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Predictors of Digital Amputation in Diabetic Patients With Surgically Treated Finger Infections. | LitMetric

AI Article Synopsis

Article Abstract

Background: Diabetes is a well-established risk factor for severe digital infection, and patients are more likely to require digital amputation for adequate source control. This study aims to identify factors predictive of digital amputation compared with preservation in patients with diabetes who present with surgically treated finger infections.

Methods: Current Procedural Terminology (CPT) and International Classification of Diseases Versions 9 and 10 (ICD-9/10) databases from a single academic medical center were queried to identify patients with type 1 or type 2 diabetes mellitus who underwent surgical treatment in the operating room for treatment of a digital infection from 2010 to 2020. Electronic medical records were reviewed to obtain historical and acute clinical variables at the time of hospital presentation. Bivariate and multivariable regression were used to identify factors associated with amputation.

Results: In total, 145 patients (61 digital amputation, 84 digital preservation) met inclusion criteria for this retrospective cohort study. Mean hospital stay was 6 days, and the average patient underwent 2 operations. Multivariable analysis revealed that the presence of osteomyelitis, ipsilateral upper extremity dialysis fistula, end-stage renal disease, and vascular disease each had significant independent predictive value for amputation rather than digital preservation.

Conclusions: Digital amputation is common in the setting of diabetic finger infection. The 4 variables found to independently predict the outcome of amputation can be understood as factors which decrease the likelihood of successful digital salvage and increase the potential consequence of ongoing uncontrolled infection. Further study should focus on clinical factors affecting surgical decision making and how the treatment rendered affects patient outcomes.

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Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC10953522PMC
http://dx.doi.org/10.1177/15589447221082160DOI Listing

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