Dynamic risk stratification using Markov chain modelling in patients with chronic heart failure

Kazmi, S., Kambhampati, C., Cleland, J. G.F. , Cuthbert, J., Kazmi, K. S., Pellicori, P. , Rigby, A. S. and Clark, A. L. (2022) Dynamic risk stratification using Markov chain modelling in patients with chronic heart failure. ESC Heart Failure, (doi: 10.1002/ehf2.14028) (PMID:35736536) (Early Online Publication)

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Abstract

Aims: Risk changes with the progression of disease and the impact of treatment. We developed a dynamic risk stratification Markov chain model using artificial intelligence in patients with chronic heart failure (CHF). Methods and results: We described the pattern of behaviour among 7496 consecutive patients assessed for suspected HF. The following mutually exclusive health states were defined and assessed every 4 months: death, hospitalization, outpatient visit, no event, and leaving the service altogether (defined as no event at any point following assessment). The observed figures at the first transition (4 months) weres 427 (6%), 1559 (21%), 2254 (30%), 1414 (19%), and 1842 (25%), respectively. The probabilities derived from the first two transitions (i.e. from baseline to 4 months and from 4 to 8 months) were used to construct the model. An example of the model's prediction is that at cycle 4, the cumulative probability of death was 14%; leaving the system, 37%; being hospitalized between 12 and 16 months, 10%; having an outpatient visit, 8%; and having no event, 31%. The corresponding observed figures were 14%, 41%, 10%, 15%, and 21%, respectively. The model predicted that during the first 2 years, a patient had a probability of dying of 0.19, and the observed value was 0.18. Conclusions: A model derived from the first 8 months of follow‐up is strongly predictive of future events in a population of patients with chronic heart failure. The course of CHF is more linear than is commonly supposed, and thus more predictable.

Item Type:Articles
Status:Early Online Publication
Refereed:Yes
Glasgow Author(s) Enlighten ID:Cleland, Professor John and Pellicori, Dr Pierpaolo
Authors: Kazmi, S., Kambhampati, C., Cleland, J. G.F., Cuthbert, J., Kazmi, K. S., Pellicori, P., Rigby, A. S., and Clark, A. L.
College/School:College of Medical Veterinary and Life Sciences > School of Health & Wellbeing > Robertson Centre
Journal Name:ESC Heart Failure
Publisher:Wiley
ISSN:2055-5822
ISSN (Online):2055-5822
Published Online:23 June 2022
Copyright Holders:Copyright © 2022 The Authors
First Published:First published in ESC Heart Failure 2022
Publisher Policy:Reproduced under a Creative Commons License

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Project CodeAward NoProject NamePrincipal InvestigatorFunder's NameFunder RefLead Dept
303944BHF Centre of ExcellenceColin BerryBritish Heart Foundation (BHF)RE/18/6/34217CAMS - Cardiovascular Science