This study aimed to investigate the risk of gastric cancer (GC) in abnormal body mass index (BMI) groups. A systematic search was carried out on Embase, PubMed/Medline, and Scopus from January 2000 to January 2023. The pooled risk ratio (RR) with a 95% confidence interval (CI) was assessed using a random-effect model. Thirteen studies with total of 14,020,031 participants were included in this systematic review. The pooled RR of GC was 1.124 (95% CI, 0.968–1.304, I²: 89.08%) in underweight class, 1.155 (95% CI, 1.051–1.270, I²: 95.18%) in overweight class, and in 1.218 (95% CI, 1.070–1.386, I²: 97.65%) obesity class. There is no difference between cardia and non-cardia gastric cancer, while non-Asian race and female gender have higher risk of cancer, as Meta-regression of obesity and overweight classes showed. These findings suggest that there is a positive association between excess body weight and the risk of GC, with a higher impact in women than men and in non-Asian than Asian populations. Since abnormal weight is tied to various diseases, including GC, healthcare experts, and policymakers should continue interventions aiming to achieve a normal BMI range.

(1) Background: In early May 2022, an increasing number of human monkeypox (mpox) cases were reported in non-endemic disparate regions of the world, which raised concerns. Here, we provide a systematic review and meta-analysis of mpox-confirmed patients presented in peer-reviewed publications over the 10 years before and during the 2022 outbreak from demographic, epidemiological, and clinical perspectives. (2) Methods: A systematic search was performed for relevant studies published in Pubmed/Medline, Embase, Scopus, and Google Scholar from 1 January 2012 up to 15 February 2023. Pooled frequencies with 95% confidence intervals (CIs) were assessed using the random or fixed effect model due to the estimated heterogeneity of the true effect sizes. (3) Results: Out of 10,163 articles, 67 met the inclusion criteria, and 31 cross-sectional studies were included for meta-analysis. Animal-to-human transmission was dominant in pre-2022 cases (61.64%), but almost all post-2022 reported cases had a history of human contact, especially sexual contact. The pooled frequency of MSM individuals was 93.5% (95% CI 91.0–95.4, I²: 86.60%) and was reported only in post-2022 included studies. The male gender was predominant in both pre- and post-2022 outbreaks, and the mean age of confirmed cases was 29.92 years (5.77–41, SD: 9.38). The most common clinical manifestations were rash, fever, lymphadenopathy, and malaise/fatigue. Proctalgia/proctitis (16.6%, 95% CI 10.3–25.6, I²: 97.76) and anal/perianal lesions (39.8%, 95% CI 30.4–49.9, I²: 98.10) were the unprecedented clinical manifestations during the 2022 outbreak, which were not described before. Genitalia involvement was more common in post-2022 mpox patients (55.6%, 95% CI 51.7–59.4, I²: 88.11). (4) Conclusions: There are speculations about the possibility of changes in the pathogenic properties of the virus. It seems that post-2022 mpox cases experience a milder disease with fewer rashes and lower mortality rates. Moreover, the vast majority of post-2022 cases are managed on an outpatient basis. Our study could serve as a basis for ongoing investigations to identify the different aspects of previous mpox outbreaks and compare them with the current ones.

Coronavirus disease 2019 (COVID-19) first emerged in Wuhan, China, in December 2019. Since that time, the frequency of bacterial and fungal coinfections has been continuously increasing. Although invasive pulmonary aspergillosis is being increasingly recognized in association with COVID-19, there is limited information regarding COVID-19-associated mucormycosis. We describe a 50-year-old woman with uncontrolled diabetes who received systemic corticosteroids and remdesevir during her admission for COVID-19. A few days after discharge, the patient was readmitted because of facial swelling and numbness, and a diagnosis of COVID-19-associated rhinosinusitis mucormycosis caused by Rhizopus arrhizus (formerly called Rhizopus oryzae) was confirmed with sequencing of the internal transcribed spacer region of the ribosomal DNA. This report aimed to address the importance of short-term follow-up for COVID-19 patients who have received systemic corticosteroids, particularly those with predisposing conditions, because early detection and prompt, aggressive treatment are essential for the management of invasive fungal infections.

We aimed to propose a mortality risk prediction model using on-admission clinical and laboratory predictors. We used a dataset of confirmed COVID-19 patients admitted to three general hospitals in Tehran. Clinical and laboratory values were gathered on admission. Six different machine learning models and two feature selection methods were used to assess the risk of in-hospital mortality. The proposed model was selected using the area under the receiver operator curve (AUC). Furthermore, a dataset from an additional hospital was used for external validation. 5320 hospitalized COVID-19 patients were enrolled in the study, with a mortality rate of 17.24% (N = 917). Among 82 features, ten laboratories and 27 clinical features were selected by LASSO. All methods showed acceptable performance (AUC > 80%), except for K-nearest neighbor. Our proposed deep neural network on features selected by LASSO showed AUC scores of 83.4% and 82.8% in internal and external validation, respectively. Furthermore, our imputer worked efficiently when two out of ten laboratory parameters were missing (AUC = 81.8%). We worked intimately with healthcare professionals to provide a tool that can solve real-world needs. Our model confirmed the potential of machine learning methods for use in clinical practice as a decision-support system.

Objective: The actual impact of the pandemic on COVID-19 specific mortality is still unclear due to the variability in access to diagnostic tools. This study aimed to estimate the excess all-cause mortality in Iran until September 2021 based on the national death statistics.Results: The autoregressive integrated moving average was used to predict seasonal all-cause death in Iran (R-squared = 0.45). We observed a 38.8% (95% confidence interval (CI) 29.7%–40.1%) rise in the all-cause mortality from 22 June 2020 to 21 June 2021. The excess all-cause mortality per 100,000 population were 178.86 (95% CI 137.2–220.5, M:F ratio = 1.3) with 49.1% of these excess deaths due to COVID-19. Comparison of spring 2019 and spring 2021 revealed that the highest percent increase in mortality was among men aged 65–69 years old (77%) and women aged 60–64 years old (86.8%). Moreover, the excess mortality among 31 provinces of Iran ranged from 109.7 (Hormozgan) to 273.2 (East-Azerbaijan) per 100,000 population.In conclusion, there was a significant rise in all-cause mortality during the pandemic. Since COVID-19 fatality explains about half of this rise, the increase in other causes of death and underestimation in reported data should be concerned by further studies.

Background. The outbreak of coronavirus disease 2019 (COVID‐19) dates back to December 2019 in China. Iran has been among the most prone countries to the virus. The aim of this study was to report demographics, clinical data, and their association with death and CFR. Methods. This observational cohort study was performed from 20th March 2020 to 18th March 2021 in three tertiary educational hospitals in Tehran, Iran. All patients were admitted based on the WHO, CDC, and Iran’s National Guidelines. Their information was recorded in their medical files. Multivariable analysis was performed to assess demographics, clinical profile, outcomes of disease, and finding the predictors of death due to COVID‐19. Results. Of all 5318 participants, the median age was 60.0 years, and 57.2% of patients were male. The most significant comorbidities were hypertension and diabetes mellitus. Cough, dyspnea, and fever were the most dominant symptoms. Results showed that ICU admission, elderly age, decreased consciousness, low BMI, HTN, IHD, CVA, dialysis, intubation, Alzheimer disease, blood injection, injection of platelets or FFP, and high number of comorbidities were associated with a higher risk of death related to COVID‐19. The trend of CFR was increasing (WPC: 1.86) during weeks 25 to 51. Conclusions. Accurate detection of predictors of poor outcomes helps healthcare providers in stratifying patients, based on their risk factors and healthcare requirements to improve their survival chance.