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RF20 Comparing strategies to prevent stroke and ischemic heart disease in the tunisian population: markov modeling approach using a comprehensive sensitivity analysis algorithm
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  1. O Saidi1,
  2. M O’Flaherty2,
  3. N Zoghlami1,
  4. D Malouche1,3,
  5. S Capewell2,
  6. J Critchley4,
  7. P Bandosz2,
  8. F Hentati5,
  9. B Romdhane1,
  10. M Guzman-Castillo2
  1. 1Cardiovascular Epidemiology and Prevention Research Laboratory, University Tunis El Manar, Tunis, Tunisia
  2. 2Department of Public Health and Policy, University of Liverpool, Liverpool, UK
  3. 3National Institute of Statistics and Data Analysis Tunis, Tunis, Tunisia
  4. 4Population Health Research Institute, University of London, London, UK
  5. 5National Institute of Neurology Tunis, Tunis, Tunisia

Abstract

Background Premature heart disease and stroke are generating a large and growing burden of disease and death in low and middle income countries. Though eminently preventable, debate continues about whether to prioritise primary, secondary or tertiary prevention.

The application of mathematical models in medicine and population health has proven useful, offering the potential to analyse and compare the effectiveness of different interventions to prevent future cardiovascular disease. We therefore developed a comprehensive algorithm of sensitivity analysis on Markov model applied to evaluate the impact of three interventions to reduce Ischemic Heart Diseases (IHD) and Stroke deaths: (i) improving medical treatments in acute phase, (ii) secondary prevention of stroke by increasing the prescribing of statins, (iii) primary prevention using health promotion to reduce dietary salt consumption.

Methods We developed and validated a Markov model for the Tunisian population aged 35–94 years old over a 20 year time horizon.

We compared the impact of specific treatment of stroke, life style and primary prevention on both IHD and stroke deaths. We reported the total number of CVD deaths (ischemic stroke and IHD deaths) that may be prevented or postponed for each specific scenario.

We then undertook extensive sensitivity analyses using a probabilistic multivariate approach and a simple linear regression metamodeling using R software.

Results The model forecasts a dramatic mortality rise, with approximately 1 11 000 cumulative IHD and Stroke deaths (95% uncertainty interval 107,000– 115,000) predicted in 2025 in Tunisia.

Dietary salt reduction offered the potentially most powerful preventive intervention. This population level strategy might reduce IHD and stroke deaths by 27%, compared with 3% for secondary prevention following stroke and 1% for medical strategies for primary prevention.

The metamodeling highlighted that that the initial development of a minor stroke substantially increased the subsequent probability of a fatal stroke or IHD death.

Conclusion The primary prevention of cardiovascular disease via a reduction in dietary salt consumption appeared much more effective that secondary or tertiary prevention approaches applied after disease had manifest in individual patients.

Our simple but comprehensive algorithm offers a potentially attractive methodological approach that might now be extended and replicated in other contexts and populations.

  • Sensitivity analysis
  • Metamodeling
  • Linear regression
  • Markov model
  • Stroke
  • Tunisia

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