Search Results
Association of Footprint Measurements with Plantar Kinetics
A Linear Regression Model
Background
The use of foot measurements to classify morphology and interpret foot function remains one of the focal concepts of lower-extremity biomechanics. However, only 27% to 55% of midfoot variance in foot pressures has been determined in the most comprehensive models. We investigated whether dynamic walking footprint measurements are associated with inter-individual foot loading variability.
Methods
Thirty individuals (15 men and 15 women; mean ± SD age, 27.17 ± 2.21 years) walked at a self-selected speed over an electronic pedography platform using the midgait technique. Kinetic variables (contact time, peak pressure, pressure-time integral, and force-time integral) were collected for six masked regions. Footprints were digitized for area and linear boundaries using digital photo planimetry software. Six footprint measurements were determined: contact area, footprint index, arch index, truncated arch index, Chippaux-Smirak index, and Staheli index. Linear regression analysis with a Bonferroni adjustment was performed to determine the association between the footprint measurements and each of the kinetic variables.
Results
The findings demonstrate that a relationship exists between increased midfoot contact and increased kinetic values in respective locations. Many of these variables produced large effect sizes while describing 38% to 71% of the common variance of select plantar kinetic variables in the medial midfoot region. In addition, larger footprints were associated with larger kinetic values at the medial heel region and both masked forefoot regions.
Conclusions
Dynamic footprint measurements are associated with dynamic plantar loading kinetics, with emphasis on the midfoot region.
Background: To compare pathogens involved in skin and soft-tissue infections (SSTIs) and pedal osteomyelitis (OM) in patients with and without diabetes with puncture wounds to the foot.
Methods: We evaluated 113 consecutive patients between June 1, 2011, and March 31, 2019, with foot infection (SSTIs and OM) from a puncture injury sustained to the foot. Eighty-three patients had diabetes and 30 did not. We evaluated the bacterial pathogens in patients with SSTIs and pedal OM.
Results: Polymicrobial infections were more common in patients with diabetes mellitus (83.1% versus 53.3%; P = .001). The most common pathogen for SSTIs and OM in patients with diabetes was Staphylococcus aureus (SSTIs, 50.7%; OM, 32.3%), whereas in patients without diabetes it was Pseudomonas (25%) for SSTIs. Anaerobes (9.4%) and fungal infection (3.1%) were uncommon. Pseudomonas aeruginosa was identified in only 5.8% of people with diabetes.
Conclusions: The most common bacterial pathogen in both SSTIs and pedal OM was S aureus in patients with diabetes. Pseudomonas species was the most common pathogen in people without diabetes with SSTIs.
Background
Persons with diabetes have a higher incidence of fractures compared with persons without diabetes. However, there is little published information concerning the deleterious effect of late-stage diabetes on fracture healing. There are no studies using animal models that evaluate the effect of advanced diabetes on fracture healing. The purpose of our study was to evaluate cytokine expression, specifically macrophage inflammatory protein 1 (MIP-1) and vascular endothelial growth factor, in fracture healing in a type 2 diabetes rat model.
Methods
We evaluated biomarker expression after femur fracture using a rat model. The two groups consisted of 24 Zucker diabetic rats (study group) and 12 Zucker lean rats (control group). An independent reviewer was used to assess delayed union. We evaluated serum samples 2, 4, 7, and 14 days after surgery for MIP-1, vascular endothelial growth factor, leptin, and other cytokine levels.
Results
At 3 weeks, Kaplan-Meier estimates showed that 45.8% of femur fractures in Zucker diabetic rats had healed, whereas 81.8% of those in Zucker lean rats had healed (P = .02). A logistic regression model to predict fast healing that included the three cytokines and diabetes status showed that the only factor achieving significance was MIP-1α. Vascular endothelial growth factor was the only biomarker to show significance compared with delayed healing.
Conclusions
These results confirm significant differences in biomarker expression between diabetic and nondiabetic rats during bone healing. The key factors for bone healing may appear early in the healing process, whereas differences in diabetes versus nondiabetes are seen later in the healing process. Increased levels of MIP-1α were associated with the likelihood of delayed healing.
Background: The aim of this study was to evaluate the incidence and recovery of acute kidney injury (AKI) in patients admitted to the hospital with and without diabetes mellitus (DM) with foot infections.
Methods: We retrospectively reviewed 294 patients with DM and 88 without DM admitted to the hospital with foot infections. The Kidney Disease: Improving Global Outcomes guidelines were used to define AKI. Recovery was divided into three categories: full, partial, and no recovery within 90 days of the index AKI.
Results: The AKI incidence was 3.0 times higher in patients with DM (DM 48.5% versus no DM 23.9%; 95% confidence interval [CI], 1.74–5.19; P < .01). Acute kidney injury incidence was similar at each stage in people with and without DM (stage 1, DM 58.1% versus no DM 47.6%; stage 2, DM 23.3% versus no DM 33.3%, and stage 3, DM 18.6% versus no DM 19.1%). Twenty-nine patients with diabetes had a second AKI event and four had a third event. In patients without DM, one patient had a second AKI. Cumulative AKI incidence was 4.7 times higher in people with DM (DM 60.9% versus no DM 25.0%; 95% CI, 2.72–8.03; P < .01). Patients with diabetes progressed to chronic kidney disease or in chronic kidney disease stage 39.4% of the time. Patients without diabetes progressed 16.7% of the time, but this trend was not significant (P = .07). Complete recovery was 3.8 times more likely in patients without diabetes (95% CI, 1.26–11.16; P = .02).
Conclusions: Acute kidney injury incidence is higher in patients with diabetes, and complete recovery after an AKI is less likely compared to patients without diabetes.
