Divergence of Demographic Factors Associated with Clinical Severity Compared with Quality of Life Impact in Acne
Bibliographic record
Abstract
BACKGROUND: Previous smaller studies suggest that age, gender, and duration of acne may individually be associated with clinical acne severity and quality of life (QoL) impact. OBJECTIVE: Our purpose was to concurrently evaluate the association of demographic factors with clinical acne severity and with QoL impact. METHODS: Clinical acne severity was assessed using the Investigators Global Assessment, whereas QoL impact was evaluated by the patient-completed Acne-QoL. These outcomes were correlated with sociodemographic variables, including age, gender, and duration of acne. RESULTS: In 862 acne patients, clinical severity was associated with younger age, male gender, and shorter acne duration (1-5 years). In contrast, greater impact on QoL was associated with older age, female gender, and longer acne duration (> 5 years). CONCLUSIONS: Clinical and QoL measures each differentiate between groups of patients most severely affected by acne. Our findings reinforce the imperative for clinicians to use both measures for comprehensive patient management. LIMITATIONS: Study limitations include referral population of acne patients and the restriction of outcome measures to facial acne.
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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 | 0.002 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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) | 0.003 | 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 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".