Among rehospitalized patients, methicillin resistant Staphylococcus infections was detected as the most common agent, and Klebsiella spp. infections were found to be significantly associated with fatality.

We aimed to investigate the predictors for limb loss among patients with diabetes who have complicated skin/soft-tissue infections. In this observational study, consecutive patients with diabetic foot infection (DFI) from 17 centres in Turkey, between May 2011 and May 2013 were included. The Turkish DFI Working Group performed the study. Predictors of limb loss were investigated by multivariate analysis. In total, 455 patients with DFI were included. Median age was 61 years, 68% were male, 65% of the patients were hospitalized, 52% of the patients had used antibiotics within the last month, and 121 (27%) had osteomyelitis. Of the 208 microorganisms isolated, 92 (44.2%) were Gram-positive cocci and 114 (54.8%) were Gram-negative rods (GNR). The most common GNR was Pseudomonas; the second was Escherichia coli, with extended spectrum β-lactamase positivity of 33%. Methicillin-resistant Staphylococcus species were found in 14% (29/208). Amputations were performed in 126/455 (28%) patients, 44/126 (34%) of these were major amputations. In multivariate analysis, significant predictors for limb loss were, male gender (OR 1.75, 95% CI 1.04-2.96, p 0.034), duration of diabetes >20 years (OR 1.9, 95% CI 1.18-3.11, p 0.008), infected ulcer versus cellulitis (OR 1.9, 95% CI 1.11-3.18, p 0.019), history of peripheral vascular disease (OR 2, 95% CI 1.26-3.27, p 0.004), retinopathy (OR 2.25, 95% CI 1.19-4.25, p 0.012), erythrocyte sedimentation rate >70 mm/hr (OR 1.6, 95% CI 1.01-2.68, p 0.05), and infection with GNR (OR 1.8, 95% CI 1.08-3.02, p 0.02). Multivariate analysis revealed that, besides the known risk factors such as male gender, duration of diabetes >20 years, infected ulcers, history of peripheral vascular disease and retinopathy, detection of GNR was a significant predictor of limb loss.

BackgroundThe primary objective of this study was to report the incidence of bloodstream infections (BSIs) and clinically or microbiologically proven bacterial or fungal BSIs during neutropenic episodes in patients with hematological malignancies.MethodsIn this retrospective observational study, all patients in the hematology department older than 14 years who developed febrile neutropenia during chemotherapy for hematological cancers were evaluated. Patients were included if they had experienced at least one neutropenic episode between November 2010 and November 2012 due to chemotherapy in the hematology ward.ResultsDuring 282 febrile episodes in 126 patients, 66 (23%) episodes of bacteremia and 24 (8%) episodes of fungemia were recorded in 48 (38%) and 18 (14%) patients, respectively. Gram-negative bacteria caused 74% (n=49) of all bacteremic episodes. Carbapenem-resistant Gram-negative bacteria (n=6) caused 12% and 9% of Gram-negative bacteremia episodes and all bacteremia episodes, respectively. Carbapenem-resistant Gram-negative bacteria included Acinetobacter baumannii (n=4), Pseudomonas aeruginosa (n=1), and Serratia marcescens (n=1). Culture-proven invasive fungal infection occurred in 24 episodes in 18 cases during the study period, with 15 episodes in ten cases occurring in the first study year and nine episodes in eight cases in the second study year. In 13 of 18 cases (72%) with bloodstream yeast infections, previous azole exposure was recorded. Candida parapsilosis, C. glabrata, and C. albicans isolates were resistant to voriconazole and fluconazole.ConclusionBSIs that occur during febrile neutropenic episodes in hematology patients due to Gram-negative bacteria should be treated initially with non-carbapenem-based antipseudomonal therapy taking into consideration antimicrobial stewardship. Non-azole antifungal drugs, including caspofungin and liposomal amphotericin B, should be preferred as empirical antifungal therapy in the events of possible or probable invasive fungal infections with an absence of pulmonary findings due to increase azole resistance.

BackgroundThe fatality attributed to pandemic influenza A H1N1 was not clear in the literature. We described the predictors for fatality related to pandemic influenza A H1N1 infection among hospitalized adult patients.MethodsThis is a multicenter study performed during the pandemic influenza A H1N1 [A(H1N1)pdm09] outbreak which occurred in 2009 and 2010. Analysis was performed among laboratory confirmed patients. Multivariate analysis was performed for the predictors of fatality.ResultsIn the second wave of the pandemic, 848 adult patients were hospitalized because of suspected influenza, 45 out of 848 (5.3%) died, with 75% of fatalities occurring within the first 2 weeks of hospitalization. Among the 241 laboratory confirmed A(H1N1)pdm09 patients, the case fatality rate was 9%. In a multivariate logistic regression model that was performed for the fatalities within 14 days after admission, early use of neuraminidase inhibitors was found to be protective (Odds ratio: 0.17, confidence interval: 0.03-0.77, p = 0.022), nosocomial infections (OR: 5.7, CI: 1.84-18, p = 0.013), presence of malignant disease (OR: 3.8, CI: 0.66-22.01, p = 0.133) significantly increased the likelihood of fatality.ConclusionsEarly detection of the infection, allowing opportunity for the early use of neuraminidase inhibitors, was found to be important for prevention of fatality. Nosocomial bacterial infections and underlying malignant diseases increased the rate of fatality.

Objective The aim of this study was to determine the associations of the neutrophil–lymphocyte ratio (NLR) and C-reactive protein (CRP)–albumin ratio (CAR) with the duration of hospital stay and fatality rate in geriatric patients with coronavirus disease 2019 (COVID-19). Methods Patients older than 65 years with polymerase chain reaction-positive COVID-19 were included. Neutrophil, lymphocyte, CRP, albumin, and demographic data and the duration of hospitalization were recorded. Results The mean length of stay was 15 days. NLR and CAR were significantly higher in patients who died than in those who survived. The cutoffs predictive of mortality were 4.02 (area under the curve [AUC] = 0.717) for NLR and 23 for CAR (AUC = 0.781). The fatality rate among patients who required inpatient treatment was 33%. Conclusion NLR and CAR, which can be calculated inexpensively and quickly at the first admission to the hospital, are extremely useful for estimating the duration of hospitalization and risk of mortality in geriatric patients with COVID-19. Using these data, treatment can quickly be intensified when needed.