ABSTRACT
Background: Treatment for coronavirus disease 2019 (COVID-19) pneumonia remains largely supportive till date and multiple clinical trials took place within the short span of time to evaluate the role of investigational therapies. The anti-inflammatory effect of low dose whole lung radiation in treating pneumonia has been documented earlier. This clinical trial analyzed the effect of low dose radiation therapy (LDRT) in a moderately affected COVID-19 pneumonia patient cohort and has evaluated its effect in stopping the conversion of moderate disease into severe disease. Methods: Patients with moderate COVID-19 pneumonia as characterized by the Ministry of Health and Family Welfare (MOHFW), Government of India, were randomized (1:1) to low dose whole lung radiation versus no radiation. All treatment of patients was concurrently being given as per institutional protocol. Patients were followed up with clinical and laboratory parameters monitored on Days 1, 3, 7, and 14. Computed tomography scan (CT scan) of thorax was performed on Days 1 and 7. Patients were evaluated for conversion of moderate into severe disease as per National Early Warning Score-2 (NEWS-2 score) as the primary end point. The secondary endpoints included changes in ratio between peripheral capillary oxygen saturation and fraction of inspired oxygen (SpO2/FiO2), biochemical markers, 25-point CT severity score, and radiation induced acute pulmonary toxicities. Findings: At the interim analysis, there were seven patients in the radiation arm and six in the control. A whole lung LDRT improved the outcome of SpO2/FiO2 at Day 3; however it did not convert into a statistically significant improvement for the NEWS-2 score. The serum levels of LDH, CRP, Ferritin and D-dimer were significantly reduced on 14 days in the LDRT arm in comparison to the baseline value but were not significant between the two groups. Interpretation: LDRT seems to have the potential to prevent moderate COVID-19 pneumonia from a deteriorating to severe category. However, further randomized clinical trial with an adequate number of such patients is warranted to establish the definitive role of LDRT in the management of COVID-19 pneumonia. Funding: An intramural research project bearing code: I-27/621, was sanctioned from the All India Institute of Medical Sciences, Patna, India. Clinical Trial Registration: Clinical Trials Registry-India (CTRI/2021/06/033912, 25th May 2021) ctri.nic.in/Clinicaltrials/login.php.
ABSTRACT
Creation of a submucosal plane to separate the lesion from the deeper muscle layer in gastrointestinal tract is an integral and essential part of endoscopic resection therapies such as endoscopic mucosal resection (EMR) and endoscopic submucosal dissection (ESD). Thereby, an optimized submucosal injection technique is required to ensure a successful process. In this study, the computational fluid dynamics (CFD) technique is employed as a foundational step towards the development of a framework that can provide useful directions to optimize the injection process. Three different lifting agents, including Glycerol, Eleview®, and ORISE® gel have been used for this study. The role of different injection angles, injection dynamics, and effect of temperature are studied to understand the lifting characteristic of each agent. The study shows that Eleview® provides the highest lifting effect, including the initial injection period. To evaluate the impact of the injection process, two cases are simulated, termed static injection and dynamic injection. Under static injection, the injection angle is investigated from lower to higher angles of injection. In the dynamic injection, two cases are modulated, where a continuous change of injection angle from lower to higher degrees (denoted as clockwise) and vice-versa in the anti-clockwise direction are investigated. Increased lifting characteristics are observed at decreasing/lower angle of injection. Further, the correlation between temperature of the lifting agents and their lifting characteristics is investigated.
ABSTRACT
The present study aims to assess the effects of two different underlying RANS models on overall behavior of the IDDES methodology when applied to different flow configurations ranging from fully attached (plane channel flow) to separated flows (periodic hill flow). This includes investigating prediction accuracy of first and second order statistics, response to grid refinement, grey area dynamics and triggering mechanism. Further, several criteria have been investigated to assess reliability and quality of the methodology when operating in scale resolving mode. It turns out that irrespective of the near wall modeling strategy, the IDDES methodology does not satisfy all criteria required to make this methodology reliable when applied to various flow configurations at different Reynolds numbers with different grid resolutions. Further, it is found that using more advanced underlying RANS model to improve prediction accuracy of the near wall dynamics results in extension of the grey area, which may delay the transition to scale resolving mode. This systematic study for attached and separated flows suggests that the shortcomings of IDDES methodology mostly lie in inaccurate prediction of the dynamics inside the grey area and demands further investigation in this direction to make this methodology capable of dealing with different flow situations reliably.
