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wiki:start:demo:covid19 [2022/02/11 01:44] kholub |
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- | ====== Demo Nest: COVID-19 Antivirals ====== | + | ====== Demo Walkthrough: COVID-19 Antivirals ====== |
- | This Nest is a copy of a previously-completed review presenting the evidence regarding the safety and efficacy of anti-virals that had randomized controlled trial (RCT) evidence reported in the treatment of COVID-19 as of January | + | Welcome to the walkthrough of the //COVID-19: Antivirals// |
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+ | This Nest is a copy of a previously-completed review presenting the evidence regarding the safety and efficacy of anti-virals that had randomized controlled trial (RCT) evidence reported in the treatment of COVID-19 as of January | ||
- | In this walkthrough, | ||
===== Nest Home ===== | ===== Nest Home ===== | ||
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Click the " | Click the " | ||
- | {{https://wiki.nested-knowledge.com// | + | {{ :wiki:start:demo:demo1.png? |
==== Tagging Module ==== | ==== Tagging Module ==== | ||
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Inside the Tagging module, tags may be applied to studies, indicating that a concept is relevant to a study. | Inside the Tagging module, tags may be applied to studies, indicating that a concept is relevant to a study. | ||
- | {{https://wiki.nested-knowledge.com// | + | {{:wiki:start:demo:covid19_tagging.png? |
In the Tagging form, select any tag from the dropdown menu, then click Apply Tag; it should now appear in the Tagging Table. | In the Tagging form, select any tag from the dropdown menu, then click Apply Tag; it should now appear in the Tagging Table. | ||
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Study Inspector is the tool in AutoLit for reviewing and searching your past extracted data. Each row in Study Inspector is a study, and columns may be user-selected in the upper left dropdown menu. Studies may be searched into the table by creating Filters. Filters may be created using the Add Filter dropdown menu, but oftentimes the typeahead search bar is fastest. In the below example, we are filtering to studies with a full text uploaded and using the typeahead menu to find all studies tagged with Mortality. Try out the title/ | Study Inspector is the tool in AutoLit for reviewing and searching your past extracted data. Each row in Study Inspector is a study, and columns may be user-selected in the upper left dropdown menu. Studies may be searched into the table by creating Filters. Filters may be created using the Add Filter dropdown menu, but oftentimes the typeahead search bar is fastest. In the below example, we are filtering to studies with a full text uploaded and using the typeahead menu to find all studies tagged with Mortality. Try out the title/ | ||
- | {{https://wiki.nested-knowledge.com// | + | {{:wiki:start:demo:covid19_inspector.png? |
===== Extraction ===== | ===== Extraction ===== | ||
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+ | Please see our [[: | ||
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+ | {{: | ||
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+ | The Study Design form specifies intervention arms in the study (Standard of care and 2 different Remdesivir dosages, in this case) as well as outcome measurement timepoints in the study (0 and 11 days). | ||
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+ | The Extracted Data form contains means, medians, dichotomous rates, and categorical counts corresponding to baseline chararcteristics and outcomes for the study. Modify some of the data points, which will be auto-saved. If you enter incomplete or invalid data (e.g. a negative value for N), the leading Status column of the table will show a red X. Hover to view the error message. | ||
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+ | ===== Synthesis ===== | ||
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+ | At this point, we've reviewed all the evidence gathered in AutoLit for the //COVID-19 Antivirals// | ||
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+ | {{: | ||
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+ | ==== PRISMA ==== | ||
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+ | Click the PRISMA button in the bottom left of the page to view a PRISMA 2020 flow diagram. The diagram is auto-populated based on searches imported and studies screened in AutoLit. | ||
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+ | {{: | ||
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+ | We can see that the 2 searches and 17 (19 - 2 duplicated records already imported in search) expert recommendations are displayed in the diagram. The diagram may be right clicked and saved as an arbtirary resolution SVG or exported in a variety of formats. | ||
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+ | ==== Qualitative Synthesis ==== | ||
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+ | Navigate back to Synthesis Home and click the Qualitative Synthesis box. Qualitative Synthesis (QLS) displays data gathered in the Tagging Module. Each slice in the sunburst diagram is a tag. Its width corresponds to how frequently it was applied. Its distance from the center corresponds to its depth in the hierearchy (how many "is a" relationships are between it and its root tag). Click a slice to filter studies displayed to those where the tag was applied. Clicking multiple slices filters to studies with all the selected tags applied. The rightmost bar shows relevant studies (bottom) and some data about the tag (top), like its frequency, excerpts, and tags that were commonly applied with the selected tag. | ||
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+ | {{: | ||
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+ | In this tag selection, we see that Mortality and Length of Stay were reported as outcomes in 7 of 16 included studies. Click the rows of the study table to take a deep dive into the extracted data. | ||
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+ | ==== Quantitative Synthesis ==== | ||
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+ | Navigate back to Synthesis Home and click the Quantitative Synthesis box. Quantitative Synthesis (QNS) displays data gathered in the Extraction Module. QNS contains 3 different analyses automatically computed from extracted data. | ||
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+ | The Summary tab contains pooled estimates of outcomes, broken out by interventions. Interventions may be expanded to different levels of precision, while outcomes analyzed may be selected from the dropdown menus. In the below example, we find a 7.3% mortality rate among all antivirals, against an 11.6% mortality rate for control/ | ||
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+ | {{: | ||
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+ | The NMA tab computes a Network Meta-Analysis, | ||
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+ | {{: | ||
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+ | ===== Closing Remarks ===== | ||
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+ | You've now seen how a review may be completed & shared with the Nested Knowledge platform. We encourage you to head back to AutoLit and explore the variety of configuration options, and ever-growing feature set we didn't get to cover here. If you're feeling ambitious, start your own Nest from scratch! | ||
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+ | Use this documentation to guide you through more complex topics, and as always, please reach out to our support team via email and make requests on [[https:// | ||