Diabetes, Lower-Extremity Amputation, and Death

Ole Hoffstad; Nandita Mitra; Jonathan Walsh; David J. Margolis


Diabetes Care. 2015;38(10):1852-1857. 

In This Article


Between 2003 and 2012, 416,434 individuals met the entrance criteria for the study. This cohort accrued an average of 9.0 years of follow-up and a total of 3.7 million diabetes person-years of follow-up. During this period of time, 6,566 (1.6%) patients had an LEA and 77,215 patients died (18.5%). Additional demographic information is reported in Table 1. Nearly all of the risk factors were statistically significantly different with respect to those who had an LEA versus those who did not and those who died versus those who did not (Table 1). The percentage of individuals who died within 30 days, 1 year, and by year 5 of their initial code for an LEA was 1.0%, 9.9%, and 27.2%, respectively. For those >65 years of age, the rates were 12.2% and 31.7%, respectively. For the full cohort of those with diabetes, the rate of death was 2.0% after 1 year of follow up and 7.3% after 5 years of follow up. In general, those with an LEA were more than three times more likely to die during a year of follow-up than an individual with diabetes who had not had an LEA.

From 2003 to 2012, the HR for death after an LEA was 3.02 (95% CI 2.90, 3.14). The HRs for the potential risk factors are presented in Table 2. With respect to death, two other risk factors had HRs similar to LEA: CHF (3.11 [95% CI 3.04, 3.18]) and age >65 years (3.58 [3.52, 3.64]). As noted above, our a priori assumption was that the HR associating LEA with death would be fully diminished (i.e., it would become 1) when adjusted for the other risk factor variables. However, the fully adjusted LEA HR was diminished only ~22% to 2.37 (95% CI 2.27, 2.48). With the exception of age >65 years, individual risk factors, in general, had minimal effect (<10%) on the HR of the association between LEA and death (Table 3). This was also true for clinical practice (data not shown). Furthermore, we estimated the HRs of each of our risk factors just among those who had an LEA in order to evaluate their effect among those with an LEA. In general, the effect estimates for each risk factor were diminished in the LEA cohort compared with the cohort of patients with diabetes (Table 2). A similar finding was noted if we limited our analysis to just those who had documentation of a major LEA (Table 2). With respect to the ability of our models to predict death, a model just containing LEA had an AUC of 0.51, which is poorly predictive (Table 3). As would be expected, the best predictors were older age and the Charlson index (Table 3). Our fully adjusted model had a moderate AUC of 0.76.

We conducted sensitivity analyses to determine the general statistical parameters of an unmeasured risk factor that could remove the association of LEA with death. We found that even if there existed a very strong risk factor with an HR of death of three, a prevalence of 10% in the general diabetes population, and a prevalence of 60% in those who had an LEA, LEA would still be associated with a statistically significant and clinically important risk of 1.30. These findings are describing a variable that would seem to be so common and so highly associated with death that it should already be clinically apparent. We also conducted sensitivity analysis excluding individuals who died within the first 30 days after their LEA. These sensitivity analyses also included adjustment for measurements of total cholesterol and LDL and HDL (which were only available for ~65% of the population) and blood pressure. These secondary sensitivity analyses demonstrated very minimal effects on the adjusted effect estimate between LEA and all-cause death as noted in Table 2.