Measuring Signs of Atopic Dermatitis in Clinical Practice
Bibliographic record
Abstract
Importance: Outcome measurement is an essential component of value-based health care and can aid patient care, quality improvement, and clinical effectiveness evidence generation. The Harmonising Outcome Measures for Eczema Clinical Practice initiative aims to identify a list of validated, feasible, outcome measurement instruments recommended to measure atopic dermatitis (AD) in the clinical practice setting. The clinical practice set is a list of instruments that clinicians can pick and choose from to suit their needs in the context of clinical care. Objective: To recommend instruments to measure clinical signs of AD in clinical practice. Evidence Review: Following the predefined roadmap, a mixed methods design was implemented and incorporated systematic reviews and qualitative consensus methods. Previous systematic reviews identified few clinical signs instruments with sufficient validation for recommendation. An updated systematic review evaluating the validity of clinical signs instruments informed an international meeting to reach consensus on recommended instruments to measure AD clinical signs in clinical practice. Consensus was defined as less than 30% disagreement. An in-person consensus exercise was held in Montreal, Canada, on October 16, 2022. The 34 attendees included patient and patient advocate research partners, health care professionals, researchers, methodologists, and industry representatives. Findings: The updated systematic review found that the Eczema Area and Severity Index (EASI), Scoring Atopic Dermatitis, and objective Scoring Atopic Dermatitis were the only instruments that demonstrated sufficient performance in all assessed measurement properties. The modified EASI and Signs Global Assessment × Body Surface Area instruments were also recommended. The EASI, Validated Investigator Global Assessment, and Investigator's Global Assessment multiplied by or measured concurrently with a body surface area measure achieved consensus in criteria and were adopted. Conclusions and Relevance: This consensus statement by the Harmonising Outcome Measures for Eczema initiative suggests that when assessing and documenting clinical signs of AD, there are several valid and feasible instruments that can best fit a clinician's specific practice needs. These instruments should improve and standardize the documentation of signs severity, help determine the effect of treatment, facilitate the generation of clinical effectiveness evidence, and enhance the implementation of value-based health care.
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.
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 | 0.099 | 0.406 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.003 |
| Bibliometrics | 0.007 | 0.011 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.009 | 0.008 |
| Open science | 0.003 | 0.005 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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".