). Thus, with increasing Deprivation Status, the proportion of total admission from the ≥65-year cohort fell substantially.

CONCLUSION

The admission incidence rate for emergency medical patients is strongly influenced by the catchment area Deprivation Status. However, because of its greater impact on the younger population, increasing deprivation alters the ratio of younger to older persons as a proportion of total emergency admissions.

Breakup of a transient wetting layer in polymer blend thin films: unification with 1D phase equilibria

We show that lateral phase separation in polymer blend thin films can proceed via the formation of a transient wetting layer which breaks up to give a laterally segregated film. We show that the growth of lateral inhomogeneities at the walls in turn causes the distortion of the interface in the transient wetting layer. By addressing the 1D phase equilibria of a polymer blend thin film confined between selectively attracting walls, we show that the breakup of a transient wetting layer is due to wall-blend interactions; there are multiple values of the volume fraction at the walls which solve equilibrium boundary conditions. This mechanism of lateral phase separation should be general.

Lateral phase separation in polymer-blend thin films: surface bifurcation

We use simulations of a binary polymer blend confined between selectively attracting walls to identify and explain the mechanism of lateral phase separation via a transient wetting layer. We first show that equilibrium phases in the film are described by one-dimensional phase equilibria in the vertical (depth) dimension, and demonstrate that effective boundary conditions imposed by the film walls pin the film profile at the walls. We then show that, prior to lateral phase separation, distortion of the interface in a transient wetting layer is coupled to lateral phase separation at the walls. Using Hamiltonian phase portraits, we explain a "surface bifurcation mechanism" whereby the volume fraction at the walls evolves and controls the dynamics of the phase separation. We suggest how solvent evaporation may assist our mechanism.

89 CSF BIOMARKER UTILITY IN SUPPORTING ALZHEIMER’S DISEASE DIAGNOSIS: CLINICAL PERSPECTIVES FROM AN IRISH REGIONAL SPECIALIST MEMORY SERVICE

Background

CSF (cerebrospinal fluid) biomarkers [amyloid- beta-42 (AB-42), phosphorylated tau (p-tau)] are increasingly used in supporting clinical diagnosis of Alzheimer’s Disease (AD). Both elevated CSF p-tau and reduced AB-42 are necessary for pathological diagnosis of AD. The aim of this study is to apply recent international recommendations to patients attending a regional specialist memory service, evaluating consistency with detailed clinical, neuroimaging, and neuropsychological ad-phenotype profiling.

Methods

All patients age &lt; 80, with mild/subjective cognitive and/or atypical neurobehavioral symptoms, non-significant vascular burden on neuroimaging, and without contraindication to lumbar puncture are offered CSF analysis. Clinical diagnosis was ascribed on the basis of specialist multi-disciplinary consensus review. We undertook a case-note and database retrospective review of those who had ad-biomarker CSF analysis, collecting demographic, clinical phenotype diagnosis, and neuropsychological performance. Data was extracted and analysed using SPSS v.25.

Results

One-hundred-sixteen patients underwent CSF biomarker testing. Forty-nine patients (42%) had positive AD-CSF biomarkers, 41/49 (84%) of whom presented with common ad phenotypes (Amnestic/Logopenic PPA/PCA). Twenty patients (17%) had negative ad-CSF (elevated AB-42, and low p-tau) studies, and half of those (10/20, 50%) had a consistent atypical non-AD clinical phenotype. Patients with negative ad-CSF were younger and tended to have non-amnestic neuropsychological profile. Therefore there was a mismatch in 18/69 (26%) people in these groups with definitive +/− ad biomarker results and ad/Non-ad clinical phenotype. A further forty seven (40%) patients had indeterminate CSF studies with one or other changes in AB-42 or p-tau, but not both as is necessary for definitive diagnosis.

Conclusion

Incorporation of CSF biomarker analysis is quickly being established as a key component of the neurocognitive/dementia diagnostic pathway. However, there are challenges and limitations arising as they are applied in clinical settings, and further research is warranted to explore variations between pathological results and clinical phenotype presentation.

505 INTERLEUKIN-6, C-REACTIVE PROTEIN, FIBRINOGEN, AND RISK OF RECURRENCE AFTER ISCHEMIC STROKE: SYSTEMATIC REVIEW AND META-ANALYSIS

Background

Recent randomised trials showed benefit for anti-inflammatory therapies in coronary disease but excluded stroke. The prognostic value of blood inflammatory markers after stroke is uncertain and guidelines do not recommend their routine measurement for risk stratification.

Methods

We performed a systematic review and meta-analysis of studies investigating the association of C-reactive protein (CRP), interleukin-6 (IL-6) and fibrinogen and risk of recurrent stroke or major vascular events (MVEs). We searched EMBASE and Ovid Medline until 10/1/19. Random-effects meta-analysis was performed for studies reporting comparable effect measures.

Results

Of 2,515 reports identified, 39 met eligibility criteria (IL-6, n = 10; CRP, n = 33; fibrinogen, n = 16). An association with recurrent stroke was reported in 12/26 studies (CRP), 2/11 (fibrinogen) and 3/6 (IL-6). On random-effects meta-analysis of comparable studies, CRP was associated with an increased risk of recurrent stroke [pooled hazard ratio (HR) per 1 standard-deviation (SD) increase in loge-CRP (1.14, 95% CI 1.06-1.22, p &lt; 0.01)] and MVEs (pooled HR 1.21, CI 1.10-1.34, p &lt; 0.01). Fibrinogen was also associated with recurrent stroke (HR 1.26, CI 1.07-1.47, p &lt; 0.01) and MVEs (HR 1.31, 95% CI 1.15-1.49, p &lt; 0.01). Trends were identified for IL-6 for recurrent stroke (HR per 1-SD increase 1.17, CI 0.97-1.41, p = 0.10) and MVEs (HR 1.22, CI 0.96-1.55, p = 0.10).

Conclusion

Despite evidence suggesting an association between inflammatory markers and post-stroke vascular recurrence, substantial methodological heterogeneity was apparent between studies. Individual-patient pooled analysis and standardisation of methods are needed to determine the prognostic role of blood inflammatory markers and to improve patient selection for randomised trials of inflammatory therapies.

Measuring cardiomyocyte cellular characteristics in cardiac hypertrophy using diffusion-weighted MRI

PURPOSE

This paper presents a hierarchical modeling approach for estimating cardiomyocyte major and minor diameters and intracellular volume fraction (ICV) using diffusion-weighted MRI (DWI) data in ex vivo mouse hearts.

METHODS

DWI data were acquired on two healthy controls and two hearts 3 weeks post transverse aortic constriction (TAC) using a bespoke diffusion scheme with multiple diffusion times (Δ $$ \Delta $$ ), q-shells and diffusion encoding directions. Firstly, a bi-exponential tensor model was fitted separately at each diffusion time to disentangle the dependence on diffusion times from diffusion weightings, that is, b-values. The slow-diffusing component was attributed to the restricted diffusion inside cardiomyocytes. ICV was then extrapolated atΔ = 0 $$ \Delta =0 $$ using linear regression. Secondly, given the secondary and the tertiary diffusion eigenvalue measurements for the slow-diffusing component obtained at different diffusion times, major and minor diameters were estimated assuming a cylinder model with an elliptical cross-section (ECS). High-resolution three-dimensional synchrotron X-ray imaging (SRI) data from the same specimen was utilized to evaluate the biophysical parameters.

RESULTS

Estimated parameters using DWI data were (control 1/control 2 vs. TAC 1/TAC 2): major diameter-17.4μ $$ \mu $$ m/18.0μ $$ \mu $$ m versus 19.2μ $$ \mu $$ m/19.0μ $$ \mu $$ m; minor diameter-10.2μ $$ \mu $$ m/9.4μ $$ \mu $$ m versus 12.8μ $$ \mu $$ m/13.4μ $$ \mu $$ m; and ICV-62%/62% versus 68%/47%. These findings were consistent with SRI measurements.

CONCLUSION

The proposed method allowed for accurate estimation of biophysical parameters suggesting cardiomyocyte diameters as sensitive biomarkers of hypertrophy in the heart.

209 NEURO-MEDICAL COMPLICATIONS OF STROKE—TRENDS OVER THE DECADES IN AN ACUTE STROKE UNIT

Background

Neuro-medical complications post-stroke are common and often serious [1]. We first described complications in our stroke cohort in 1998 and sought to assess whether the severity and the nature of neuro-medical complications may have changed over time due to changes in presentation and the processes of care [2].

Methods

Analysis of stroke service database, which captures all neuro-medical complications as part of its portal for the Irish National Audit of Stroke (INAS), was completed. The frequency of each of the 19 complications was expressed as the percentage of patients that developed each complication over a certain year and over 5 years. Historical comparison was made with dataset from 1998, which captured six complications.

Results

Data on 1,283 patients presenting over 5 years between 2015–2019 was collected. The median age of all patients was 71 years (Range 21–101). In all, 19 different post-stroke complications were recorded; 48% (n = 622) had post-stroke pain, while 23.85% (n = 306) had cognitive decline. Data on 100 patients from 1998 was compared for a number of common metrics including; 21.82% (n = 275) of patients developed an LRTI in the 2015–2019 cohort compared with 14%(n = 14) in the 1998 cohort (p = 0.09) while 16.29% (n = 209) of patients developed a swallow disorder compared to 21% (n = 21) in 1998 (p = 0.22).

Conclusion

There are high levels of neuro-medical complications in stroke patients. Twenty years has seen extensive investment in hyperacute stroke care yet post-acute care complications did not appear to reduce significantly between this time, albeit with low numbers. Direction of future funding may consider the full spectrum of stroke care.