Surgical site infections persist as a substantial concern within the realm of hospital-acquired infections. This enduring issue is further compounded by the mounting challenge of antibiotic resistance, a surge in surgical interventions, and the presence of comorbidities among patients. Thus, a comprehensive exploration of all discernible risk factors, as well as proactive preventive and prophylactic strategies, becomes imperative. Moreover, the prevalence of multidrug-resistant microorganisms has reached alarming proportions. Consequently, there is an acute need to investigate and scrutinize all potential therapeutic interventions to counter this burgeoning threat. Consequently, the primary objective of this review is to meticulously assess the origins and risk elements intertwined with surgical site infections across a diverse spectrum of surgical procedures. As the medical landscape continues to evolve, this critical analysis seeks to provide a nuanced understanding of the multi-faceted factors contributing to surgical site infections, with the overarching aim of facilitating more effective management and mitigation strategies. By exploring these dimensions comprehensively, we endeavor to enhance patient safety and the quality of surgical care in this era of evolving healthcare challenges.

Background: CTX-M betalactamases have shown a rapid spread in the recent years among Enterobacteriaceae and have become the most prevalent Extended Spectrum Beta-Lactamases (ESBLs) in many parts of the world. The introduction and dissemination of antibiotic-resistant genes limits options for treatment, increases mortality and morbidity in patients, and leads to longer hospitalization and expensive costs. We aimed to identify the beta-lactamases circulating encoded by the genes bla_CTX-M-15, bla_SHV-1 and bla_TEM-1 in Escherichia coli (E. coli) and Klebsiella pneumoniae (K. pneumoniae) strains. Furthermore, we established the associated resistance phenotypes among patients hospitalized in the Intensive Care Unit (ICU) from County Clinical Emergency Hospital of Craiova, Romania. Methods: A total of 46 non-duplicated bacterial strains (14 strains of E. coli and 32 strains of K. pneumoniae), which were resistant to ceftazidime (CAZ) and cefotaxime (CTX) by Kirby–Bauer disk diffusion method, were identified using the automated VITEK2 system. Detection of ESBL-encoding genes and other resistance genes was carried out by PCR. Results. E. coli strains were resistant to 3rd generation cephalosporins and moderately resistant to quinolones, whereas K. pneumoniae strains were resistant to penicillins, cephalosporins, and sulfamides, and moderately resistant to quinolones and carbapenems. Most E. coli strains harbored bla_CTX-M-15 gene (13/14 strains), a single strain had the bla_SHV-1 gene, but 11 strains harbored bla_TEM-1 gene. The mcr-1 gene was not detected. We detected tet(A) gene in six strains and tet(B) in one strain. In K. pneumoniae strains we detected bla_CTX-M-15 in 23 strains, bla_SHV-₁ in all strains and bla_TEM-1 in 14 strains. The colistin resistance gene mcr-1 was not detected. The tetracycline gene tet(A) was detected in 11 strains, but the gene tet(B) was not detected in any strains. Conclusions. The development in antibiotic resistance highlights the importance of establishing policies to reduce antibiotic use and improving the national resistance surveillance system in order to create local antibiotic therapy guidelines.

Acute pancreatitis (AP) is a severe disease with a high prevalence and 3 to 15% mortality worldwide, which can represent an important challenge for the physician. Oxidative stress and antioxidants are involved in AP progression. The mechanisms responsible for the onset and progression of AP are still poorly understood. Previous studies have highlighted the important contribution of antioxidants and oxidative stress in AP. The existence of a relationship between oxidative stress and antioxidants in AP is unquestionable, although a more accurate understanding of the mechanistic pathways involved is required to create a solid basis for potential prevention or treatment strategies. Further investigation is needed to clarify the role of antioxidant status and the severity of AP and to determine the association between oxidative stress and pancreatic enzyme activities. Antioxidant therapy may represent an interesting option for the management of patients with AP, although additional information about the effectiveness of this potential treatment is required.

Background and Objectives: At present, thyroid disorders have a great incidence in the worldwide population, so the development of alternative methods for improving the diagnosis process is necessary. Materials and Methods: For this purpose, we developed an ensemble method that fused two deep learning models, one based on convolutional neural network and the other based on transfer learning. For the first model, called 5-CNN, we developed an efficient end-to-end trained model with five convolutional layers, while for the second model, the pre-trained VGG-19 architecture was repurposed, optimized and trained. We trained and validated our models using a dataset of ultrasound images consisting of four types of thyroidal images: autoimmune, nodular, micro-nodular, and normal. Results: Excellent results were obtained by the ensemble CNN-VGG method, which outperformed the 5-CNN and VGG-19 models: 97.35% for the overall test accuracy with an overall specificity of 98.43%, sensitivity of 95.75%, positive and negative predictive value of 95.41%, and 98.05%. The micro average areas under each receiver operating characteristic curves was 0.96. The results were also validated by two physicians: an endocrinologist and a pediatrician. Conclusions: We proposed a new deep learning study for classifying ultrasound thyroidal images to assist physicians in the diagnosis process.

The study evaluated the evolution of the incidence of infections with Klebsiella in the County Clinical Emergency Hospital of Craiova (SCJUC), Romania. Also, we monitored antibiotic resistance over more than two years and detected changes in resistance to various antimicrobial agents. Our study included 2062 patients (823 women and 1239 men) hospitalised in SCJUC during the period 1st of September 2017 to 30 June 2019. In 458 patients (22.21%) from the 2062 total patients, the collected samples (1116) were positive and from those, we isolated 251 strains of Klebsiella spp. We conducted a longitudinal analysis of the prevalence of Klebsiella spp. over calendar months, which showed a prevalence in surgical wards that ranged between 5.25% and 19.49% in June 2018, while in medical wards the variation was much wider, between 5.15% and 17.36% in April 2018. Klebsiella spp. strains showed significant resistance to Amoxicillin/Clavulanate, Aztreonam and Cephalosporins such as Ceftriaxone, Ceftazidime and Cefepime. We examined the possible link with the consumption of antibiotics in the same month by performing a multiple linear regression analysis. The evolution of antibiotic resistance in Klebsiella was correlated with the variation of resistance in other bacteria, which suggests common resistance mechanisms in the hospital environment. By performing the regression for dependency between antibiotic resistance and antibiotic consumption, we observed some correlations between antibiotic consumption and the development of antibiotic resistance after 1, 2 and even 3 months (e.g., resistance to meropenem was influenced by the consumption in the hospital ward of imipenem 1 month and two months before, but only 1 month before by the consumption of meropenem). The clustering of strains showed filiation between multiresistant Klebsiella spp. strains isolated from specific patients from the ICU. The evolution of prevalence and antibiotic resistance in Klebsiella correlated with the resistance in other bacteria, which suggest common resistance mechanisms in the hospital environment, and also with the consumption of antibiotics.

Currently, non-alcoholic fatty liver disease is the most common liver disease worldwide, with a prevalence of 32%. It is much more common among men (40%) and among patients with metabolic comorbidities such as obesity, diabetes and dyslipidemia. Being an asymptomatic disease, the diagnosis is often established on the basis of imaging methods, with an important role given to abdominal ultrasonography, computed tomography and magnetic resonance imaging. In order to facilitate diagnosis, experts have introduced a series of blood biomarkers. Two biomarker panels are currently validated for the diagnosis of non-alcoholic fatty liver disease: the fatty liver index, and the hepatic steatosis index. The fatty liver index has been in use in medical practice for over 17 years and has demonstrated its accuracy in various studies that compared it with other diagnostic methods, highlighted its role in screening patients with cardiovascular risk and validated the effects of different diets and drugs that are proposed for the treatment of the disease. In the management of non-alcoholic fatty liver disease, the fatty liver index is an important algorithm in the diagnosis and prognosis of patients with metabolic risk. Taking into account the diversity of drugs to be approved in the treatment of non-alcoholic fatty liver disease, the fatty liver index will become an effective tool in monitoring the effects of these therapies.