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Objective:This study aimed to examine the sleep quality of common variable immunodeficiency (CVID) patients and to investigate the relationship between sleep quality and depression, anxiety, fatigue, excessive daytime sleepiness and naturel killer (NK) cell counts.Materials and Methods:The study included 53 patients followed with CVID diagnosis. To determine sleep quality and conditions associated with sleep quality in CVID patients, Pittsburgh sleep quality index (PSQI), fatigue severity scale (FSS), Hamilton depression scale (HAM-D), Hamilton anxiety scale (HAM-A) and Epworth sleepiness scale (ESS) were used.Results:Fatigue was found in 37 (70%) patients, poor sleep quality in 34 (64%), depression in 20 (38%), anxiety in 16 (30%), and excessive daytime sleepiness in 11 (21%) patients. All patients CVID patients received immunoglobulin replacement therapy: Intravenous immunoglobulin (IVIG) in 37 (72%) and subcutaneous immunoglobulin (SCIG) in 16 (28%) patients. The PSQI, HAM-A, HAM-D and FSS scores of the patients receiving IVIG treatment were higher than those of the patients receiving SCIG treatment (all, p

Aim: Candidemia has high morbidity and mortality rate in critically ill patients hospitalized in intensive care units. Prompt initiation of accurate anti-fungal therapy is essential for survival. In this study, a 6-year retrospective candidemia analysis of pediatric intensive care unit (PICU) was performed to review candida species distribution, risk factors for candidemia and change in the antifungal resistance in years. Material and Method: The candidemia episodes of children followed in the PICU of XXX Hospital between January 2014 and January 2020 were analyzed. The demographic and clinical characteristics, laboratory findings, treatments and outcomes of the patients were obtained from the medical records. Results: Fifty-nine episodes of candidemia (54.2% female) were reported in six years, median age at diagnosis was 43 months (range 1-225), median hospital stay was 48 days (range 3-664). All patients had used broad-spectrum antibiotics, majority had comorbidities (89.8%), nasogastric tube (84.7), central venous catheter (78.0%), and on mechanic ventilation (76.3%). Type of candida species was identified in 36 episodes of candidemia; 47.2% of these episodes were caused by C. parapsilosis, 38,9% by C. albicans, 8.3% by C. glabrata (8.3%), 2.8% by C. lusitaniae, and 2.8% by C. tropicalis. Length of hospital stay was longer among patients with nonalbicans candidemia, and these patients had higher leucocyte count at diagnosis. The rate of antifungal resistance increased over the years. Overall, thirty-day mortality rate was 16.9%. Conclusion: For critically ill patients with markedly elevated leucocyte count and long hospital stay, empiric antifungal treatment should cover nonalbicans candida with antifungal resistance.

Objective: Body mass index (BMI) and waist circumference (WC) as measures of obesity have some limitations. The aim of this study was to evaluate whether one measure could predict the presence of diastolic dysfunction (DD) more accurately than the other measures. Methods: A total of 91 obese patients without any other risk factors for DD were prospectively enrolled. Echocardiographic examination was performed. DD was defined and categorized according to recent guidelines. The study participants were divided into 2 groups according to the presence of DD. Weight, height, and WC were measured; BMI and waist-to-hip ratio (WHR) were calculated; and a body shape index (ABSI) was calculated as WC/(BMI2/3height1/2). The associations between ABSI, BMI, WHR, and WC and the presence of DD were examined using logistic regression analyses. Analysis of covariance was used to examine the differences. Results: WC and BMI were significantly greater in subjects with DD (p=0.049 and 0.051, respectively). A greater BMI, WC, and WHR increased the risk of the presence of DD (BMIDD: odds ratio [OR]=1.096, p=0.024; WC-DD: OR=1.059, p=0.007; WHR-DD: OR=2.363, p=0.007). After adjustment for age and sex, only BMI continued to be significantly associated with DD (p=0.031). ABSI was not associated with DD. Conclusion: After adjustment for age and sex, BMI was the only predictor of DD in obesity. Despite its limitations, BMI may still be a potentially more accurate measure of DD compared with other obesity measures.