mySinusitisCoach: patient empowerment in chronic rhinosinusitis using mobile technology
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
BACKGROUND: The European Position Papers on Rhinosinusitis from 2005, 2007 and 2012 have had a measurable impact on the way this common condition with high impact on quality of life is managed around the world. EPOS2020 will be the latest iteration of the guideline, addressing new stakeholders and target users, presenting a summary of the latest literature and evolving treatment modalities, and formulating clear recommendations based on all available evidence. METHODOLOGY: Based on the AGREE II framework, this article demonstrates how the EPOS2020 steering group will address six key areas to ensure consistency in quality and presentation of information in the latest rhinosinusitis clinical practice guideline: scope and purpose; stakeholder involvement; rigour of development; clarity of presentation; recommendations and applicability; editorial independence. RESULTS: By analysing the guidance from AGREE II, we formulated a detailed development strategy for EPOS2020. We identify new stakeholders and target users and ratify the importance of patient involvement in the latest EPOS guideline. New and expanded areas of research to be addressed are highlighted. We confirm our intention to use mixed methodologies, combining evidence-based medicine with real life studies; when no evidence can be found, use Delphi rounds to achieve clear, inclusive recommendations. We also introduce new concepts for dissemination of the guideline, using Internet and social media to improve accessibility. CONCLUSION: This article is an introduction to the EPOS2020 project, and presents the key goals, core stakeholders, planned methodology and dissemination strategies for the latest version of this influential guideline.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.001 |
| Bibliometrics | 0.003 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it