Living evidence syntheses for long COVID therapeutics: combining rigorous protocols to build efficiency while...

Given the rapidly changing evidence, the creation and maintenance of a living systematic review database of therapeutics for long COVID is an ideal and necessary approach considering the rapidly changing evidence that continues to be identified. This paper describes methods and results of a collaboration between three teams who produced a living literature review on long COVID therapeutics-Australian Living Evidence Collaboration (ALEC), Bond University, and Epistemonikos COVID-19 L.OVE (Living Overview of Evidence) database.

We took a collaborative and iterative approach to analyse the commonalities and differences between each project and develop an agreed comprehensive, collective approach. A plan for ongoing (monthly) updates and dissemination was built.

Despite minor differences, there was also a clear alignment of goals between the three teams. Differences in search strategy, search methods and screening criteria were identified, investigated, and resolved. A comparison of overlaps helped establish a common collaborative approach. A combined library of 218 randomised controlled trials and 56 systematic reviews was created which led to the optimised search strategy. The combined 218 RCT library covered 20 different treatment categories of which 14 were pharmacological and 6 were non-pharmacological. Further refinements and collaborations led to a transformed initial database library of 102 randomised controlled trials as of June 2024 before the team commenced monthly updates.

Despite initial differences, a comprehensive search strategy based on the collaboration of the three teams was developed. Ongoing monthly updates were initiated and are now planned for well into the future to make continual and rapid updates to the library of evidence surrounding therapeutics for long COVID. Where global public health is concerned, it is valuable to review and refine processes in the early stages, so that they can be reliable. We recommend open collaboration to achieve the goal of creating accessible, efficient, and reliable evidence syntheses.