POS0887 INFLUENCE OF CONTEXTUAL FACTORS AND RELIABILITY OF ULTRASOUND SKIN MEASURES IN PERSONS WITH SYSTEMIC SCLEROSIS AND HEALTHY CONTROLS
Bibliographic record
Abstract
Background Skin involvement is a cardinal feature for the diagnosis and prognosis of systemic sclerosis (SSc) and is associated with worse functional ability and quality of life.[1] Gender and age have been found to influence ultrasound dermal thickness and skin stiffness, and preliminary normal reference percentile curves for these ultrasound measures have been proposed.[2] The possibility that contextual factors, like room temperature, may influence these measurement is of crucial importance, but it has been very scarcely addressed.[3] Objectives To examine the influence of contextual factors upon the evaluation of skin thickness and stiffness by ultrasound and to assess the reliability of these parameters. Methods Ultrasound dermal thickness (by B-mode, 18MHz) and skin stiffness (by shear-wave elastography, 9MHz) were assessed in persons with systemic sclerosis (SSc) and in healthy controls. The influence of contextual factors upon repeated measures was evaluated: (i) room temperature (16-17ºC vs 22-24ºC); (ii) time of day (morning vs afternoon), and (iii) menstrual cycle phase (menstrual vs ovulatory). Differences were analyzed using the related-samples Wilcoxon signed-rank test. Inter- and intra-rater reliability of ultrasound skin thickness and stiffness were evaluated in the 17 skin Rodnan sites of 20 persons with SSc and 20 healthy controls, under stable contextual conditions. Results A significant increase in dermal thickness values was observed between the morning and afternoon evaluations, at the leg 6.96% (SD3.39), p=0.007, and 7.39% (8.42), p=0.018, in SSc patients and in controls, respectively (Table 1).No significant changes were observed in association with room temperature and menstrual cycle. Intra- and inter-rater-reliability was good to excellent for ultrasound dermal thickness and stiffness, both in SSc and healthy controls. Conclusion The timing of the ultrasound procedure within each day seems to influence the ultrasound measures at the legs and feet, and this aspect should deserve attention when designing and reporting future trials. Our study corroborates that ultrasound dermal thickness and skin stiffness are reliable domains to quantify skin involvement in SSc. References [1]doi:10.1093/rheumatology/kep108; [2]doi:10.1136/rmdopen-2022-002577; [3]doi:10.1016/j.semarthrit.2022.151954 Acknowledgements: NIL. Disclosure of Interests None Declared.
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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 | 0.001 | 0.003 |
| 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 | 0.001 | 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".