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Jernigan Sexton posted an update 6 months, 2 weeks ago
Public interest in radiation rose after the Tokyo Electric Power Company (TEPCO) Fukushima Daiichi Nuclear Power Station accident was caused by an earthquake off the Pacific coast of Tohoku on March 11, 2011. Various reports on the accident and radiation were spread by the mass media, and people displayed their emotional reactions, which were thought to be related to information about the Fukushima accident, on Twitter, Facebook, and other social networking sites. Fears about radiation were spread as well, leading to harmful rumors about Fukushima and the refusal to test children for radiation. It is believed that identifying the process by which people emotionally responded to this information, and hence became gripped by an increased aversion to Fukushima, might be useful in risk communication when similar disasters and accidents occur in the future. There are few studies surveying how people feel about radiation in Fukushima and other regions in an unbiased form.
The purpose of this study is to identifgradually trended toward positive feelings, the bots and retweets about Fukushima Prefecture trended toward negative feelings.
Polycystic ovary syndrome (PCOS) is the most common endocrine disorder in women of reproductive age. Diet and lifestyle programs improve health, but women’s preferences for these programs have not been formally explored.
The aim of our study was to examine diet and lifestyle program preferences among women with PCOS.
We conducted a cross-sectional online survey of women with PCOS.
At least half of the 197 respondents expressed strong interest in programs addressing energy level, anxiety, depression, weight, diabetes prevention, menstrual period regulation, and hirsutism. Similarly, at least half reported willingness to modify their sleep, stress, and physical activity; and slightly less than half reported willingness to adopt a very low-carbohydrate, paleo, or low-glycemic index diet. see more At least half reported interest in online or mobile programs and email-based mentoring. Younger age was associated with interest in help with acne and fertility; higher body mass index was associated with wanting help with weight loss, energy, and anxiety; and greater stress eating was associated with wanting help with depression, anxiety, and menstrual period regulation.
To our knowledge, this is the first study to examine attitudes and preferences of women with PCOS toward such programs. Future online and mobile diet and lifestyle programs may be able to capitalize on this information to better target this population’s expressed preferences.
To our knowledge, this is the first study to examine attitudes and preferences of women with PCOS toward such programs. Future online and mobile diet and lifestyle programs may be able to capitalize on this information to better target this population’s expressed preferences.
We aimed to evaluate the diagnostic performance of low-dose chest computed tomography (CT) in patients under investigation for coronavirus disease 2019 (COVID-19).
This retrospective study included 330 patients suspected of having COVID-19 from March 15 to April 16, 2020. We examined 306 patients upon initial presentation using both CT and real-time reverse-transcriptase polymerase-chain-reaction (rRT-PCR). The diagnostic performance of CT was calculated using rRT-PCR as a reference. Clinical and laboratory data, CT characteristics, and lesion distribution were assessed for patients with a confirmed diagnosis via rRT-PCR.
A total of 250 patients were finally diagnosed with COVID-19. Clinical and laboratory findings included myalgia or fatigue (76%), fever (64.8%), dry cough (60.8%), elevated levels of C-reactive protein (86.4%), procalcitonin (62%), and D-dimer (58.2%), increased neutrophil-lymphocyte ratio (NLR) (54.8%), and lymphopenia (34%). Sensitivity, specificity, positive predictive value (PPV) aially by radiologists. We suggest that patients with typical CT findings but negative rRT-PCR results should be isolated, and rRT-PCR should be repeated to avoid misdiagnosis.
This study aims to identify chest computed tomography (CT) characteristics of coronavirus disease 2019 (COVID-19), investigate the association between CT findings and laboratory or demographic findings, and compare the accuracy of chest CT with reverse transcription-polymerase chain reaction (RT-PCR).
Overall, 120 of 159 consecutive cases isolated due to suspected COVID-19 at our hospital between 17 and 25 March 2020 were included in this retrospective study. All patients underwent both chest CT and RT-PCR at first admission. The patients were divided into two groups laboratory-confirmed COVID-19 and clinically diagnosed COVID-19. Clinical findings, laboratory findings, radiologic features and CT severity index (CT-SI) of the patients were noted. The sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), and accuracy of chest CT were calculated for the diagnosis of COVID-19, using RT-PCR as reference.
The laboratory-confirmed and clinically diagnosed COVID-19 groups ive protein (CRP) values in the laboratory-confirmed COVID-19 subgroup. Chest CT and RT-PCR positivity rates among patients with suspected COVID-19 were 87.5% (105/120) and 57.5% (69/120), respectively. The sensitivity, specificity, PPV, NPV and accuracy rates of chest CT were determined as 94.2% (95% confidence interval , 85.8-98.4), 21.57% (95% CI, 11.3-35.3), 61.90% (95% CI, 58.2-65.5), 73.3% (95% CI, 48.2-89.1) and 63.3% (95% CI, 54.1-71.9), respectively.
Chest CT has high sensitivity and low specificity in the diagnosis of COVID-19. The clinical, laboratory, and CT findings of laboratory-confirmed and clinically diagnosed COVID-19 patients are similar.
Chest CT has high sensitivity and low specificity in the diagnosis of COVID-19. The clinical, laboratory, and CT findings of laboratory-confirmed and clinically diagnosed COVID-19 patients are similar.
The aim of this study was to evaluate visual and software-based quantitative assessment of parenchymal changes and normal lung parenchyma in patients with coronavirus disease 2019 (COVID-19) pneumonia. The secondary aim of the study was to compare the radiologic findings with clinical and laboratory data.
Patients with COVID-19 who underwent chest computed tomography (CT) between March 11, 2020 and April 15, 2020 were retrospectively evaluated. Clinical and laboratory findings of patients with abnormal findings on chest CT and PCR-evidence of COVID-19 infection were recorded. Visual quantitative assessment score (VQAS) was performed according to the extent of lung opacities. Software-based quantitative assessment of the normal lung parenchyma percentage (SQNLP) was automatically quantified by a deep learning software. The presence of consolidation and crazy paving pattern (CPP) was also recorded. Statistical analyses were performed to evaluate the correlation between quantitative radiologic assessments, and clinical and laboratory findings, as well as to determine the predictive utility of radiologic findings for estimating severe pneumonia and admission to intensive care unit (ICU).