The dynamics of disease progression in sepsis: Markov modeling describing the natural history and the likely impact of effective antisepsis agents

Clin Infect Dis. 1998 Jul;27(1):185-90. doi: 10.1086/514630.


We conducted a 9-month prospective cohort study of 2,527 patients with systemic inflammatory response syndrome in three intensive care units and three general wards in a tertiary health care institution. Markov models were developed to predict the probability of movement to and from more severe stages--sepsis, severe sepsis, or septic shock--at 1, 3, and 7 days. For patients with sepsis, severe sepsis, and septic shock, the probabilities of remaining in the same category after 1 day were .65, .68, and .61, respectively. The probability for progression after 1 day was .09 for sepsis to severe sepsis and .026 for severe sepsis to shock. The probability of patients with sepsis, severe sepsis, and septic shock dying after 1 day was .005, .009, and .079, respectively. The model can be used to predict the reduction in end organ dysfunction and mortality with use of increasingly effective antisepsis agents.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Disease Progression
  • Humans
  • Intensive Care Units
  • Markov Chains
  • Probability
  • Prospective Studies
  • Sepsis / drug therapy
  • Sepsis / mortality
  • Sepsis / physiopathology*
  • Systemic Inflammatory Response Syndrome / drug therapy
  • Systemic Inflammatory Response Syndrome / mortality
  • Systemic Inflammatory Response Syndrome / physiopathology