The use of ultrasonography in the diagnosis of nail disease among patients with psoriasis and psoriatic arthritis: a systematic review
Bibliographic record
Abstract
BACKGROUND: Nail involvement has been described as a key clinical feature for both psoriasis (PsO) and psoriatic arthritis (PsA) and is an important risk factor in PsA. Thus, early diagnosis of nail involvement may be essential for better management of PsO and PsA. Ultrasonography is considered a highly promising method to visualize nail disease. The main aim of this review was to evaluate the use of ultrasonography for the diagnosis of nail disease in patients with PsO and PsA by reviewing ultrasound parameters with the best diagnostic accuracy. Main body of the abstract: A systematic search was performed in MEDLINE via the PubMed and LILACS databases. Conference proceedings of relevant rheumatology scientific meetings were also screened. RESULTS: After applying eligibility criteria, only 13 articles and 5 abstracts were included in this review. The selected studies showed a huge variability in evaluation methods (and therefore in the results) and were mainly focused on the assessment of nails ultrasound parameters that may differ among patients and healthy controls, especially the morphological aspects in B-mode ultrasonography and vascularization of the nail bed by Doppler ultrasonography. Our research indicated that the evaluation of nail disease in PsO and PsA is still underrepresented in the literature, probably reflecting a restricted use in clinical practice, despite the widespread use of ultrasonography in the management of chronic arthritis. SHORT CONCLUSIONS: Despite the potential relevance of ultrasonography for the diagnosis of nail disease, additional studies are needed to determine which features are more reliable and clinically pertinent to ensure accuracy in the evaluation of nail involvement in PsO and PsA.
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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 | 0.005 | 0.035 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.006 | 0.005 |
| Bibliometrics | 0.009 | 0.010 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| 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".