The Personalised Acne Care Pathway—Recommendations to guide longitudinal management from the Personalising Acne: Consensus of Experts
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: Acne is a chronic disease with a varying presentation that requires long-term management. Despite this, the clinical guidelines for acne offer limited guidance to facilitate personalized or longitudinal management of patients. OBJECTIVES: To generate recommendations to support comprehensive, personalized, long-term patient management that address all presentations of acne and its current and potential future burden. METHODS: The Personalising Acne: Consensus of Experts panel consisted of 13 dermatologists who used a modified Delphi approach to reach consensus on statements related to longitudinal acne management. The consensus was defined as ≥75% voting "agree" or "strongly agree." All voting was electronic and blinded. RESULTS: Key management domains, consisting of distinct considerations, points to discuss with patients, and "pivot points" were identified and incorporated into the Personalised Acne Care Pathway. Long-term treatment goals and expectations and risk of (or fears about) sequelae are highlighted as particularly important to discuss frequently with patients. LIMITATIONS: Recommendations are based on expert opinion, which could potentially differ from patients' perspectives. Regional variations in health care systems may not have been captured. CONCLUSIONS: The Personalised Acne Care Pathway provides practical recommendations to facilitate the longitudinal management of acne, which can be used by health care professionals to optimize and personalize care throughout the patient journey.
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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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