학술논문
Dynamic risk stratification using Markov chain modelling in patients with chronic heart failure.
Document Type
Academic Journal
Author
Kazmi S; Department of Academic Cardiology, Hull University Teaching Hospital NHS Trust, Hull, UK.; Department of Computer Science and Technology, University of Hull, Hull, UK.; Kambhampati C; Department of Computer Science and Technology, University of Hull, Hull, UK.; Cleland JGF; Robertson Centre for Biostatistics and Clinical Trials, University of Glasgow, Glasgow, UK.; Cuthbert J; Department of Academic Cardiology, Hull University Teaching Hospital NHS Trust, Hull, UK.; Department of Cardiorespiratory Medicine, Centre for Clinical Sciences, Hull York Medical School, University of Hull, Hull, UK.; Kazmi KS; Department of General Medicine, Ghurki Trust Teaching Hospital, Lahore, Pakistan.; Pellicori P; Robertson Centre for Biostatistics and Clinical Trials, University of Glasgow, Glasgow, UK.; Rigby AS; Hull York Medical School, University of Hull, Hull, UK.; Clark AL; Department of Academic Cardiology, Hull University Teaching Hospital NHS Trust, Hull, UK.
Source
Publisher: John Wiley & Sons Ltd on behalf of the European Society of Cardiology Country of Publication: England NLM ID: 101669191 Publication Model: Print-Electronic Cited Medium: Internet ISSN: 2055-5822 (Electronic) Linking ISSN: 20555822 NLM ISO Abbreviation: ESC Heart Fail Subsets: MEDLINE
Subject
Language
English
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.
(© 2022 The Authors. ESC Heart Failure published by John Wiley & Sons Ltd on behalf of European Society of Cardiology.)
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.
(© 2022 The Authors. ESC Heart Failure published by John Wiley & Sons Ltd on behalf of European Society of Cardiology.)