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Purpose: Cancellation or postponement of sports events due to the COVID-19 pandemic has caused great stress for athletes. There are limited studies on how physical activity levels, nutritional habits, and sleep quality are affected, especially in physically disabled athletes(para-athletes) during the pandemic process. The aim of the research is to examine the physical activity, nutritional habits, and sleep quality levels of para-athletes during the pandemic process. Material and Methods: Eighty-seven male para-athletes were included in the study. The personal data form required to determine the characteristics within the study subject International Physical Activity Questionnaire Short Form (IPAQ Short Form), the Pittsburg Sleep Quality Index Questionnaire were used in a way consistent with the study. In addition to these sections, changes in participants' nutritional habits were also questioned. Results: The total MET values of para-athletes were determined as 3233 +/- 1421. The sleep quality index total score averages of the participants were 5.83 +/- 0.80 points, indicating the level of "poor sleep quality". Food consumption of the participants It was found that 56% of them increased their food consumption, 28% did not change, and 18% decreased. Conclusion: The results of the study showed that physical activity, nutrition, and sleep processes, which have an important place in the life cycle of para-athletes, were adversely affected during the pandemic process.
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Background and Aim: Troponin and some inflammation biomarkers were associated with Covid-19 severity and intensive care unit (ICU) admissions related with cardiac injury. But cardiac magnetic resonance imaging (CMRI) remains to be the gold standard for revealing myocardial involvement. In this study, we aim to investigate whether admission troponin levels were associated with both clinical severity and cardiac injury shown using CMRI. Method(s): The study sample consisted of 51 recovered patients who had needed in-hospital follow-up, either in COVID-19 ICU (Group 1, n=16) and COVID-19 clinics (Group 2, n=35). Hs-cTnT, CRP, PCT, NLR, D-dimer, ferritin levels and SII and were measured at admission to hospital. All of these participants were referred to electrocardiography (ECG), transthoracic echocardiography (TTE) and CMRI simultaneously on an average of 4-6 weeks after discharge. Study groups were compared according to these findings. Result(s): Among study population, 25 patients (49%) had SARS-CoV-2 variants, including the Alpha variant [n=16, (31%)], the Beta [n=5, (10%)] and the Delta variant [n=4, (8%)]. Respiratory distress as initial symptom was higher in group 1 compared to group 2. Group 1 had higher respiratory rate, lower SpO2 levels and higher supplemental oxygen requirement compared with group 2, which would explain respiratory distress. Hs-cTnT levels and inflammatory biomarkers were significantly higher in ICU patients (p<0.05). ROC curve revealed significant correlation between Hs-cTnT, NLR, D-dimer, ferritin, CRP, SII levels and ICU admission (p<0.05) (Figure 1). ECG and TTE features of groups were similar. Functional parameters were also similar for both groups in CMRI findings. But, a total of 32 patients had any kind of injury on CMRI, including at least one of the following: myocardial oedema (n=7), pericardial effusion (n=13) and right ventricular failure (n=12), ischemic (n=8) or non-ischemic fibrosis (n=27) on late gadolinium enhancement imaging. CMRI images of various myocardial injury patterns were shown in Figure 2. There was a significant difference between patients who followed up in Group 1 vs. Group 2 for non-ischemic fibrosis [n=12 (75%) vs. n=15 (43%);p=0.03]. ICU patients had more common non-ischemic fibrosis on CMRI (p=0.03). ROC curve exposed a significant correlation between Hs-cTnT and SII levels with any injury shown on CMRI (p<0.05) (Figure 3). Conclusion(s): Admission troponin and SII levels were associated with disease severity and cardiac injury shown by CMRI even if echocardiographic evaluation is normal. Both of them could be used to have an idea about both the need of ICU and serious cardiac involvement. (Figure Presented).
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Objectives: Coronavirus disease 2019 (COVID-19) can affect the menstrual cycle and menstrual flow. To examine changes in menstrual symptoms of women recovering from COVID-19 and to identify factors that influence these changes. Material(s) and Method(s): A questionnaire, prepared using Google Forms, was completed by 180 women (26.08+/-6.62 years) recovered from COVID-19. The menstrual symptoms, menstrual pain, fatigue severity and anxiety level of the participants were evaluated respectively with the Menstrual Symptom Questionnaire (MSQ), visual analogue scale (VAS), fatigue severity scale (FSS), and coronavirus anxiety scale (CAS). Result(s): Post-COVID-19 individuals' MSQ totals, subgroup scores, FSS scores and menstrual pain levels showed significant increase compared to pre-COVID-19. Regression analysis identified that age at menarche, changes in FSS and VAS scores as contributors to 38.4% of the variance explained in the significant regression for change in MSQ score. Individuals with prolonged fatigue, muscle- joint pain and dyspnea symptoms showed increase in MSQ total scores (P = 0.006, P = 0.009, P = 0.046 respectively) and MSQ negative effects/somatic complaints scores (P = 0.004, P = 0.002, P = 0.017 respectively). Individuals with prolonged gastrointestinal symptoms showed increase in MSQ pain symptoms (P = 0.029) and MSQ coping methods scores (P = 0.002), while those with prolonged muscle and joint pain showed increase in MSQ coping methods (P = 0.022) scores. Conclusion(s): The results of this study indicated that menstrual symptoms, fatigue, and menstrual pain severity are deteriorated in women recovered from COVID-19. Age at menarche, changes in fatigue and menstrual pain after COVID-19 were determiners of the deteriorated menstrual symptoms. Menstrual symptoms were more severe in those who have prolonged fatigue, dyspnea, muscle- joint pain and gastrointestinal symptoms. Copyright © 2022 The Author(s).
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BACKGROUND: This study aimed to investigate pregnancy frequency and evaluate the factors affecting live births in hemodialysis (HD) patients. METHODS: Female HD patients whose pregnancy was retrospectively reported between January 1, 2014, and December 31, 2019. The duration of HD, primary disease, and the information on whether the pregnancy resulted in abortion, stillbirth, or live birth, whether the HD duration was prolonged after diagnosing the pregnancy and whether it accompanied preeclampsia were recorded. RESULTS: In this study, we reached 9038 HD female patients' data in the study. A total of 235 pregnancies were detected in 145 patients. The mean age was 35.42 (35 ± 7.4) years. The mean age at first gestation was 30.8 ± 6.5 years. The average birth week was 32 (28 -36) weeks. A total of 53.8% (no = 78) of the patients had live birth, 51.7% (no = 70) had at least one abortion in the first 20 weeks, and 13.1% (no = 19) had at least one stillbirth after 20 weeks. The rate of patients' increased numbers of dialysis sessions during pregnancy was 71.7%. The abortion rate was 22.4% in those with increased HD sessions, whereas 79.3% in those not increased HD sessions (p < 0.001). Live birth frequency was 67.2% in the increased HD sessions group and 3.4% in those who did not differ in HD sessions (p < 0.001). DISCUSSION: For the first time, we reported pregnancy outcomes in HD female patients, covering all regions of Turkey. It has been observed that;increasing the number of HD sessions in dialysis patients will decrease fetal and maternal complications and increase live birth rates.
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Purpose The purpose of this study is to investigate volatility connectedness between major cryptocurrencies by the virtue of market capitalization. In this context, this paper implements the frequency connectedness approach of Barunik and Krehlik (2018) and to measure short-, medium- and long-term connectedness between realized volatilities of cryptocurrencies. Additionally, this paper analyzes network graphs of directional TO/FROM spillovers before and after the announcement of the COVID-19 pandemic by the World Health Organization. Design/methodology/approach In this study, we examine the volatility connectedness among eight major cryptocurrencies by the virtue of market capitalization by using the frequency connectedness approach over the period July 26, 2017 and October 28, 2020. To this end, this paper computes short-, medium- and long-cycle overall spillover indexes on different frequency bands. All indexes properly capture well-known events such as the 2018 cryptocurrency market crash and COVID-19 pandemic and markedly surge around these incidents. Furthermore, owing to notably increased volatilities after the official announcement of the COVID-19 pandemic, this paper concentrates on network connectedness of volatility spillovers for two distinct periods, July 26, 2017-March 10, 2020 and March 11, 2020-October 28, 2020, respectively. In line with the related studies, major cryptocurrencies stand at the epicenter of the connectedness network and directional volatility spillovers dramatically intensify based on the network analysis. Findings Overall spillover indexes have fluctuated between 54% and 92% in May 2018 and April 2020. The indexes gradually escalated till November 9, 2018 and surpassed their average values (71.92%, 73.66% and 74.23%, respectively). Overall spillover indexes dramatically plummeted till January 2019 and reached their troughs (54.04%, 57.81% and 57.81%, respectively). Etherium catalyst the highest sum of volatility spillovers to other cryptocurrencies (94.2%) and is followed by Litecoin (79.8%) and Bitcoin (76.4%) before the COVID-19 announcement, whereas Litecoin becomes the largest transmitter of total volatility (89.5%) and followed by Bitcoin (89.3%) and Etherium (88.9%). Except for Etherium, the magnitudes of total volatility spillovers from each cryptocurrency notably increase after - COVID-19 announcement period. The medium-cycle network topology of pairwise spillovers indicates that the largest transmitter of total volatility spillover is Litecoin (89.5%) and followed by Bitcoin (89.3%) and Etherium (88.9%) before the COVID-19 announcement. Etherium keeps its leading role of transmitting the highest sum of volatility spillovers (89.4%), followed by Bitcoin (88.9%) and Litecoin (88.2%) after the COVID-19 announcement. The largest transmitter of total volatility spillovers is Etherium (95.7%), followed by Litecoin (81.2%) and Binance Coin (75.5%) for the long-cycle connectedness network in the before-COVID-19 announcement period. These nodes keep their leading roles in propagating volatility spillover in the latter period with the following sum of spillovers (Etherium-89.5%, Bitcoin-88.9% and Litecoin-88.1%, respectively). Research limitations/implications The study can be extended by including more cryptocurrencies and high-frequency data. Originality/value The study is original and contributes to the extant literature threefold. First, this paper identifies connectedness between major cryptocurrencies on different frequency bands by using a novel methodology. Second, this paper estimates volatility connectedness between major cryptocurrencies before and after the announcement of the COVID-19 pandemic and thereby to concentrate on its impact on the cryptocurrency market. Third, this paper plots network graphs of volatility connectedness and herewith picture the intensification of cryptocurrencies due to a major financial distress event.
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Introduction: It is known that nitric oxide (NO) is actively involved against microorganisms due to its antiviral and bacteriostatic activity in the upper respiratory tract and rises in the blood and exhaled air during this process. Therefore, considering that COVID-19 can damage various tissues and cells in the body, it is predicted that Covid-19 may be an early biomarker in the diagnosis of measurement of Nitric oxide (FENO) in Exhaled air. Materials and methods: 102 COVID-19 patients with different clinical findings, whose diagnoses were made by polymerase chain reaction (PCR) and whose treatment was started, were included in the study. A control group was formed from healthy volunteers. Demographic features, clinical findings and the amount of nitric oxide (FeNO) measured in exhaled air were recorded. Results: In terms of exhaled nitric oxide (FeNO) values, the exhaled nitric oxide value in COVID-19 patients was 31.73 ± 14.80 mmol / lt, while it was 15.48 ± 6.64 mmol / lt in the control group and was statistically significant. In the Roc graph, FeNO threshold value was measured as 24.5 Mmol level and its sensitivity was 62.1% and specificity was 96.0% in diagnosing Covid-19. Conclusion: Non-invasive method, FeNO measurement, can be used in an easy and outpatient environment and is reproducible. This shows that it is a candidate to be among the diagnostic methods in the future. © 2021 A. CARBONE Editore. All rights reserved.