523 A Survey of Skin Substitute Use Among Burn Surgeons Across the Country
Notice bibliographique
Résumé
Abstract Introduction A plethora of “skin substitutes” exist in burn care with limited comparative analysis trials in the literature. This presents a unique challenge to providers seeking to optimize product selection. We sought to perform a cross-sectional survey of practicing burn surgeons to explore what products being utilized and identify the indications for use. Methods A 14-question survey was distributed to burn surgeons across the country who attended academic meetings. Contributors were actively practicing burn surgeons and identified the skin substitutes they routinely use in practice and completed a separate product-specific survey on each product, covering aspects such as indication, usage frequency, clinical environment, perceived benefits, and practice changes due to lack of porcine xenograft availability. Statistical analysis involved descriptive statistics, Welch two-sample t-tests, and Pearson’s correlation coefficient. Results Contributions were received from 48 surgeons across 39 institutions and 23 US states and Canada in 2022-2023. Over 20 products were reported, On average 4.3 skin substitutes were used per respondent, with no differences between academic and private institutions (p = 0.33) or based on years of practice (r(31) = -0.320, p = 0.069). For neodermal substitutes, a Dermal Regeneration Template (26 respondents) was used for staged full-thickness burns. Polyurethane Foam (PF) (22 respondents), was used similarly and was believed to reduce dressing changes and healing time. Bovine Dermal Scaffold (10 respondents) and Collagen-Elastin Matrix (8 respondents) had mixed feedback. For epidermal substitutes, Polylactic Acid Copolymer (PAC) (20 respondents) was used for middle thickness burns and cited for reduced dressing changes and healing time, whereas Biosynthetic Matrix (BM) (5 respondents) had mixed reviews. Some products were used across multiple indications, including Porcine Lyophilized Extracellular Matrix and Acellularized Human Skin with mixed feedback. Allograft was widely used (28 respondents) for deep partial and full thickness burns. The discontinuation of Porcine xenograft led to increased use of PAC and BM by some respondents. Allograft was preferred for deep partial and mixed thickness burns by most respondents, PF and allograft for full-thickness burns, and PAC for middle thickness burns, cited for expedited wound closure (n=52), decreased pain (n=18) and reduced infection risk (n=13). Conclusions Our data highlights the diversity of skin substitute products available to burn surgeons and the lack of consensus on how to utilize these products. The findings highlight the need for more collaboration and consultation between the larger burn community and industry partners to optimize wound indications for product application. Applicability of Research to Practice Further research using more comprehensive surveys and blinded outcomes data will help surgeons optimize product selection. Funding for the Study N/A
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,001 | 0,005 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,001 | 0,002 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,001 | 0,000 |
| Science ouverte | 0,000 | 0,001 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,004 | 0,001 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».