Impact of the COVID-19 Pandemic on Emergency Adult Surgical Patients and Surgical Services: An International Multi-center Cohort Study and Department Survey.

OBJECTIVES: The PREDICT study aimed to determine how the COVID-19 pandemic affected surgical services and surgical patients and to identify predictors of outcomes in this cohort. BACKGROUND: High mortality rates were reported for surgical patients with COVID-19 in the early stages of the pandemic. However, the indirect impact of the pandemic on this cohort is not understood, and risk predictors are yet to be identified. METHODS: PREDICT is an international longitudinal cohort study comprising surgical patients presenting to hospital between March and August 2020, conducted alongside a survey of staff redeployment and departmental restructuring. A subgroup analysis of 3176 adult emergency patients, recruited by 55 teams across 18 countries is presented. RESULTS: Among adult emergency surgical patients, all-cause in-hospital mortality (IHM) was 3.6%, compared to 15.5% for those with COVID-19. However, only 14.1% received a COVID-19 test on admission in March, increasing to 76.5% by July.Higher Clinical Frailty Scale scores (CFS >7 aOR 18.87), ASA grade above 2 (aOR 4.29), and COVID-19 infection (aOR 5.12) were independently associated with significantly increased IHM.The peak months of the first wave were independently associated with significantly higher IHM (March aOR 4.34; April aOR 4.25; May aOR 3.97), compared to non-peak months.During the study, UK operating theatre capacity decreased by a mean of 63.6% with a concomitant 27.3% reduction in surgical staffing. CONCLUSION: The first wave of the COVID-19 pandemic significantly impacted surgical patients, both directly through co-morbid infection and indirectly as shown by increasing mortality in peak months, irrespective of COVID-19 status.Higher CFS scores and ASA grades strongly predict outcomes in surgical patients and are an important risk assessment tool during the pandemic.

Using a Secure, Continually Updating, Web Source Processing Pipeline to Support the Real-Time Data Synthesis and Analysis of Scientific Literature: Development and Validation Study.

BACKGROUND: The scale and quality of the global scientific response to the COVID-19 pandemic have unquestionably saved lives. However, the COVID-19 pandemic has also triggered an unprecedented "infodemic"; the velocity and volume of data production have overwhelmed many key stakeholders such as clinicians and policy makers, as they have been unable to process structured and unstructured data for evidence-based decision making. Solutions that aim to alleviate this data synthesis-related challenge are unable to capture heterogeneous web data in real time for the production of concomitant answers and are not based on the high-quality information in responses to a free-text query. OBJECTIVE: The main objective of this project is to build a generic, real-time, continuously updating curation platform that can support the data synthesis and analysis of a scientific literature framework. Our secondary objective is to validate this platform and the curation methodology for COVID-19-related medical literature by expanding the COVID-19 Open Research Dataset via the addition of new, unstructured data. METHODS: To create an infrastructure that addresses our objectives, the PanSurg Collaborative at Imperial College London has developed a unique data pipeline based on a web crawler extraction methodology. This data pipeline uses a novel curation methodology that adopts a human-in-the-loop approach for the characterization of quality, relevance, and key evidence across a range of scientific literature sources. RESULTS: REDASA (Realtime Data Synthesis and Analysis) is now one of the world's largest and most up-to-date sources of COVID-19-related evidence; it consists of 104,000 documents. By capturing curators' critical appraisal methodologies through the discrete labeling and rating of information, REDASA rapidly developed a foundational, pooled, data science data set of over 1400 articles in under 2 weeks. These articles provide COVID-19-related information and represent around 10% of all papers about COVID-19. CONCLUSIONS: This data set can act as ground truth for the future implementation of a live, automated systematic review. The three benefits of REDASA's design are as follows: (1) it adopts a user-friendly, human-in-the-loop methodology by embedding an efficient, user-friendly curation platform into a natural language processing search engine; (2) it provides a curated data set in the JavaScript Object Notation format for experienced academic reviewers' critical appraisal choices and decision-making methodologies; and (3) due to the wide scope and depth of its web crawling method, REDASA has already captured one of the world's largest COVID-19-related data corpora for searches and curation.

Xpert MRSA screening in surgical patient flow; time for a rethink for hub-and-spoke laboratory models?

The move towards pathology networks and hub-and-spoke models of medical laboratory service provision has significantly changed the flow of samples, and the impact of results on patients, over recent years. At the same time advances in technology, including rapid, simple to use molecular platforms, are changing the way microbiology results can be utilized. Like many other medical microbiology laboratories, we struggle with this balance for many different sample types and test requests. Work published by Neilson et al. in Journal of Medical Microbiology last year looked at this balance for methicillin-resistant Staphylococcus aureus (MRSA) genotypic diagnostics and suggested significant cost savings when a whole-healthcare economy perspective was adopted. However, as with all changes, implementing MRSA molecular diagnostics in different clinical settings must be considered carefully. We add to this discussion in our accompanying letter, detailing our experience (in a hub-and-spoke medical microbiology laboratory setting) of 'rapid' MRSA molecular diagnostics for day-case surgery where pre-operative assessment had been missed, exploring the impact and costs of these tests. We find no impact on patient care, but at considerable additional cost. We hope this will add a cautionary note to those considering implementing molecular microbiology diagnostics, and reopen the debate on where, in hub-and-spoke laboratory models, such devices should be situated.