The risk of tuberculosis is higher in cases who have used antiTNF treatments. However, it is not clearly known whether there is a relationship between other biologic agents and the risk of developing tuberculosis or not. We aimed to investigate the prevalence of active tuberculosis among patients with rheumatic disease treated with biologic drugs. The study was performed at a tertiary referral center from January 2015 to December 2019. A total of 2000 patients with rheumatic diseases were screened and 461 patients were enrolled in the study due to regular records. They were underwent LTBI screening tests and were followedup at least 1 year after TNF inhibitor treatment initiation. The median age of all patients was 48 (min-max 19-80). 283 patients (61.3%) were female and 178 (38.7%) were male. AZD1080 price The most common diseases were ankylosing spondylitis (67.2%), rheumatoid arthritis (26%) and psoriatic arthritis (5.2%). Anti-TNF treatments were given to 85.2% of all cases and other biologic treatments were given to 14.8%. Tuberculin skin test was applied to 429 patients and 70.4% positivity was found. Quantiferon-TB test was applied to 93 patients and 20.4% positivity was found. 320 patients were treated for LTBI due to positive tuberculin skin test and/or positive quantiferon-TB test. TB was developed in only one patient out of 393 patients who were treated with anti-TNF treatments and the the prevalence of TB development was found 255/100.000. The incidence of tuberculosis was quite low in our patients with rheumatic disease who were receiving anti-TNF treatment compared to previous studies. Also, in patients who were using other biological treatments, no TB cases were developed.The incidence of tuberculosis was quite low in our patients with rheumatic disease who were receiving anti-TNF treatment compared to previous studies. Also, in patients who were using other biological treatments, no TB cases were developed. SARS-CoV-2 (COVID-19), which emerged in Wuhan, China in December 2019, infected more than six million people in a short time. In COVID-19, the relationship of many laboratory parameters to morbidity and mortality has been defined. In our study, we aimed to determine the relationship of serum vitamin D level to clinical course and prognosis. This study included 108 patients; 88 patients who stayed in Ataturk University and Erzurum City Hospital between March 24, 2020 and May 15, 2020, who were identified as COVID-19 by real-time PCR method from the nasopharyngeal swab and 20 asymptomatic voluntary medical personnel who tested negative for real-time PCR after routine check-up in our hospital. In statistical analysis conducted between healthy control group and vitamin D levels of patients admitted due to COVID-19, it was observed that patients infected with COVID-19 had a lower level (p= 0.004). In 20 patients developing MAS, a lower level of vitamin D was observed (p= 0.004) compared to 68 patients who did not develop. In the comparison of vitamin D levels of the patients (n= 8) who developed exitus in their follow up due to COVID-19, it was observed that vitamin D levels were statistically significantly lower compared to the living (p= 0.009). Due to COVID-19, pandemic, long-running quarantines caused insufficient use of sunlight and worsening of vitamin D deficiency. We wanted to draw attention again with our study to vitamin D which can be responsible for the heavy clinical course of COVID-19 and whose replacement is easy to apply.Due to COVID-19, pandemic, long-running quarantines caused insufficient use of sunlight and worsening of vitamin D deficiency. We wanted to draw attention again with our study to vitamin D which can be responsible for the heavy clinical course of COVID-19 and whose replacement is easy to apply. The aim of this study is to investigate and report on the data regarding the clinical characteristics and outcomes of healthcare workers with COVID-19 at tertiary education hospitals from Turkey. This was a single center, retrospective, descriptive and observational study using cross-sectional data, which were collected from confirmed COVID-19 patients at a tertiary education hospital. Patients' demographic and clinical characteristics, mortality rates, and the factors associated with hospitalization were analyzed. By May 15, 2020, 480 patients were diagnosed with COVID-19 in our hospital where 49 (10.2%) of whom were HCWs. The mean age was 40.0 ± 8.45 (75.5% female). The most common symptoms were cough (32.7%), fever (30.6%), and myalgia (14.3%). Comorbidities were present in 32.7% of the patients. Most of the HCWs were nurses (53.1%) and physicians (18.4%), and the remaining 14 (28.6%) were cleaning and administrative staff. The severity of the disease was mild in 65.3% and severe in 34.7% HCWs. Leukocyte, neutrophil, lymphocyte and platelet values were statistically lower in hospitalized patients. There was a statistically significant relationship between the presence of infiltration on the chest X-ray, and the patient's symptoms with the severity of the disease (respectively p= 0.002 and 0.009). In conclusion, the frequency of COVID-19 in healthcare workers is high. The study presents the characteristics of HCWs infected with coronavirus from a single center in Turkey.In conclusion, the frequency of COVID-19 in healthcare workers is high. The study presents the characteristics of HCWs infected with coronavirus from a single center in Turkey. Intensive care physicians are increasingly involved in decision making about the prognosis of intensive care unit ICU patients. With this study; we aimed to evaluate the power of clinician foresight at prediction of mortality in patient at triage to intensive care and patient follow-up. This study was conducted in ICUs located in various geographical regions of Turkey between January 1, 2017-April 30, 2017.The clinical research was planned as observational, multicenter, cross-sectional. A total of 1169 intubated patients were followed in 37 different ICU. At the beginning of the follow-up we asked the physician who will follow the patient in the ICU to give a score for the probability of survival of the patients. Scoring included a total of 6 scores from 0 to 5, with the "0" the worst probability "5" being the best. According to this distribution, only 1 (0.9%) of 113 patients who were given 0 points survived. Three (6.1%) of 49 with the best score of 5 died. Survival rates were significantly different in each score group (r -0.