Spontaneous Hemothorax during pregnancy: A case report.

INTRODUCTION AND IMPORTANCE: Spontaneous hemothorax is a rare but life-threatening condition, which is the main cause of respiratory distress during pregnancy and after delivery without any evidence of post-traumatic injury. CASE PRESENTATION: A 34-year-old woman, pregnant at 20 weeks, presented in the emergency department complaining of dyspnea accompanied by epigastric pain, with dominance on the left side. Chest X-ray and CT-scan revealed an opacity by displacing heart to the right side. Considering, there was a probability of bleeding from venous arterial malformation. Inappropriate cervical condition two days after the patient appeared thermodynamically stable a cesarean section was performed. CLINICAL DISCUSSION: Pregnancy leads to increasing the size of AVM by rising cardiac output and hypoxia. Patients who are predisposed to PAVM and intend to be pregnant should be evaluated a priori. CONCLUSION: Although the hemothorax is a rare phenomenon during pregnancy, management of fetus following this critical condition requires multidisciplinary assessment.

Hearing the Voices of Wingless Angels: A Critical Content Analysis of Nurses' COVID-19 Experiences.

The world has been affected by an outbreak of the novel coronavirus (COVID-19). Health care workers are among those most at risk of contracting the virus. In the fight against the coronavirus, nurses play a critical role. Still, most social media platforms demonstrate that nurses fear that their health is not being prioritized. The purpose of this study is to investigate nurses' experiences through analyzing the main themes shared on Instagram by nurses during the COVID-19 pandemic. In contrast with highly structured research, the current paper highlights nurses' natural language use in describing their experiences during the first months of the outbreak in their workplace. Instagram captions were utilized as a data source. Leximancer was utilized for the content analysis of nurses' narratives towards their coronavirus experience. We sought to accomplish three research objectives: the first was to identify the main themes in the descriptions of nurses' experiences shared via their social media, specifically Instagram; then, to determine the relationships among concepts, and finally, to give useful implications based on the findings. The current study uses a qualitative (i.e., narratives) approach to analyze the main components of the nurses' experiences during the pandemic. The Leximancer software analysis revealed nine major textual themes and the relationships among these themes. In order of the relative importance, the themes were "patients", "coronavirus", "exhaustion", "family", "hospital", "personal protective equipment" (PPE), "shift", "fear", and "uncertainty". The results offer practical implications based on the social media information regarding nurses' overall experiences.

Enrolment Phase Results of the Tabari Cohort Study: Comparing Family History, Lipids and Anthropometric Profiles Among Diabetic Patients.

OBJECTIVES: Different factors are responsible for the silent epidemic of diabetes mellitus in developing and developed countries. This study aimed to determine the role of demographic factors, lipid profile, family history (the estimation of genetic association) and anthropometric factors on diabetes onset. METHODS: Data from the enrolment phase of the Tabari Cohort study was applied for this study and included 10,255 participants aged between 35-70 years. Anthropometric variables were measured by trained staff using standard tools. Blood specimens were collected for lipid profile and blood glucose measurements. Data analyses were performed using SPSS version 24, with univariate and multivariate logistic regression. RESULTS: The prevalence of diabetes mellitus was estimated to be 17.2% in the cohort population, 15.6% in men, and 18.3% in women. The adjusted odds ratios (95% confidence intervals) for age groups 40-49, 50-59 and over 60 were 2.58 (2.20-3.69), 5.80 (4.51-7.48) and 8.72 (6.67-11.39), respectively. In addition, the odds ratios (95% confidence intervals) for 2 (or more), and 1 affected family member were 4.12 (3.55-4.90) and 2.34 (2.07-2.65), respectively. Triglyceride concentrations more than 500, and abnormal high-density lipoprotein levels increased the odds of diabetes mellitus by 3.29- and 1.18-fold, respectively. CONCLUSION: The current study showed that old age and a family history were strong predictors for diabetes mellitus.