Page 13 - Laurens Bosman
P. 13

Aims and outline of this thesis

              Our aim to find ways to improve arrhythmic risk prediction in ARVC started with a systematic
              review and meta-analysis of the current literature in Chapter 3. In this study we identified
              several risk factors with consistent evidence supporting their association with increased risk
              of ventricular arrhythmia. These results led to our hypothesis that we could use these risk
              factors  combined  in  a  multivariable  prediction  model  to  estimate  the  risk  of  ventricular
              arrhythmia risk of individual patients. In order to conduct such a study, we needed to have a
              large longitudinal dataset of ARVC patients, for which we had to redesign the Netherlands
              ACM Registry database as described in Chapter 4.

                   In Chapter 5 we confirmed our hypothesis by successfully developing a risk prediction
              model using the eight risk predictors we pre-selected (based on the results in Chapter 3). The
              resulting model predicts the risk of a first sustained ventricular arrhythmia in ARVC patients
              without a prior sustained event (i.e. primary prevention). In Chapter 6 we study the relation
              between  physical  exercise  and  arrhythmic  risk  in  ARVC  patients,  and  explore  if  adding
              exercise  as  a  risk  factor  would  improve  the  risk  prediction  model  we  developed.  As  the
              prediction model in Chapter 5 was designed to be used for primary prevention patients only,
              we  subsequently  developed  a  model  for  all  ARVC  patients  as  described  in  Chapter  7.
              Furthermore, instead of predicting any type of sustained ventricular arrhythmia, this second
              model predicts fast (>250 beats per minute) events to closer approximate the risk of SCD.

                   Alternative to our two prediction models, there are several risk stratification flow-charts
              available from published guidelines and consensus documents.   In contrast to our models,
              these flow-charts are designed by expert consensus, hence their actual clinical performance
              was unknown. The aim of our study in Chapter 8 was to estimate and compare the clinical
              performance of these stratification flow-charts.

                   Moving away from prognosis, in Chapter 9 we focus on the clinical diagnosis of ARVC.
              There is no single gold standard test to diagnose ARVC, instead, the diagnosis is determined
              by a complex set of different tests and criteria as specified in the Task Force Criteria (TFC).
              While many studies focus on finding ways to improve the diagnostic performance of the TFC,
              no study had validated the clinical performance of the TFC as a whole in a real-life consecutive
              diagnostic  cohort.  Therefore,  in  Chapter  9  we  validate  the  performance  and  evaluate
              strengths and weaknesses that could guide future studies regarding criteria improvements.

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