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Antibiotic resistance (ABR) and antimicrobial stewardship arethe two sides of the same coin that constitute a public health hydra. This study aimed to assessthe knowledge and attitude of healthcare workers (HCWs), on antibiotic use and antimicrobial resistance in Western Greece. A total of 200 healthcare workers (doctors, nurses, and others) from the two largest tertiary hospitals in Western Greece were included in our survey. HCWs seem not to decide based on patient opinion in order to prescribe antibiotics. Approximately 97% of them are aware of their main adverse effects. Remarkably, 25% of respondents prescribe antibiotics due to diagnostic uncertainty, and 32.5% of them prescribe antibiotics based on their experience. HCWs statedthat they do not report adverse effects often. Inappropriate antibiotic prescriptions were mentioned as the main reason for bacterial resistance to antimicrobials. Monitoring the patient's treatment progress, using electronic prescriptions, and adhering to international guidelines were suggested as solutions to the problem. Post Hoc analysis showed that nursing staff apply to the national guidelines (p: 0.011) and use electronic prescriptions (p: 0.003) less often compared to consultants, doctor directors, and trainees. The findings of our survey may be useful for the development of future national education programs and interventions thatmay improve healthcare workers' knowledge and ability to manage antibiotics.

Background: The Pancreatic Stone Protein (PSP) is an acute-phase protein that is mainly secreted by pancreatic cells in response to stress. The current literature supports its use as a predictor of sepsis. Its prognostic role has recently been evaluated in a point-of-care setting, mostly in high-risk patients. We conducted a prospective observational cohort study to evaluate its utility in the prognosis of patients admitted to the hospital with a diagnosis of intra-abdominal infection., Methods: Adult patients consecutively admitted to the Internal Medicine Department of the University Hospital of Patras, Greece, with a diagnosis of intra-abdominal infection were enrolled. PSP levels were measured within 24 h of admission in whole blood., Results: a total of 40 patients were included after being diagnosed with IAI. PSP was used as an independent predictive factor for sepsis after adjusting for age with OR = 7.888 (95% CI: 1.247-49.890). PSP also predicted readmission and the need for treatment escalation ( p : <0.01) and was an excellent prognostic factor regarding these outcomes (AUC = 0.899, 95% CI: 0.794-1.0, and AUC = 0.862, 95% CI: 0.748-0.976, respectively). PSP also proved superior to CRP, ferritin, and fibrinogen in sepsis diagnosis, treatment escalation, and readmission prediction with an AUC of 0.862, 0.698, and 0.899, respectively., Conclusions: PSP can predict unfavorable outcomes, such as sepsis development, readmission, and the need for treatment escalation among patients with intra-abdominal infections.

Atrial fibrillation (AF) is the most common arrhythmia with a high burden of morbidity including impaired quality of life and increased risk of thromboembolism. Early detection and management of AF could prevent thromboembolic events. Artificial intelligence (AI)--based methods in healthcare are developing quickly and can be proved as valuable for the detection of atrial fibrillation. In this metanalysis, we aim to review the diagnostic accuracy of AI-based methods for the diagnosis of atrial fibrillation. A predetermined search strategy was applied on four databases, the PubMed on 31 August 2022, the Google Scholar and Cochrane Library on 3 September 2022, and the Embase on 15 October 2022. The identified studies were screened by two independent investigators. Studies assessing the diagnostic accuracy of AI-based devices for the detection of AF in adults against a gold standard were selected. Qualitative and quantitative synthesis to calculate the pooled sensitivity and specificity was performed, and the QUADAS-2 tool was used for the risk of bias and applicability assessment. We screened 14,770 studies, from which 31 were eligible and included. All were diagnostic accuracy studies with case-control or cohort design. The main technologies used were: (a) photoplethysmography (PPG) with pooled sensitivity 95.1% and specificity 96.2%, and (b) single-lead ECG with pooled sensitivity 92.3% and specificity 96.2%. In the PPG group, 0% to 43.2% of the tracings could not be classified using the AI algorithm as AF or not, and in the single-lead ECG group, this figure fluctuated between 0% and 38%. Our analysis showed that AI-based methods for the diagnosis of atrial fibrillation have high sensitivity and specificity for the detection of AF. Further studies should examine whether utilization of these methods could improve clinical outcomes.

Background: Along with important factors that worsen the clinical outcome of COVID-19, it has been described that bacterial infections among patients positive for a SARS-CoV-2 infection can play a dramatic role in the disease process. Co-infections or community-acquired infections are recognized within the first 48 h after the admission of patients. Superinfections occur at least 48 h after admission and are considered to contribute to a worse prognosis. Microbiologic parameters differentiate infections that happen after the fifth day of hospitalization from those appearing earlier. Specifically, after the fifth day, the detection of resistant bacteria increases and difficult microorganisms emerge., Objectives: The aim of the study was to evaluate the impact of bacterial infections in patients with COVID-19 on the length of the hospital stay and mortality., Methods: A total of 177 patients hospitalized due to COVID-19 pneumonia were consecutively sampled during the third and fourth wave of the pandemic at a University Hospital in Greece. A confirmed bacterial infection was defined as positive blood, urinary, bronchoalveolar lavage (BAL) or any other infected body fluid. Patients with confirmed infections were further divided into subgroups according to the time from admission to the positive culture result., Results: When comparing the groups of patients, those with a confirmed infection had increased odds of death (odds ratio: 3.634; CI 95%: 1.795-7.358; p < 0.001) and a longer length of hospital stay (median 13 vs. 7 days). A late onset of infection was the most common finding in our cohort and was an independent risk factor for in-hospital death. Mortality and the length of hospital stay significantly differed between the subgroups., Conclusion: In this case series, microbial infections were an independent risk factor for a worse outcome among patients with COVID-19. Further, a correlation between the onset of infection and a negative outcome in terms of non-infected, community-acquired, early hospital-acquired and late hospital-acquired infections was identified. Late hospital-acquired infections increased the mortality of COVID-19 patients whilst superinfections were responsible for an extended length of hospital stay.

Diabetes mellitus (DM) and heart failure (HF) are two chronic disorders that affect millions worldwide. Hyperglycemia can induce excessive generation of highly reactive free radicals that promote oxidative stress and further exacerbate diabetes progression and its complications. Vascular dysfunction and damage to cellular proteins, membrane lipids and nucleic acids can stem from overproduction and/or insufficient removal of free radicals. The aim of this article is to review the literature regarding the use of antidiabetic drugs and their role in glycemic control in patients with heart failure and oxidative stress. Metformin exerts a minor benefit to these patients. Thiazolidinediones are not recommended in diabetic patients, as they increase the risk of HF. There is a lack of robust evidence on the use of meglinitides and acarbose. Insulin and dipeptidyl peptidase-4 (DPP-4) inhibitors may have a neutral cardiovascular effect on diabetic patients. The majority of current research focuses on sodium glucose cotransporter 2 (SGLT2) inhibitors and glucagon-like peptide 1 (GLP-1) receptor agonists. SGLT2 inhibitors induce positive cardiovascular effects in diabetic patients, leading to a reduction in cardiovascular mortality and HF hospitalization. GLP-1 receptor agonists may also be used in HF patients, but in the case of chronic kidney disease, SLGT2 inhibitors should be preferred.