Ultrasound measurement of traumatic scar and skin thickness: a scoping review of evidence across the translational pipeline of research-to-practice
Bibliographic record
Abstract
OBJECTIVES: To identify the ultrasound methods used in the literature to measure traumatic scar thickness, and map gaps in the translation of these methods using evidence across the research-to-practice pipeline. DESIGN: Scoping review. DATA SOURCES: Electronic database searches of Ovid MEDLINE, Embase, Cumulative Index of Nursing and Allied Health Literature and Web of Science. Grey literature searches were conducted in Google. Searches were conducted from inception (date last searched 27 May 2022). DATA EXTRACTION: Records using brightness mode (B-mode) ultrasound to measure scar and skin thickness across the research-to-practice pipeline of evidence were included. Data were extracted from included records pertaining to: methods used; reliability and measurement error; clinical, health service, implementation and feasibility outcomes; factors influencing measurement methods; strengths and limitations; and use of measurement guidelines and/or frameworks. RESULTS: Of the 9309 records identified, 118 were analysed (n=82 articles, n=36 abstracts) encompassing 5213 participants. Reporting of methods used was poor. B-mode, including high-frequency (ie, >20 MHz) ultrasound was the most common type of ultrasound used (n=72 records; 61% of records), and measurement of the combined epidermal and dermal thickness (n=28; 24%) was more commonly measured than the epidermis or dermis alone (n=7, 6%). Reliability of ultrasound measurement was poorly reported (n=14; 12%). The scar characteristics most commonly reported to be measured were epidermal oedema, dermal fibrosis and hair follicle density. Most records analysed (n=115; 97%) pertained to the early stages of the research-to-practice pipeline, as part of research initiatives. CONCLUSIONS: The lack of evaluation of measurement initiatives in routine clinical practice was identified as an evidence gap. Diverse methods used in the literature identified the need for greater standardisation of ultrasound thickness measurements. Findings have been used to develop nine methodological considerations for practitioners to guide methods and reporting.
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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 | 0.058 | 0.261 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.007 | 0.007 |
| Bibliometrics | 0.028 | 0.026 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.008 | 0.009 |
| Open science | 0.004 | 0.004 |
| Research integrity | 0.005 | 0.003 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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".