@article{enlighten272593,
          volume = {9},
          number = {5},
           month = {October},
          author = {Syed Kazmi and Chandrasekhar Kambhampati and John G.F. Cleland and Joe Cuthbert and Khurram Shehzad Kazmi and Pierpaolo Pellicori and Alan S. Rigby and Andrew L. Clark},
           title = {Dynamic risk stratification using Markov chain modelling in patients with chronic heart failure},
       publisher = {Wiley},
            year = {2022},
         journal = {ESC Heart Failure},
           pages = {3009--3018},
             url = {https://eprints.gla.ac.uk/272593/},
        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.},
             doi = {10.1002/ehf2.14028}
}