Figure 4 - uploaded by Yen Ting Lin
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Distributions of age at which paroxysmal AF sets it (panel (a)), age at which permanent AF sets in (panel (b)), and the time elapsed between these two events (panel (c)). Data were generated from 5000 independent simulation runs of the model.
Source publication
We propose a stochastic individual-based model of the progression of atrial
fibrillation (AF). The model operates at patient level over a lifetime and is
based on elements of the physiology and biophysics of AF, making contact with
existing mechanistic models. The outputs of the model are times when the
patient is in normal rhythm and AF, and we ca...
Contexts in source publication
Context 1
... model then allows us to simulate population statistics for the age at which patients develop parox- ysmal AF ('event 1') and for the time at which they transition into permanent AF ('event 2'). These are shown in Fig. 4 (panels (a) and (b)), along with statistics of the time that elapses between the on- set of paroxysmal and permanent AF (panel (c)). It seems reasonable to assign a minimum threshold which would prompt a patient to present themselves for clin- ical diagnosis (assuming symptomatic AF). We set this threshold as an AF episode of duration ...
Context 2
... now turn to a discussion of model outputs in a form that may be clinically relevant. In our model we assume that the starting point of a patient's clinical trajectory is the time at which they develop parox- ysmal AF. Given the intrinsic stochasticity, this time point will vary from patient to patient, as indicated in panel (a) of Fig. 4 In the lower-left part of the figure we shown his- tograms of AF burden at the 15 time points indicated in the top-left panel. The numbers in the smaller panels refer to the number of years since the onset of paroxysmal AF. At initial times after the onset of paroxysmal AF the burden shows a unimodal distri- bution, and over the ...
Context 3
... literature [33,38]. However, it must be noted that the model records all events, while in real- ity these events may be asymptomatic, and therefore remain undiagnosed and therefore undocumented for many years [43]. As a consequence of the recording of asymptomatic events prior to clinical diagnosis, the time taken to transition to permanent AF (Fig. 4(c)) may appear to be overly long. The follow-up period in published studies on the transition to permanent AF (e.g. [44,45]) are of a duration of between 1 and 5 years or up to 30 years in studies of lone-AF (e.g. [42]), and include patients in both paroxysmal and persistent states at recruitment, so direct comparison with the present ...
Context 4
... AF (e.g. [44,45]) are of a duration of between 1 and 5 years or up to 30 years in studies of lone-AF (e.g. [42]), and include patients in both paroxysmal and persistent states at recruitment, so direct comparison with the present model result is challenging. However if we con- sider the age of transition of the patient to permanent AF, see Fig. 4(b), this does reflect findings in the liter- ature that age is an independent predictor of chronic AF (both persistent and permanent) and that the risk associated with age increases beyond the age of 74 [5]. Additionally, this model takes no account of any med- ical interventions where the transition to permanent AF may be affected by ...
