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Appendix Figure 1. Markov model of diabetes disease progression. The model is used to follow the disease progression of all members of a cohort simultaneously on 5 different disease paths. At the end of any period, the cohort occupies one state on each of the disease paths. For the simulation, transitions between states take place at discrete time intervals 1 year apart. Thus, at the end of each 1-year period, portions of the cohort can move from one disease state to another or stay in the same disease state. The simulation program determines what proportion of the cohort will move from one state to another on the basis of the transition probability. In several cases, an individual can experience a complication event that the patient either dies of or survives during the period. The Markov model keeps track of the number of patients who are in each state in each period. It also tracks the cumulative incidence of patients who have undergone complication events, such as lower-extremity amputation (LEA), angina, cardiac arrest (CA) or myocardial infarction (MI), and stroke. In the diagrams, complication events are represented by diamonds; states are numbered and represented by ovals. CHD = coronary heart disease. ESRD = end-stage renal disease.
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Diabetes diagnosis by screening; 
Diabetes diagnosed clinically.