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This meta-analysis assessed the association between gonadotropin hormone-releasing hormone (GnRH) antibodies and irritable bowel syndrome (IBS). We defined a search strategy and implemented it with PubMed, Ovid, Scopus, and Web of Science databases for English language publications. The data were evaluated for acceptability, and randomized controlled studies as well as case-control, cross-sectional, and cohort studies reporting the prevalence of GnRH antibodies in IBS patients were included. The total number of patients in the included studies was 1095: 270 patients in the IBS group and 825 patients in the control group. By comparing the IBS group and the control group, we found a statistically significant association between IBS and the increased prevalence of GnRH IgM antibodies (risk ratio = 2.29, 95% confidence interval = 1.58 to 3.31, P < 0.0001). We also found a statistically significant association between IBS and increased prevalence of GnRH receptor IgM antibodies compared with controls (risk ratio = 3.80, 95% confidence interval = 1.72 to 8.38, P = 0.001). The meta-analysis revealed a statistically significant association between IBS and increased prevalence of GnRH IgM and GnRH receptor IgM antibodies.
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Surges of technology use along with limited interpersonal interactions have led to the amplification and dissemination of false information during the COVID-19 pandemic. Infodemic refers to an overabundance of information that may have increased burden of covid-19 pandemic and mental disorder. Given the rise of suicide behavior during the pandemic, infodemic has been considered as a risk of suicidal behavior. The aim of this article is to address suicide in the context of infodemic and provide some strategy to adjust the impact of infodemic on mental health.
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Subdural empyema is a rare intracranial infection with an accumulation of purulent material between the dura and arachnoid matter. We report a case of 17 years old presented with an altered conscious level. CSF analysis showed increased WBCs. His situation has improved after treating by acyclovir, ceftriaxone, vancomycin, and dexamethasone.
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We report a rare case of a 50-year-old female patient with COVID-19 presented to the emergency department where supplementary oxygen is delivered via noninvasive face mask ventilation. X-ray imaging confirmed the existence of pneumoperitoneum. CT scan was not applicable due to the advanced status of the patient.
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INTRODUCTION: The retroperitoneum is the anatomical compartment positioned behind the peritoneal cavity. It is separated into three primary spaces: the anterior pararenal, perirenal, and posterior pararenal spaces. Retroperitoneal cystic mass is a rare surgical problem that is often wrongly identified before surgery. CASE PRESENTATION: We report a case of a 27-year-old female presenting with abdominal swelling and pain starting from 9 months. An abdominal computed tomography scan showed a right adnexal mass with a high probability of a serous ovarian. The patient was diagnosed with ovarian tumors before surgery, but it was identified with a retroperitoneal cyst during surgery. DISCUSSION: A retroperitoneal cyst's clinical signs and symptoms vary, and the diagnosis can often be challenging. Computed tomography scans are appropriate for assessing retroperitoneal pathology because they produce separate sectional images and couldn't find the correct diagnosis in previous cases. CONCLUSION: This paper shows the rare case of primary retroperitoneal lesions, which can be hard to diagnose before surgery, even though medical imaging has come a long way.
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Artificial intelligence has been prevalent recently as its use in the medical field is noticed to be increased. However, middle east countries like Syria are deficient in multiple AI implementation methods in the field of medicine. So, holding these AI implementation methods in the medical field is necessary, which may be incredibly beneficial for making diagnosis more accessible and help in the treatment. This paper intends to determine AI's knowledge, attitude, and practice among doctors and medical students in Syria. A questionnaire conducted an online cross-sectional study on the google form website consisting of demographic data, knowledge, and perception of AI. There were 1,494 responses from both doctors and medical students. We included Syrian medical students and doctors who are currently residing in Syria. Of the 1,494 participants, 255 (16.9%) are doctors, while the other 1,252 (83.1%) are undergraduate medical students. About 1,055 (70%) participants have previous knowledge about AI. However, only 357 (23.7%) participants know about its application in the medical field. Most have shown positive attitudes toward its necessity in the medical field; 689 (45.7%) individuals strongly agree, and 628 (41.7%) agree. The undergraduate students had 3.327 times more adequate knowledge of AI than students in the first year. In contrast, the undergraduate 6th-year students had 2.868 times the attitude toward AI higher than students in the first year. The residents and assistant professors had 2.371 and 4.422 times the practice of AI higher than students, respectively. Although most physicians and medical students do not sufficiently understand AI and its significance in the medical field, they have favorable views regarding using AI in the medical field. Syrian medical authorities and international organizations should suggest including artificial intelligence in the medical field, particularly when training residents and fellowship physicians.
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BACKGROUND: After the COVID-19 pandemic, anxiety and depression have reached high levels, especially after the last wave, Omicron. Healthcare workers in contact with COVID-19 patients or those who come in contact with them may exhibit high levels of anxiety and depression. Therefore, we aimed to assess anxiety and depression symptoms among ICU companions of COVID-19 patients. METHODS: From 30 November 2021 to 1 March 2022, sixth-year medical students at Aleppo University Hospital conducted interviews with the companions of COVID-19 patients who they brought their patient to the ICU centre as part of a cross-sectional quantitative study using the PHQ-9 and GAD-7 tools to gauge their level of anxiety and depression among companions of COVID-19 patients. The data were analyzed using the SPSS program. In addition, logistic regression models were used to study possible factors of anxiety and depression symptoms during COVID-19. RESULTS: The total number was 997 participants in contact with COVID-19 patients. The mean score of the depression assessment tool (PHQ-9) in our questionnaire was 9.5 with a range of 0 to 27. At the same time, the anxiety assessment tool (GAD-7) had a mean score of 9.1, ranging from 0 to 21. A binary logistic regression was used to predict the relationship between depression and anxiety and various factors. We found that the companions with medical specialties were substantially less likely to develop anxiety than other companions [AOR = 0.459; 95%CI (0.23-0.9)], in addition females were substantially higher likely to develop depression than males [AOR = 1.322; 95%CI (0.992-1.762)]. 45.4% of companions had moderate to severe anxiety, in additon 50.8% of companions had moderate to severe depression. CONCLUSION: Our research reveals that moderate to severe anxiety and sadness are present in roughly half of the COVID19 patients' companions. Females, people with children, and hard workers were more inclined to feel anxious than others, and those who are not in the medical field were more likely to suffer from depression than others, thus it is critical to assist these groups during the present outbreaks (Omicron and Monkeybox).