Mapping the Effect of Psoriatic Arthritis Using the International Classification of Functioning, Disability and Health
Bibliographic record
Abstract
OBJECTIVE: The effect of a disease can be categorized by a standardized reference system: the International Classification of Functioning, Disability and Health (ICF). The objective was to map the effect of psoriatic arthritis (PsA) from the patient's perspective to the ICF. METHODS: A systematic literature review was performed. Qualitative publications reporting domains of impact important for patients with PsA were identified using the following terms: ("psoriatic arthritis") AND ("quality of life" OR "impact"). Meaningful concepts were extracted from the publications, grouped into domains and linked to the ICF categories. The number of concepts linked to each ICF category and to each ICF level was calculated. The number of concepts not linkable was also calculated. RESULTS: Eleven studies (13 articles) were included in the analysis. Twenty-five domains of impact were cited, of which the ability to work/volunteer and social participation were the most cited (both by 10 studies). In total, 258 concepts were identified, of which 217 could be linked to 136 different ICF categories; 41 concepts, mostly personal factors, could not be precisely linked. The most represented ICF component was activities and participation (42.6%) rather than body structures (10.3%) or body functions (29.4%). Ten studies (90.9%) reported impairments in the ability to work/volunteer and social participation, and 7 (63.6%) reported leisure activities, family and intimacy, pain, skin problems, and body image. CONCLUSION: PsA widely affects all aspects of patients' lives, in particular aspects related to activities and participation. The ICF is a useful approach for the classification of disease effect.
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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 | 0.028 | 0.084 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.006 |
| Bibliometrics | 0.042 | 0.027 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".