Developing an aid for virtual clinics for education and identification of lipohypertrophy during the Covid-19 pandemic: Diabetesclinic@ home

Aims/objectives: To develop an app to support virtual diabetes clinics to help people with diabetes to check themselves for lipos and to discuss what they found during the virtual consultation. Method(s): Collaborative project between clinical teams and medical illustrators in Swansea Bay University Health Board, academics in Swansea University and Eli Lilly under a Collaborative Working Agreement. The teams worked together to develop the content, animations, and a learning technologist developed progressive web app (PWA). The app was tested by diabetes patient groups in Wales, as well as HCP groups, Welsh Academy for Nurses in Diabetes (WAND) and Diabetes Specialist Nurses (DSN) forum prior to launch in June 2021. Result(s): Between 28th June 2021 and 11th November 2022 the app had 827 unique users and 124 returning users. Users came from 15 different countries including UK, Australia, USA, Germany, Brazil and Saudi Arabia. The proportion of UK users were 480 (60%) England, 265 (34%) Wales, and 19 (2%) Scotland. A total of 41 users completed the feedback form;of those 11 (27%) did not know about lipos prior to using the app, 11 (27%) found a lipo using the app, 14 (34%) said they made changes to injection technique after using the app and 37 (90%) said their knowledge of lipos increased following using the app. Conclusion(s): A PWA can help to aid virtual clinics an provide education for people with diabetes. The diabetesclinic@ home app improved knowledge and detection of lipos and improved injection technique.

Determinants of turnaround time in a rapid genome sequencing program

Previous studies of genome sequencing (GS) in critically ill childrenhave made use of either modified hardware or working procedureswhich would be difficult, if not impossible, to integrate into existingclinical workflows1. Our lab’s transition from exome sequencing (ES) to GS offered an opportunity to implement in-house rapid genomesequencing (rGS) in critically ill children in a manner which couldintegrate with existing clinical workflows. We conducted a feasibilityand implementation pilot by offering rGS to child-parent triosconcurrently undergoing clinical rapid ES (rES) via a reference lab.The purpose of this study was to identify and address operationalbarriers to implementation of a rGS program capable of communicatinga preliminary result within 7 days of consent. We consideredthis time span to be more reflective of clinical realities than lab-quotedturnaround times (TAT) which typically start at sample receipt andthus do not account for challenges in sample acquisition and pre-testcounseling in a critical care setting, nor the impact of shipping times.Here we present data on TAT and lessons learned from the first 27subjects enrolled.Using rapid cycle improvement methodologies, we identified fourdistinct but inter-related workflows requiring optimization:1. Pre-analytic: patient identification through acquisition ofsamples2. Wet-lab: extraction through sequencing3. Bioinformatics: secondary and tertiary analysis as well as rapididentification of causal variants4. Return of resultsFigure 1 summarizes TAT across cases, demonstrating the markedimprovements in TAT with our programmatic approach to improvement.We used our first 9 cases to determine a baseline TAT for theentire process and to delineate the 4 main workflows (above). Atbaseline, excluding cases delayed by COVID-19 restrictions, mean TATwas 17.12 days (3 sequential deviant range: 7.05–27.19 days).Following deployment of our programmatic approach to rGS, meanTAT fell to 6.19 days (3 sequential deviant range: 0.51–11.87 days).Table 1 summarizes the observations and insights, by workflow, whichimpacted upon TAT and/or implementation. The single biggest impacton TAT was optimization of bioinformatics by removing all manualsteps between starting sequencing and producing human interpretable,filtered, annotated output of high-priority variants for interpretation.The second biggest source of improvement was optimization ofthe sequencing itself as well as prioritizing sample processing for andaccess to sequencing runs. While variant ranking is helpful in identifying causal variants, in 9/10 cases with a diagnostic findingthe causal variant(s)were obvious to the study teamwithin minutes ofviewing the annotated variant list, regardless of variant rank. (Figure Presented) As time required for sequencing and analytic workflows fell, therelative contribution of other workflows to overall TAT shifted and itbecame more obvious that early identification and utilization of thisapproach is very important in lowering overall time to diagnosis(Figure 2). In 6/10 cases with a diagnostic finding, the initial approachof the clinical team was NOT rES (and thus patients were not eligiblefor rGS on a research basis). Had rGS been the initial diagnosticmodality chosen, a diagnosis could have been reached in a median 12days sooner (range 2–28 days). There were also several cases wheresequencing was delayed when one or both parents did not present tothe lab to provide a blood sample in a timely manner. Optimization ofsequencing or analytic workflows cannot meaningfully improveoutcomes either of these situations.Our findings suggest some important considerations for institutionsdeveloping or seeking to improve rapid sequencing programs for acuteand critically ill children: (Table Presented) • Optimization of computational resource utilization and phenotypecuration saves more time than improved variant filtering orprioritization.• Obtaining samples from parents is non-trivial.• Even trained geneticists may fail to recognize appropriatecandidates for rGS.

Guidelines for the management of diabetes services and patients during the COVID-19 pandemic.

The UK National Diabetes Inpatient COVID Response Group was formed at the end of March 2020 to support the provision of diabetes inpatient care during the COVID pandemic. It was formed in response to two emerging needs. First to ensure that basic diabetes services are secured and maintained at a time when there was a call for re-deployment to support the need for general medical expertise across secondary care services. The second was to provide simple safe diabetes guidelines for use by specialists and non-specialists treating inpatients with or suspected of COVID-19 infection. To date the group, comprising UK-based specialists in diabetes, pharmacy and psychology, have produced two sets of guidelines which will be continually revised as new evidence emerges. It is supported by Diabetes UK, the Association of British Clinical Diabetologists and NHS England.