ABSTRACT
Background: The unprecedented scientific response to the SARS-Cov-2 pandemic in 2020 required the rapid development and activation of extensive clinical trial networks to study vaccines and therapeutics. The COVID-19 Prevention Network (CoVPN) coordinated hundreds of sites conducting phase 2 and 3 clinical trials of vaccines and antibody therapeutics. To facilitate these clinical trials, the CoVPN Volunteer Screening Registry (VSR) was created to collect volunteer information at scale, identify volunteers at risk of COVID-19 who met enrollment criteria, distribute candidates across clinical trial sites, and enable monitoring of volunteering and enrollment progress. Methods: We developed a secure database to support three primary web-based interfaces: a national volunteer questionnaire intake form, a clinical trial site portal, and an Administrative Portal. The Site Portal supported filters based on volunteer attributes, visual analytics, enrollment status tracking, geographic search, and clinical risk prediction. The Administrative Portal supported oversight and development with pre-specified reports aggregated by geography, trial, and trial site; charts of volunteer rates over time; volunteer risk score calculation; and dynamic, user-defined reports. Findings: Over 650,000 volunteers joined the VSR, and 1094 users were trained to utilize the system. The VSR played a key role in recruitment for the Moderna, Oxford-AstraZeneca, Janssen, and Novavax vaccine clinical trials, provided support to the Pfizer and Sanofi vaccine and prophylactic antibody clinical trials, and enhanced the diversity of trial participants. Clinical trial sites selected 166,729 volunteer records for follow-up screening, and of these 47·7% represented groups prioritized for increased enrollment. Despite the unprecedented urgency of its development, the system maintained 99·99% uptime. Interpretation: The success of the VSR demonstrates that information tools can be rapidly yet safely developed through a public-private partnership and integrated into a distributed and accelerated clinical trial setting. We further summarize the requirements, design, and development of the system, and discuss lessons learned for future pandemic preparedness.
ABSTRACT
Applications such as medical diagnosis, navigation, robotics, etc., require 3D images. Recently, deep learning networks have been extensively applied to estimate depth. Depth prediction from 2D images poses a problem that is both ill-posed and non-linear. Such networks are computationally and time-wise expensive as they have dense configurations. Further, the network performance depends on the trained model configuration, the loss functions used, and the dataset applied for training. We propose a moderately dense encoder-decoder network based on discrete wavelet decomposition and trainable coefficients (LL, LH, HL, HH). Our Nested Wavelet-Net (NDWTN) preserves the high-frequency information that is otherwise lost during the downsampling process in the encoder. Furthermore, we study the effect of activation functions, batch normalization, convolution layers, skip, etc., in our models. The network is trained with NYU datasets. Our network trains faster with good results.
ABSTRACT
BACKGROUND: Graft fixation is important for graft take. Fibrin glue has been proposed as an ideal material, because of its human origin and it provides firm adhesion in seconds or minutes. OBJECTIVE: To evaluate the efficiency of fibrin glue, in increasing the take of skin graft. Assessment includes surgical time taken for graft fixation, haematoma/seroma formation, engraftment and wound closure by day 14. METHODS: The study is an observational prospective study conducted in the Department of Plastic Surgery, Jawaharlal Institute of Postgraduate Medical Education and Research, Puducherry, from January 2016 to June 2016. Sixteen patients who underwent split skin grafting were assessed during the study period. Fibrin glue was used on the recipient bed before grafting. RESULTS: Better haemostasis and graft adhesion, with a significant reduction of surgical time, were noted. CONCLUSION: The safety profile of fibrin glue was excellent as indicated by the lack of any related serious adverse experiences. These findings demonstrate that it is safe and effective for attachment of skin grafts, with outcomes at least as good as conventional methods.
