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Using time-kill methodology, we investigated the interactions of fosfomycin with meropenem or colistin or gentamicin against 17 genetically distinct Klebsiella pneumoniae clinical isolates carrying bla KPC-2 . Synergy was observed with meropenem or colistin against 64.7 and 11.8% of tested isolates, while the combination with gentamicin resulted in indifference. All studied combinations showed improved bactericidal activity, compared to fosfomycin alone and prevented the development of fosfomycin resistance in 69.2, 53.8, and 81.8% of susceptible isolates, respectively.

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PURPOSE Financial burden caused by cancer treatment is associated with material loss, distress, and poorer outcomes. Financial resources exist to support patients but identification of need is difficult. We sought to develop and test a tool to accurately predict an individual's risk of financial toxicity based on clinical, demographic, and patient-reported data prior to initiation of breast cancer treatment. PATIENTS AND METHODS We surveyed 611 patients undergoing breast cancer therapy at MD Anderson Cancer Center. We collected data using the validated COmprehensive Score for financial Toxicity (COST) patient-reported outcome measure alongside other financial indicators (credit score, income, and insurance status). We also collected clinical and perioperative data. We trained and tested an ensemble of machine learning (ML) algorithms (neural network, regularized linear model, support vector machines, and a classification tree) to predict financial toxicity. Data were randomly partitioned into training and test samples (2:1 ratio). Predictive performance was assessed using area-under-the-receiver-operating-characteristics-curve (AUROC), accuracy, sensitivity, and specificity. RESULTS In our test sample (N = 203), 48 of 203 women (23.6%) reported significant financial burden. The algorithm ensemble performed well to predict financial burden with an AUROC of 0.85, accuracy of 0.82, sensitivity of 0.85, and specificity of 0.81. Key clinical predictors of financial burden from the linear model were neoadjuvant therapy (βregularized, .11) and autologous, rather than implant-based, reconstruction (βregularized, .06). Notably, radiation and clinical tumor stage had no effect on financial burden. CONCLUSION ML models accurately predicted financial toxicity related to breast cancer treatment. These predictions may inform decision making and care planning to avoid financial distress during cancer treatment or enable targeted financial support. Further research is warranted to validate this tool and assess applicability for other types of cancer.

Summary:Intravascular papillary endothelial hyperplasia (IPEH) or Masson’s tumor is a rare benign entity commonly found on the head, neck, and upper extremities. It usually arises within a blood vessel but is considered to be a nonneoplastic reactive process often associated with vascular injury. Typically, IPEHs cause no symptoms and present as slowly growing soft-tissue masses. Given their prevalent location and indolent clinical presentation, the plastic surgeon should be familiar with this rare entity. We are presenting a case of IPEH of the forehead with unusual clinical and pathologic characteristics. Differential diagnosis, special considerations regarding preoperative work-up, and treatment options are discussed.

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BackgroundPrevious reports individually identified different factors that predict death after burns. The authors employed the multi-center American Burn Association’s (ABA) National Burn Repository (NBR) to elucidate which parameters have the highest negative impact on burn mortality.MethodsWe audited data from the NBR v8.0 for the years 2002–2011 and included 137,061 patients in our study. The cases were stratified into two cohorts based on the primary outcome of death/survival and then evaluated for demographic data, intraoperative details, and their morbidity after admission. A multivariable regression analysis aimed to identify independent risk factors associated with mortality.ResultsA total of 3.3% of patients in this analysis did not survive their burn injuries. Of those, 52.0% expired within 7 days after admission. Patients in the mortality cohort were of older age (p < 0.001), more frequently female (p < 0.001), and had more pre-existing comorbidities (p < 0.001). Total body surface area (TBSA), inhalation injury, hospitalization time, and occurrence of complications were higher compared to survivors (p < 0.001). Lack of insurance (odds ratio (OR) = 1.84, confidence interval (CI) 1.38–2.46), diabetes (OR = 1.24, CI 1.01–1.53), any complication (OR = 4.09, CI 3.27–5.12), inhalation injury (OR = 3.84, CI 3.38–4.36), and the need for operative procedures (OR = 2.60, CI 2.20–3.08) were the strongest independent contributors to mortality after burns (p < 0.001). Age (OR = 1.07, CI 1.06–1.07) and TBSA (OR = 1.09, CI 1.09–1.09) were significant on a continuous scale (p < 0.001) while overall comorbidities were not a statistical risk factor.ConclusionUninsured status, inhalation injury, in-hospital complications, and operative procedures were the strongest mortality predictors after burns. Since most fatal outcomes (52.0%) occur within 7 days after injury, physicians and medical staff need to be aware of these risk factors upon patient admission to a burn center.

All figures are projected. * Data unavailable in prior year. **87% of total 2017 breast implants were silicone; 13% were saline. ***Botulinum Toxin Type A numbers are of anatomic sites injected. ****Counts of procedures performed by ASPS member surgeons only. In 2000 figure included all animal bites.^I n 2000 figure included facial laceration repair.^^^I