Bayesian neural network approach for determining the risk of re-intervention after endovascular aortic aneurysm repair

This article proposes a Bayesian neural network approach to determine the risk of re-intervention after endovascular aortic aneurysm repair surgery. The target of proposed technique is to determine which patients have high chance to re-intervention (high-risk patients) and which are not (low-risk patients) after 5 years of the surgery. Two censored datasets relating to the clinical conditions of aortic aneurysms have been collected from two different vascular centers in the United Kingdom. A Bayesian network was first employed to solve the censoring issue in the datasets. Then, a back propagation neural network model was built using the uncensored data of the first center to predict re-intervention on the second center and classify the patients into high-risk and low-risk groups. Kaplan-Meier curves were plotted for each group of patients separately to show whether there is a significant difference between the two risk groups. Finally, the logrank test was applied to determine whether the neural network model was capable of predicting and distinguishing between the two risk groups. The results show that the Bayesian network used for uncensoring the data has improved the performance of the neural networks that were built for the two centers separately. More importantly, the neural network that was trained with uncensored data of the first center was able to predict and discriminate between groups of low risk and high risk of re-intervention after 5 years of endovascular aortic aneurysm surgery at center 2 (p = 0.0037 in the logrank test).

An artificial neural network stratifies the risks of reintervention and mortality after endovascular aneurysm repair:a retrospective observational study

Background Lifelong surveillance after endovascular repair (EVAR) of abdominal aortic aneurysms (AAA) is considered mandatory to detect potentially life-threatening endograft complications. A minority of patients require reintervention but cannot be predictively identified by existing methods. This study aimed to improve the prediction of endograft complications and mortality, through the application of machine-learning techniques. Methods Patients undergoing EVAR at 2 centres were studied from 2004-2010. Pre-operative aneurysm morphology was quantified and endograft complications were recorded up to 5 years following surgery. An artificial neural networks (ANN) approach was used to predict whether patients would be at low- or high-risk of endograft complications (aortic/limb) or mortality. Centre 1 data were used for training and centre 2 data for validation. ANN performance was assessed by Kaplan-Meier analysis to compare the incidence of aortic complications, limb complications, and mortality; in patients predicted to be low-risk, versus those predicted to be high-risk. Results 761 patients aged 75 +/- 7 years underwent EVAR. Mean follow-up was 36+/- 20 months. An ANN was created from morphological features including angulation/length/areas/diameters/ volume/tortuosity of the aneurysm neck/sac/iliac segments. ANN models predicted endograft complications and mortality with excellent discrimination between a low-risk and high-risk group. In external validation, the 5-year rates of freedom from aortic complications, limb complications and mortality were 95.9% vs 67.9%; 99.3% vs 92.0%; and 87.9% vs 79.3% respectively (p0.001) Conclusion This study presents ANN models that stratify the 5-year risk of endograft complications or mortality using routinely available pre-operative data.

Patients' and physicians' experiences of atrial fibrillation consultations and anticoagulation decision-making:a multi-perspective IPA design

OBJECTIVE: To explore patients' and physicians' experiences of atrial fibrillation consultations and oral anticoagulation decision-making. DESIGN: Multi-perspective interpretative phenomenological analyses. METHODS: Participants included small homogeneous subgroups: AF patients who accepted (n=4), refused (n=4), or discontinued (n=3) warfarin, and four physician subgroups (n=4 each group): consultant cardiologists, consultant general physicians, general practitioners and cardiology registrars. Semi-structured interviews were conducted. Transcripts were analysed using multi-perspective IPA analyses to attend to individuals within subgroups and making comparisons within and between groups. RESULTS: Three themes represented patients' experiences: Positioning within the physician-patient dyad, Health-life balance, and Drug myths and fear of stroke. Physicians' accounts generated three themes: Mechanised metaphors and probabilities, Navigating toward the 'right' decision, and Negotiating systemic factors. CONCLUSIONS: This multi-perspective IPA design facilitated an understanding of the diagnostic consultation and treatment decision-making which foregrounded patients' and physicians' experiences. We drew on Habermas' theory of communicative action to recommend broadening the content within consultations and shifting the focus to patients' life contexts. Interventions including specialist multidisciplinary teams, flexible management in primary care, and multifaceted interventions for information provision may enable the creation of an environment that supports genuine patient involvement and participatory decision-making.

Psychological influence of the media on patients commencing oral anticoagulation in atrial fibrillation:a qualitative analysis

Background: Oral anticoagulation (OAC) reduces stroke risk in patients with atrial fibrillation (AF); however it is still underutilized and sometimes refused by patients. Two inter-related studies were undertaken to understand the experiences and what influences this un- derutilisation of warfarin treatment in AF patients. These studies explored physician and patient experiences of AF and OAC treatment. The paper focuses on specific sub-themes from the study that explored patients’ experiences will be discussed. Aim: The study in question aimed to explore the experiences which influence patients’ decisions to accept, decline or discontinue OAC. Methods: Semi-structured individual interviews with patients were con- ducted. Three sub-groups of patients (n = 11) diagnosed with AF were interviewed; those who accepted, refused, and who discontinued war- farin. Interpretative phenomenological analysis (IPA) was used to examine the data. IPA is a qualitative method that focuses on how participants make sense of an experiences phenomenon Results: Three over-arching themes comprised patients’ experiences: (i)the initial consultation, (ii) life after the consultation, and (iii) patients’reflections. In the last theme, patients reflected on their perceptions ofaspirin and warfarin. Aspirin was perceived as a natural wonder-drugwhile warfarin was perceived as a dangerous drug usually given to peo-ple at the end of their life. Interestingly they perceive both drugs as‘old’. However, for aspirin it had a positive association, old meaningtried and tested. While for warfarin, old meant ‘has been around fortoo long’.Conclusion: Media had an important role in how patients’ perceptionsof these two drugs were influenced. Literature shows that framingtechniques, i.e. using certain words or phrases such as ‘rat poison’, areprocesses adopted by media to alter medical knowledge into lay per-son’s language. Patients in turn form negative cognitive schemas,between the word ‘poison’ and warfarin, leading to the negative per-ception of warfarin which could influence non-adherence to treatment.This qualitative research highlighted the potential influences of themedia on AF patient perceptions commencing OAC treatment. Theassociation between media stimuli and patient perceptions on OACshould be further explored. The influential power of lay-media couldalso be instrumental in disseminating appropriate educational materialto the public

Developing a complex educational–behavioural intervention:the TREAT intervention for patients with atrial fibrillation

This article describes the theoretical and pragmatic development of a patient-centred intervention for patients with atrial fibrillation (AF). Theoretical models (Common Sense Model, Necessity-Concerns Framework), clinical frameworks, and AF patient feedback contributed to the design of a one-off hour-long behaviour-change intervention package. Intervention materials consisted of a DVD, educational booklet, diary and worksheet, which were patient-centred and easy to administer. The intervention was evaluated within a randomised controlled trial. Several “active theoretical ingredients” were identified (for e.g., where patients believed their medication was less harmful they spent more time within the therapeutic range (TTR), with general harm scores predicting TTR at 6 months). Allowing for social comparison and adopting behaviour change techniques enabled accurate patient understanding of their condition and medication. The process of developing the intervention using theory-derived content and evaluation tools allowed a greater understanding of the mechanisms by which this intervention was successful. Alleviating concerns about treatment medication by educating patients can help to improve adherence. This process of intervention development could be adopted for a range of chronic illnesses and treatments. Critical elements should include the use of: (1) clinical guidelines; (2) appropriate theoretical models; (3) patient input; and (4) appropriate evaluation tools.

The risk of re-intervention after endovascular aortic aneurysm repair

This thesis studies survival analysis techniques dealing with censoring to produce predictive tools that predict the risk of endovascular aortic aneurysm repair (EVAR) re-intervention. Censoring indicates that some patients do not continue follow up, so their outcome class is unknown. Methods dealing with censoring have drawbacks and cannot handle the high censoring of the two EVAR datasets collected. Therefore, this thesis presents a new solution to high censoring by modifying an approach that was incapable of differentiating between risks groups of aortic complications. Feature selection (FS) becomes complicated with censoring. Most survival FS methods depends on Cox's model, however machine learning classifiers (MLC) are preferred. Few methods adopted MLC to perform survival FS, but they cannot be used with high censoring. This thesis proposes two FS methods which use MLC to evaluate features. The two FS methods use the new solution to deal with censoring. They combine factor analysis with greedy stepwise FS search which allows eliminated features to enter the FS process. The first FS method searches for the best neural networks' configuration and subset of features. The second approach combines support vector machines, neural networks, and K nearest neighbor classifiers using simple and weighted majority voting to construct a multiple classifier system (MCS) for improving the performance of individual classifiers. It presents a new hybrid FS process by using MCS as a wrapper method and merging it with the iterated feature ranking filter method to further reduce the features. The proposed techniques outperformed FS methods based on Cox's model such as; Akaike and Bayesian information criteria, and least absolute shrinkage and selector operator in the log-rank test's p-values, sensitivity, and concordance. This proves that the proposed techniques are more powerful in correctly predicting the risk of re-intervention. Consequently, they enable doctors to set patients’ appropriate future observation plan.

miRNAS circulantes como biomarcadores para fibrilação atrial aguda

Atrial fibrillation (AF) is the most common sustained cardiac arrhythmia. Some non-coding RNAs (miRNAs) have been involved in regulatory activity in arrhythmogenesis, targeting genes that contribute to the development of AF. The present study aimed to evaluate the expression of candidate miRNAs in plasma from patients with AF and new-onset AF and its application as future markers for diagnosis and monitoring of disease. miR-21, miR-133a, miR-133b, miR-150, miR-328 and miR-499 were selected as targets in this study through a prior literature review. They were isolated from plas-ma of individuals aged from 20 to 85 years old with AF (n = 17), new-onset AF (n = 5) and without AF (n = 15), where the latter was the control group. The results were ana-lyzed by Real-Time PCR (RT-PCR) with miScript SYBR Green PCR. We observed that miR-21, miR-133b, miR-328 and miR-499 had different levels of expression be-tween the three groups (p <0.05). Increased expression of miR-21 (0.6-fold), miR-133b (1.4-fold), miR-328 (2.0-fold) and miR-499 (2.3-fold) in patients with new-onset AF when compared to AF and control subjects. The miR-133a and miR-150 expression did not differ among the groups. miR-21, miR-133b, miR-328 and miR-499 may be potential biomarkers for AF as well as for new-onset AF, for monitoring and for the di-agnosis. These findings may contribute to the understanding of the process that trig-gers AF and suggest application these molecules as future biomarkers for AF.

miRNAS circulantes como biomarcadores para fibrilação atrial aguda

Atrial fibrillation (AF) is the most common sustained cardiac arrhythmia. Some non-coding RNAs (miRNAs) have been involved in regulatory activity in arrhythmogenesis, targeting genes that contribute to the development of AF. The present study aimed to evaluate the expression of candidate miRNAs in plasma from patients with AF and new-onset AF and its application as future markers for diagnosis and monitoring of disease. miR-21, miR-133a, miR-133b, miR-150, miR-328 and miR-499 were selected as targets in this study through a prior literature review. They were isolated from plas-ma of individuals aged from 20 to 85 years old with AF (n = 17), new-onset AF (n = 5) and without AF (n = 15), where the latter was the control group. The results were ana-lyzed by Real-Time PCR (RT-PCR) with miScript SYBR Green PCR. We observed that miR-21, miR-133b, miR-328 and miR-499 had different levels of expression be-tween the three groups (p <0.05). Increased expression of miR-21 (0.6-fold), miR-133b (1.4-fold), miR-328 (2.0-fold) and miR-499 (2.3-fold) in patients with new-onset AF when compared to AF and control subjects. The miR-133a and miR-150 expression did not differ among the groups. miR-21, miR-133b, miR-328 and miR-499 may be potential biomarkers for AF as well as for new-onset AF, for monitoring and for the di-agnosis. These findings may contribute to the understanding of the process that trig-gers AF and suggest application these molecules as future biomarkers for AF.

The effects of stenting and endothelial denudation on experimental aneurysm healing and gene expression following endovascular treatment

Mémoire numérisé par la Direction des bibliothèques de l'Université de Montréal.

Influence of Outlet Boundary Conditions on Cerebrovascular Aneurysm Hemodynamics

Computational fluid dynamic (CFD) studies of blood flow in cerebrovascular aneurysms have potential to improve patient treatment planning by enabling clinicians and engineers to model patient-specific geometries and compute predictors and risks prior to neurovascular intervention. However, the use of patient-specific computational models in clinical settings is unfeasible due to their complexity, computationally intensive and time-consuming nature. An important factor contributing to this challenge is the choice of outlet boundary conditions, which often involves a trade-off between physiological accuracy, patient-specificity, simplicity and speed. In this study, we analyze how resistance and impedance outlet boundary conditions affect blood flow velocities, wall shear stresses and pressure distributions in a patient-specific model of a cerebrovascular aneurysm. We also use geometrical manipulation techniques to obtain a model of the patient’s vasculature prior to aneurysm development, and study how forces and stresses may have been involved in the initiation of aneurysm growth. Our CFD results show that the nature of the prescribed outlet boundary conditions is not as important as the relative distributions of blood flow through each outlet branch. As long as the appropriate parameters are chosen to keep these flow distributions consistent with physiology, resistance boundary conditions, which are simpler, easier to use and more practical than their impedance counterparts, are sufficient to study aneurysm pathophysiology, since they predict very similar wall shear stresses, time-averaged wall shear stresses, time-averaged pressures, and blood flow patterns and velocities. The only situations where the use of impedance boundary conditions should be prioritized is if pressure waveforms are being analyzed, or if local pressure distributions are being evaluated at specific time points, especially at peak systole, where the use of resistance boundary conditions leads to unnaturally large pressure pulses. In addition, we show that in this specific patient, the region of the blood vessel where the neck of the aneurysm developed was subject to abnormally high wall shear stresses, and that regions surrounding blebs on the aneurysmal surface were subject to low, oscillatory wall shear stresses. Computational models using resistance outlet boundary conditions may be suitable to study patient-specific aneurysm progression in a clinical setting, although several other challenges must be addressed before these tools can be applied clinically.

The effects of stenting and endothelial denudation on experimental aneurysm healing and gene expression following endovascular treatment

Mémoire numérisé par la Direction des bibliothèques de l'Université de Montréal.

Processing the Intracardiac Electrogram for Atrial Fibrillation Ablation

Atrial fibrillation (AF) is a major global health issue as it is the most prevalent sustained supraventricular arrhythmia. Catheter-based ablation of some parts of the atria is considered an effective treatment of AF. The main objective of this research is to analyze atrial intracardiac electrograms (IEGMs) and extract insightful information for the ablation therapy. Throughout this thesis we propose several computationally efficient algorithms that take streams of IEGMs from different atrial sites as the input signals, sequentially analyze them in various domains (e.g., time and frequency), and create color-coded three-dimensional map of the atria to be used in the ablation therapy.

Progression of left atrial volume index in a population at risk for heart failure:a substudy of the STOP-HF (St Vincent's Screening TO Prevent Heart Failure) trial

AIMS: Limited data are available concerning the evolution of the left atrial volume index (LAVI) in pre-heart failure (HF) patients. The aim of this study was to investigate clinical characteristics and serological biomarkers in a cohort with risk factors for HF and evidence of serial atrial dilatation.

METHODS AND RESULTS: This was a prospective substudy within the framework of the STOP-HF cohort (NCT00921960) involving 518 patients with risk factors for HF electively undergoing serial clinical, echocardiographic, and natriuretic peptide assessment. Mean follow-up time between assessments was 15 ± 6 months. 'Progressors' (n = 39) were defined as those with serial LAVI change ≥3.5 mL/m(2) (and baseline LAVI between 20 and 34 mL/m(2)). This cut-off was derived from a calculated reference change value above the biological, analytical, and observer variability of serial LAVI measurement. Multivariate analysis identified significant baseline clinical associates of LAVI progression as increased age, beta-blocker usage, and left ventricular mass index (all P < 0.05). Serological biomarkers were measured in a randomly selected subcohort of 30 'Progressors' matched to 30 'Non-progressors'. For 'Progressors', relative changes in matrix metalloproteinase 9 (MMP9), tissue inhibitor of metalloproteinase 1 (TIMP1), and the TIMP1/MMP9 ratio, markers of interstitial remodelling, tracked with changes in LAVI over time (all P < 0.05).

CONCLUSION: Accelerated LAVI increase was found to occur in up to 14% of all pre-HF patients undergoing serial echocardiograms over a relatively short follow-up period. In a randomly selected subcohort of 'Progressors', changes in LAVI were closely linked with alterations in MMP9, TIMP1, and the ratio of these enzymes, a potential aid in highlighting this at-risk group.