The Impact of Sociodemographic Variables on Functional Recovery following Lower Extremity Amputation.

Background: We hypothesize that sociodemographic variables, particularly disadvantaged financial environments, impact both rate of prosthetic utilization and the achievement of ambulation post major amputation.

Methods: All cases in the Vascular Quality Initiative amputation module were queried between April 2013 and January 2024. Inclusion was limited to patients who underwent below knee, through knee, and above knee amputation. Two primary outcomes were investigated: Nonambulatory status after amputation (minimum of 120 days follow-up); and, not having obtained a prosthetic limb (minimum of 90 days follow-up). The ambulation status and prosthetic status analyses had 6,984 and 6,793 patients meet inclusion, respectively. Multivariable binary logistic regression analysis was performed utilizing variables which achieved univariable significance (P < 0.05) for the outcomes.

Results: Mean follow-up for those meeting inclusion was 432 days. Among all patients meeting inclusion, 46.7% of patients did not acquire a prosthetic limb and 44.1% were nonambulatory. Sociodemographic factors with significant multivariable association for the outcome of no prosthetic limb acquisition in follow-up were as follows: advancing age (adjusted odds ratio [aOR] 1.011/year (1.006-1.016), P < 0.001); female sex (aOR 1.43 (1.28-1.61), P < 0.001); top 20% area deprivation index representing highest deprivation (aOR 1.24 (1.09-1.41) P = 0.001); race (P = 0.002) insurance status (P = 0.028) with protective status for commercial insurance (39% rate of no prosthetic) and non-US insurance (33%) versus Medicare (51%), Medicaid (48%), Veterans Affairs insurance (49%), Self-pay (42%), and Medicare Advantage (51%). There were numerous comorbidities which also had association with lack of prosthetic limb acquisition. Sociodemographic variables which achieved multivariable significance (P < 0.05) for the outcome of nonambulatory status after major amputation were as follows: female sex (aOR 1.37 (1.23-1.54), P < 0.001); Medicare insurance (P = 0.016); advancing age (aOR 1.009/year (1.004-1.014), P < 0.001); congestive heart failure (aOR 1.15 (1.02-1.31), P = 0.028); and, not living at home in follow-up (aOR (3.53 (2.99-4.17) P < 0.001). Physical therapy at any point after surgery (aOR 0.742 (0.662-0.832), P < 0.001) and commercial insurance (aOR 0.839 (0.737-0.956), P = 0.008) were protective. There were numerous comorbidities which also had association with nonambulatory status in follow-up.

Conclusions: Living within the most financially disadvantaged areas and race both have a significant independent association with lack of prosthetic limb acquisition following major amputation. Black, Native American, and Pacific Islander demographic patients experience lack of acquisition at a higher rate than White and Asian patients independent of comorbidities and socioeconomic covariables. Female patients obtain a prosthetic limb and ambulate less frequently than males after major amputation, largely due to a higher rate of above knee amputation. Comorbidities and not socioeconomic variables are the leading drivers of nonambulation.