A concept for integrated care pathways for atopic dermatitis—A GA2LEN ADCARE initiative
Bibliographic record
Abstract
The integrated care pathways for atopic dermatitis (AD-ICPs) aim to bridge the gap between existing AD treatment evidence-based guidelines and expert opinion based on daily practice by offering a structured multidisciplinary plan for patient management of AD. ICPs have the potential to enhance guideline recommendations by combining interventions and aspects from different guidelines, integrating quality assurance, and describing co-ordination of care. Most importantly, patients can enter the ICPs at any level depending on AD severity, resources available in their country, and economic factors such as differences in insurance reimbursement systems.The GA2 LEN ADCARE network and partners as well as all stakeholders, abbreviated as the AD-ICPs working group, were involved in the discussion and preparation of the AD ICPs during a series of subgroup workshops and meetings in years 2020 and 2021, after which the document was circulated within all GAL2 EN ADCARE centres.The AD-ICPs outline the diagnostic procedures, possible co-morbidities, different available treatment options including differential approaches for the pediatric population, and the role of the pharmacists and other stakeholders, as well as remaining unmet needs in the management of AD.The AD-ICPs provide a multidisciplinary plan for improved diagnosis, treatment, and patient feedback in AD management, as well as addressing critical unmet needs, including improved access to care, training specialists, implementation of educational programs, assessment on the impact of climate change, and fostering a personalised treatment approach. By focusing on these key areas, the initiative aims to pave the way for a brighter future in the management of AD.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.022 | 0.015 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.004 |
| Scholarly communication | 0.010 | 0.008 |
| Open science | 0.003 | 0.015 |
| Research integrity | 0.005 | 0.007 |
| Insufficient payload (model declined to judge) | 0.006 | 0.002 |
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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".