BackgroundThere are no determined treatment agents for the severe coronavirus disease 2019 (COVID-19); therefore, it is suggested that methylprednisolone, as an immunosuppressive treatment, can reduce the inflammation of the respiratory system.MethodsWe conducted a single-blind, randomised, controlled, clinical trial involving severe hospitalised patients with confirmed COVID-19 at the early pulmonary phase of the illness in Iran. The patients were randomly allocated in a 1:1 ratio by block randomisation method to receive standard care with methylprednisolone pulse (intravenous injection, 250 mg·day−1 for 3 days) or standard care alone. The study endpoint was the time of clinical improvement or death, whichever came first. Primary and safety analysis was done in the intention-to-treat (ITT) population.ResultsSixty-eight eligible patients underwent randomisation (34 patients in each group) from April 20, till Jun 20, 2020. In the standard care group, six patients received corticosteroids by the attending physician during treatment and excluded from the ITT population. Patients with clinical improvement were higher in the methylprednisolone group than in the standard care group (94·1% versus 57·1%), and the mortality rate was numerically lower in the methylprednisolone group (5·9% versus 42.9%; p <0·001). We demonstrated that patients in the methylprednisolone intervention group had a significantly increased survival time compared with the patients in the standard care group [Log rank test: p<0.001; Hazard ratio: 0.293; 95% C‎‎I: 0.‎154–0.556]. A total of two patients in each group (5·8% and 7·1% respectively) showed severe adverse events between initiation of treatment and the end of the study.ConclusionsOur results suggested that methylprednisolone pulse could be an efficient therapeutic agent for hospitalised severe COVID-19 patients at the pulmonary phase.

Pipelines are one of the most popular and effective ways of transporting hazardous materials, especially natural gas. However, the rapid development of gas pipelines and stations in urban areas has introduced a serious threat to public safety and assets. Although different methods have been developed for risk analysis of gas transportation systems, a comprehensive methodology for risk analysis is still lacking, especially in natural gas stations. The present work is aimed at developing a dynamic and comprehensive quantitative risk analysis (DCQRA) approach for accident scenario and risk modeling of natural gas stations. In this approach, a FMEA is used for hazard analysis while a Bow-tie diagram and Bayesian network are employed to model the worst-case accident scenario and to assess the risks. The results have indicated that the failure of the regulator system was the worst-case accident scenario with the human error as the most contributing factor. Thus, in risk management plan of natural gas stations, priority should be given to the most probable root events and main contribution factors, which have identified in the present study, in order to reduce the occurrence probability of the accident scenarios and thus alleviate the risks.

No abstract

The severe acute respiratory syndrome-coronavirus 2 (SARS-CoV-2) spread rapidly all over the world in late 2019 and caused critical illness and death in some infected patients. This study aimed at examining several laboratory factors, especially inflammatory and immunological mediators, to identify severity and mortality associated biomarkers. Ninety-three hospitalized patients with confirmed coronavirus disease 2019 (COVID-19) were classified based on disease severity. The levels of biochemical, hematological, immunological, and inflammatory mediators were assessed, and their association with severity and mortality were evaluated. Hospitalized patients were mostly men (77.4%) with an average (standard deviation) age of 59.14 (14.81) years. The mortality rate was significantly higher in critical patients (85.7%). Increased serum levels of blood sugar, urea, creatinine, uric acid, phosphorus, total bilirubin, serum glutamic-oxaloacetic transaminase, serum glutamic-oxaloacetic transaminase, lactic dehydrogenase, C-reactive protein, ferritin, and procalcitonin were significantly prevalent (p=0.002, p<0.001, p<0.001, p=0.014, p=0.047, p=0.003, p<0.001, p<0.001, p<0.001, p<0.001, P<0.001, and p<0.001, respectively) in COVID-19 patients. Decreased red blood cell, hemoglobin, and hematocrit were significantly prevalent among COVID-19 patients than healthy control subjects (p<0.001 for all). Troponin-I, interleukin-6, neutrophil/lymphocyte ratio (NLR), procalcitonin, and D-dimer showed a significant association with the mortality of patients with specificity and sensitivity more than 60%. Age, sex, underlying diseases, blood oxygen pressure, complete blood count along with C-reactive protein, lactic dehydrogenase, procalcitonin, D-dimer, and interleukin-6 evaluation help to predict the severity and required management for COVID-19 patients. Further investigations are highly recommended in a larger cohort study for validation of the present findings.

The results of the present study could provide guidance to help safety and health management by adopting proper intervention strategies to reduce mining accidents.

Background: Firefighters often perform multiple tasks during firefighting operations under unknown and unpredictable conditions in hot and hostile environments. Methods: In this interventional study each firefighters engaged in 4 conditions: namely (1) no cooling device; control (NC), (2) cooling gel (CG), (3) cool vest (CV), and (4) CG+CV. Cooling effects of the employed interventions were evaluated based on heart rate (HR), temporal temperature (TT), reaction time (RT), and the correct response (CR). Results: HR and TT values for use of CG+CV (147.47 bpm [SD 4.8]; 37.88°C [SD 0.20]) and CV bpm (147.53 [SD 4.67]; 37.90°C [SD 0.22]) were significantly lower than the CG (153.67 bpm [SD 4.82]; 38.10°C [SD 0.22]) and NC (154.4 bpm [SD 4.91]; 38.11°C [SD 0.23]) at the end of the activity. RT and CR for use of CG + CV (389.87 ms [SD 6.12]; 143.53 [SD 1.24]) and CV (389.53 ms [SD 6.24]; 143.47 [SD 1.18]) were significantly higher than the CG (385.73 [SD 7.25] ms; 143.07 [SD 0.88]) and NC (385.67 ms [SD 7.19]; 143.00 [SD 0.84]) at the end of the activity. Conclusion: It is concluded that CV was more effective than the CG in attenuating physiological responses and cognitive functions during firefighting operations. Furthermore, combining CV with CG provides no additional benefit.

Process complex systems in particular oil and gas plants due to dealing with hazardous materials at severe process conditions are much prone to catastrophic accidents. In this context, safety risk analysis is a crucial tool to develop effective strategies to prevent accident and provide mitigative measures. Dynamic risk analysis (DRA) is one of the most practical approaches for risk analysis that helps provide safer operations of complex process systems. The present work is aimed at demonstrating the application of an integrated DRA approach to comprehensive quantitative modeling and analysis of the both aspects of risk, that is, probability and consequence assessments. In this approach, first, the worst case scenario is identified and then a robust tool is developed for dynamic accident scenario modeling and risk assessment by means of Bayesian Network. This approach is applied to risk analysis of a flammable liquid storage system at a gas refinery. The work provides valuable information on the identification and comprehensive analysis of worst case accident scenarios, their main consequences, critical basic events, and minimal cut sets which lead to accident scenarios and also for dynamic updating of probabilities and risk. The obtained results are more appropriate and rigorous to developing preventive and mitigative strategies for potential accident scenarios and thus increase the safety level in the complex process systems. © 2017 American Institute of Chemical Engineers Process Saf Prog 36: 399–407, 2017

Background: Researchers have already reported a high level of interleukin (IL)-6 in patients affected by Coronavirus Disease 2019 (COVID-19). In this study, we investigated the surge of IL-6 level and its association with the clinical and paraclinical markers in these patients. Materials and Methods: The study sample comprised 205 confirmed hospitalized patients with Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) and 70 healthy volunteer individuals. Routine laboratory examinations, including hematology, biochemistry, and hormone analysis, as well as IL-6 level measurement, were conducted. The patients grouped into 5 based on their IL-6 levels. Then, they were compared with regard to their need for mechanical ventilator and clinical laboratory routine tests. Results: IL-6 levels were significantly higher in hospitalized patients compared with healthy individuals (P<0.001). The IL-6 level was approximately 10-fold of the normal range in 22.9% of the patients. Also, more than 56.1% of them signify IL-6 over 3-fold of the normal range. IL-6