This study aimed to investigate the presence of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) in patients presenting with only sudden sensorineural hearing loss (SSHNL) during the COVID-19 pandemic. Methods: The study included five male patients who presented with the sole complaint of unilateral SSNHL to the otolaryngology outpatient clinic between 03-12 April 2020. The patients were referred to the infectious diseases clinic to be evaluated for SARS-CoV-2 by real time polymerase chain reaction (RT-PCR) testing. Results: RT-PCR testing for SARS-CoV-2 was positive in one of the patients and negative in the other four patients. A positive response to COVID-19-specific treatment in the SARS-CoV-2 positive SSNHL patient was noted. Conclusion: It should be remembered that non-specific symptoms such as SSNHL could be the only sign with which to recognize a COVID-19 case. Awareness of such a non-specific presentation of COVID-19 patients is crucial during this pandemic period for preventing infectious spread through isolation and early initiation of COVID-19 targeted treatment.

The novel coronavirus disease (COVID-19) first surfaced in the Chinese city of Wuhan on 1 December 2019 and quickly turned into a global issue. On 11 March 2020, the World Health Organization (WHO) declared this outbreak a pandemic. 1 COVID-19 can affect different organ systems, probably including the oral mucosa. Although cutaneous involvement has been defined for COVID-19, there are no studies that report oropharyngeal involvement. To the best of our knowledge, this is the first case report of oropharyngeal involvement in COVID-19 describing oral lesions in detail. A 51-year-old male patient was admitted to the hospital with a sore throat. The patient was a family practitioner in contact with COVID-19 infected patient. Our subject's symptoms had started on

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By definition, the terms sepsis and septic shock refer to a potentially fatal infectious state in which the early administration of an effective antibiotic is the most significant determinant of the outcome. Because of the global spread of resistant bacteria, the efficacy of antibiotics has been severely compromised. , (), ,, and are the predominant pathogens of sepsis and septic shock. It is common for, , and to be resistant to multiple drugs. Multiple drug resistance is caused by the interplay of multiple resistance mechanisms those emerge via the acquisition of extraneous resistance determinants or spontaneous mutations. Extended-spectrum beta-lactamases (ESBLs), carbapenemases, aminoglycoside-modifying enzymes (AMEs) and quinolone resistance determinants are typically external and disseminate on mobile genetic elements, while porin-efflux mechanisms are activated by spontaneous modifications of inherited structures. Porin and efflux mechanisms are frequent companions of multiple drug resistance in and but only occasionally detected among and . Antibiotic resistance became a global health threat. This review examines the major resistance mechanisms of the leading microorganisms of sepsis.

Background:Candida auris has emerged globally as a multi-drug resistant yeast and is commonly associated with nosocomial outbreaks in ICUs. Methods: We conducted a retrospective observational multicentre study to determine the epidemiology of C. auris infections, its management strategies, patient outcomes, and infection prevention and control practices across 10 centres from five countries. Results: Significant risk factors for C. auris infection include the age group of 61–70 years (39%), recent history of ICU admission (63%), diabetes (63%), renal failure (52%), presence of CVC (91%) and previous history of antibiotic treatment (96%). C. auris was commonly isolated from blood (76%). Echinocandins were the most sensitive drugs. Most common antifungals used for treatment were caspofungin (40%), anidulafungin (28%) and micafungin (15%). The median duration of treatment was 20 days. Source removal was conductedin 74% patients. All-cause crude mortality rate after 30 days was 37%. Antifungal therapy was associated with a reduction in mortality (OR:0.27) and so was source removal (OR:0.74). Contact isolation precautions were followed in 87% patients. Conclusions:C. auris infection carries a high risk for associated mortality. The organism is mainly resistant to most azoles and even amphotericin-B. Targeted antifungal therapy, mainly an echinocandin, and source control are the prominent therapeutic approaches.

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This manuscript aims to present a treatment algorithm we applied to manage COVID-19 patients admitted to our hospital. During the study period, 2043 patients with suspected COVID-19 were admitted to the emergency department. Molecular tests indicated that 475 of these patients tested positive for COVID-19. We administered hydroxychloroquine plus doxycycline to mild cases (isolated at home) for 3 days and lopinavir plus doxycycline to moderate and severe cases (hospitalized) for 5 days. The overall case fatality rate was 4.2% (20/475).

This study aims to provide both a model by using cumulative cases and cumulative death toll for SARS-CoV-2 (severe acute respiratory syndrome coronavirus 2) outbreak in four countries, China, Italy, South Korea, and Turkey, starting from the first diagnosis and to compare associated indicators. The most successful estimation was obtained from the cubic model with natural logarithm for China, Italy, South Korea, and Turkey. The success of the models was around 99%. However, differences began to emerge in China, Italy, and South Korea after the second week. Although the highest number of new cases per 1 million people in China was 9.8 on February 28, 2020; it was 108.4 on March 21, 2020, in Italy; and this was 16.6 on March 5, 2020, in South Korea. On the other hand, the number of new cases was 24.6 per 1 million people on March 27, 2020, in Turkey. The log-cubic model proposed in this study has been set forth to obtain successful results for aforementioned countries, as well as to estimate the course of the COVID-19 outbreak. Other factors such as climacteric factors and genetic differences, which may have an impact on viral spreading and transmission, would also have strengthened the model prediction capacity.