Dynamic risk stratification using Markov chain modelling in patients with chronic heart failure. (23rd June 2022)

• Record Type: Journal Article
• Authors: Kazmi, Syed; Kambhampati, Chandrasekhar; Cleland, John G.F.; Cuthbert, Joe; Kazmi, Khurram Shehzad; Pellicori, Pierpaolo; Rigby, Alan S.; Clark, Andrew L.
• Is Part Of: ESC heart failure. Volume 9:Number 5(2022)
• Page Start: 3009
• Page End: 3018
• Publication Date: 2022-06-23
• Subjects: Heart failure -- Absorbing Markov chains -- Disease trajectory -- Artificial intelligence -- Machine learning; Heart failure -- Periodicals; 616.129005
• DOI: 10.1002/ehf2.14028
• Languages: English
• ISSNs: 2055-5822

Abstract

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.