ArticleEpidemiology and infection2019
Development of predictive nomograms for clinical use to quantify the risk of isolating resistance prone organisms in patients with infected foot ulcers.
Article in Epidemiology and infection, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
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3 citing papers in PubMed, 5 citations in OpenAlex.
- Epidemiology, Risk Factors, and External Validation of Predictive Models for Multidrug-Resistant Bacterial Infections in Diabetic Foot Ulcers.Infection and drug resistance · 2025Article
- A Web-Based Dynamic Nomogram to Predict the Risk of Methicillin-Resistant Staphylococcal Infection in Patients with Pneumonia.Diagnostics (Basel, Switzerland) · 2024Article
- Diabetic Foot Infections: Local Prevalence of and Case-Control Study of Risk Factors for Methicillin-ResistantOpen forum infectious diseases · 2020Article
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Authors and funding
9 authors at 3 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Pseudomonas aeruginosa and methicillin-resistant Staphylococcus aureus (MRSA) have been considered prevalent pathogens in foot infections. However, whether empiric therapy directed against these organisms is necessary, and in whom to consider treatment, is rather unclear. The aim of this study was to develop predictive algorithms for forecasting the probability of isolating these organisms in the infected wounds of patients in a population where the prevalence of resistant pathogens is low. This was a retrospective study of regression model-based risk factor analysis that included 140 patients who presented with infected, culture positive foot ulcers to two urban hospitals. A total of 307 bacteria were identified, most frequently MRSA (11.1%). P. aeruginosa prevalence was 6.5%. In the multivariable analysis, amputation (odds ratio (OR) 5.75, 95% confidence interval (CI) 1.48-27.63), renal disease (OR 5.46, 95% CI 1.43-25.16) and gangrene (OR 2.78, 95% CI 0.82-9.59) were identified as risk factors associated with higher while diabetes (OR 0.07, 95% CI 0.01-0.34) and Infectious Diseases Society of America infection severity >3 (OR 0.18, 95% CI 0.03-0.65) were associated with lower odds of P. aeruginosa isolation (C statistic 0.81). Similar analysis for MRSA showed that amputation was associated with significantly lower (OR 0.29, 95% CI 0.09-0.79) risk, while history of MRSA infection (OR 5.63, 95% CI 1.56-20.63) and osteomyelitis (OR 2.523, 95% CI 1.00-6.79) was associated with higher odds of isolation (C statistic 0.69). We developed two predictive nomograms with reasonable to strong ability to discriminate between patients who were likely of being infected with P. aeruginosa or MRSA and those who were not. These analyses confirm the association of some, but also question the significance of other frequently described risk factors in predicting the isolation of these organisms.
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