Facing Pandemic: Burnout in Nurses in Turkey.

OBJECTIVE: Burnout syndrome is a disorder that characterized by emotional exhaustion, depersonalization, and personal lack of accomplishment perception and it is common in nurses. During the coronavirus disease 2019 pandemic, nurses tried to take care of their patients and protect themselves and their families from disease and death. This study examines the factors affecting nurses' burnout in Turkey during the coronavirus disease 2019 pandemic. MATERIAL AND METHODS: Data were collected from 3523 nurses in 69 cities across Turkey by sociodemographic questions and Maslach Burnout Scale with the electronic questionnaire created in the "SurveyMonkey" application between June 9, 2020 and June 21, 2020. To assess the impact of the pandemic on nurses' burnout, nurses were categorized as those working in pandemic units and others. RESULTS: The response rate was 68%, and 3523 nurses from 69 cities across Turkey participated in the survey. Analyses were conducted with 2386 nurses that answered all questions. 76.45% of the nurses were from tertiary hospitals, and 54.9% (n = 1309) worked in pandemic units. Of 2386 participants, 86.13% (n = 2055) were female, the mean age was 33.9 (±8.43), and 58.76% (n = 1402) were married. Of 2386 participants, 54.9% (n = 1309) worked in pandemic units (outpatient clinics, inpatient clinics, and intensive care units). In multivariate linear regression analyses, the emotional exhaustion score was higher in nurses working in pandemic units (P < .05). CONCLUSION: The factors that have been shown to cause burnout in previous studies were similar. However, in this study, it was also seen that the pandemic is a fundamental cause of burnout.

A 5-year surveillance of healthcare-associated infections in a university hospital: A retrospective analysis.

Objectives: "Nosocomial infections" or "healthcare-associated infections" are a significant public health problem around the world. This study aimed to assess the rate of laboratory-confirmed healthcare-associated infections, frequency of nosocomial pathogens, and the antimicrobial resistance patterns of bacterial isolates in a University Hospital. Methods: A retrospective evaluation of healthcare-associated infections in a University Hospital, between the years 2015 and 2019 in Tekirdag, Turkey. Results: During the 5 years, the incidence densities of healthcare-associated infections in intensive care units and clinics were 10.31 and 1.70/1000 patient-days, respectively. The rates of ventilator-associated pneumonia, central line-associated bloodstream infections, and catheter-associated urinary tract infections in intensive care units were 11.57, 4.02, and 1.99 per 1000 device-days, respectively. The most common healthcare-associated infections according to the primary sites were bloodstream infections (55.3%) and pneumonia (20.4%). 67.5% of the isolated microorganisms as nosocomial agents were Gram-negative bacteria, 24.9% of Gram-positive bacteria, and 7.6% of Candida. The most frequently isolated causative agents were Escherichia coli (16.7%) and Pseudomonas aeruginosa (15.7%). The rate of extended-spectrum beta-lactamase production among E. coli isolates was 51.1%. Carbapenem resistance was 29.8% among isolates of P. aeruginosa, 95.1% among isolates of Acinetobacter baumannii, and 18.2% among isolates of Klebsiella pneumoniae. Colistin resistance was 2.4% among isolates of A. baumannii. Vancomycin resistance was 5.3% among isolates of Enterococci. Conclusion: Our study results demonstrate that healthcare-associated infections are predominantly originated by intensive care units. The microorganisms isolated from intensive care units are highly resistant to many antimicrobial agents. The rising incidence of multidrug-resistant microorganisms indicates that more interventions are urgently needed to reduce healthcare-associated infections in our intensive care units.

Demonstration and evaluation of a digital twin-based virtual factory.

Smart manufacturing, tailored by the 4th industrial revolution and forces like innovation, competition, and changing demands, lies behind the concurrent evolution (also known as co-evolution) of products, processes and production systems. Manufacturing companies need to adapt to ever-changing environments by simultaneously reforming and regenerating their product, process, and system models as well as goals and strategies to stay competitive. However, the ever-increasing complexity and ever-shortening lifecycles of product, process and system domains challenge manufacturing organization's conventional approaches to analysing and formalizing models and processes as well as management, maintenance and simulation of product and system life cycles. The digital twin-based virtual factory (VF) concept, as an integrated simulation model of a factory including its subsystems, is promising for supporting manufacturing organizations in adapting to dynamic and complex environments. In this paper, we present the demonstration and evaluation of previously introduced digital twin-based VF concept to support modelling, simulation and evaluation of complex manufacturing systems while employing multi-user collaborative virtual reality (VR) learning/training scenarios. The concept is demonstrated and evaluated using two different wind turbine manufacturing cases, including a wind blade manufacturing plant and a nacelle assembly line. Thirteen industry experts who have diverse backgrounds and expertise were interviewed after their participation in a demonstration. We present the experts' discussions and arguments to evaluate the DT-based VF concept based on four dimensions, namely, dynamic, open, cognitive, and holistic systems. The semi-structured conversational interview results show that the DT-based VF stands out by having the potential to support concurrent engineering by virtual collaboration. Moreover, DT-based VF is promising for decreasing physical builds and saving time by virtual prototyping (VP).

[Evaluation of the BD Phoenix100 System and Colistin Broth Disk Elution Method for Antimicrobial Susceptibility Testing of Colistin Against Gram-negative Bacteria]. / Kolistinin Gram-negatif Bakterilere In Vitro Etkinliginin Belirlenmesinde BD Phoenix100 Sistemi ve Kolistin Sivi Disk Elüsyon Yöntemlerinin Degerlendirilmesi.

Infections with multidrug resistant gram-negative bacteria is a growing problem especially in health care settings. Colistin is one of the last resort antibiotics for such infections in which treatment options are limited. Increasing resistance to colistin is a global problem. Clinical and Laboratory Standards Institute (CLSI) and the European Committee on Antimicrobial Susceptibility Testing (EUCAST) study groups have recommended the ISO-standard broth microdilution method (20776-1) as the reference method for the determination of colistin susceptibility. Since the broth microdilution method is not a practical method, it is rarely used in routine clinical microbiology laboratories, yet simple and accurate phenotypic detection methods for the determination of colistin resistance in routine microbiology laboratories are not precisely defined. The aim of this study was to evaluate BD Phoenix100 (Becton Dickinson, USA) system and colistin broth disk elution method for the detection of in vitro activity of colistin against gram-negative bacteria. A total of 419 gram-negative bacteria, including 199 Klebsiella pneumoniae, 163 Acinetobacter baumannii, 34 Escherichia coli, 20 Enterobacter spp., and three Citrobacter spp. isolates which were isolated from various clinical samples in our hospital between 2016-2018 were tested. The broth microdilution method was used as the reference method applying ISO-standard broth microdilution methods (20776-1) and CLSI/EUCAST recommendations. For colistin broth disk elution method, final concentrations of 0 (growth control), 1, 2 and 4 µg/ml were obtained by adding 10 µg colistin disks to four tubes containing 10 ml cation-adjusted Mueller Hinton broth per isolate. After incubation at room temperature for 30 minutes, 50 µl of standardized inoculum suspensions were added to the tubes. Colistin minimum inhibitor concentration (MIC) values were read visually after 16-20 hours of incubation at 35°C in ambient air. Manufacturer's recommendations were followed for BD Phoenix100 system. The categorical agreement between the reference broth microdilution method and the colistin broth disk elution method was 99.3%, very major error and major error rates were 0.2% and 0.5%, respectively. For BD Phoenix100 system, the categorical agreement was 95%, with a very major error rate of 5%. Our results showed that colistin broth disc elution method worked well compared to the reference broth microdilution method. The BD Phoenix100 system, with a high very major error rate, does not reliably distinguish colistin-resistant and colistin-susceptible strains.