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Enregistrement W4405042293 · doi:10.33137/cpoj.v7i2.43716

WOUND MANAGEMENT, HEALING, AND EARLY PROSTHETIC REHABILITATION: PART 2 - A SCOPING REVIEW OF PHYSICAL BIOMARKERS

2024· review· en· W4405042293 sur OpenAlexvenueaboutno aff
Hannnelore Williams-Reid, Anton Johannesson, Arjan Buis

Notice bibliographique

RevueCanadian Prosthetics & Orthotics Journal · 2024
Typereview
Langueen
DomaineEngineering
ThématiqueProsthetics and Rehabilitation Robotics
Établissements canadiensnon disponible
Organismes subventionnairesnon disponible
Mots-clésRehabilitationMedicineWound healingPhysical therapyIntensive care medicineSurgery

Résumé

récupéré en direct d'OpenAlex

BACKGROUND: The timely provision of load-bearing prostheses significantly reduces healthcare costs and lowers post-amputation mortality risk. However, current methods for assessing residuum health remain subjective, underscoring the need for standardized, evidence-based approaches incorporating physical biomarkers to evaluate residual limb healing and determine readiness for prosthetic rehabilitation. OBJECTIVE(S): This review aimed to identify predictive, diagnostic, and indicative physical biomarkers of healing of the tissues and structures found in the residual limbs of adults with amputation. METHODOLOGY: A scoping review was conducted following Joanna Briggs Institute (JBI) and PRISMA-ScR guidance. Searches using “biomarkers”, “wound healing”, and “amputation” were performed on May 6, 2023, on Web of Science, Ovid MEDLINE, Ovid Embase, Scopus, Cochrane, PubMed, and CINAHL databases. Inclusion criteria were: 1) References to physical biomarkers and healing; 2) Residuum tissue healing; 3) Clear methodology with ethical approval; 4) Published from 2017 onwards. Articles were assessed for quality (QualSyst tool) and evidence level (JBI system), and categorized by study, wound, and model type. Physical biomarkers that were repeated not just within categories, but across more than one of the study categories were reported on. FINDINGS: The search strategy identified 3,306 sources, 157 of which met the inclusion criteria. Histology was the most frequently repeated physical biomarker used in 64 sources, offering crucial diagnostic insights into cellular healing processes. Additional repeated indicative and predictive physical biomarkers, including ankle-brachial index, oxygenation measures, perfusion, and blood pulse and pressure measurements, were reported in 25, 19, 13, and 12 sources, respectively, providing valuable data on tissue oxygenation and vascular health. CONCLUSION: Ultimately, adopting a multifaceted approach that integrates a diverse array of physical biomarkers (accounting for physiological factors and comorbidities known to influence healing) may substantially enhance our understanding of the healing process and inform the development of effective rehabilitation strategies for individuals undergoing amputation. Layman's Abstract Providing prosthetic limbs soon after amputation reduces healthcare costs and lowers mortality risk. However, current methods for evaluating the health of the remaining limb often rely on subjective judgment, highlighting the need for a standardized, evidence-based approach using physical biomarkers to assess healing and readiness for prosthetics. This review aimed to identify physical biomarkers that can predict, diagnose, or indicate healing in amputated limbs. On May 6, 2023, a comprehensive review was conducted across multiple databases, including Web of Science, Ovid MEDLINE, Ovid Embase, Scopus, Cochrane, PubMed, and CINAHL, to find studies using search terms like “biomarkers”, “wound healing”, and “amputation”. To be included, studies had to focus on biomarkers related to healing in residual limbs, use clear research methods, have ethical approval, and be published after 2017. The quality of the studies was evaluated, and biomarkers found across multiple studies were reported. Of 3,306 sources identified, 157 focused on physical biomarkers, with histology (tissue analysis) being the most commonly reported, allowing healing progress to be diagnosed at the cellular level. Other frequently mentioned biomarkers included the ankle-brachial index and oxygenation measures, which are used to assess tissue oxygen levels and blood flow, therefore predicting or indicating healing. Using a combination of different physical markers (while considering things like overall health and existing medical conditions) can give us a much better understanding of how healing works. This approach can also help create more effective rehabilitation plans for people who have had an amputation. Article PDF Link: https://jps.library.utoronto.ca/index.php/cpoj/article/view/43716/33400 How To Cite: Williams-Reid H, Johannesson A, Buis A. Wound management, healing, and early prosthetic rehabilitation: Part 2 - A scoping review of physical biomarkers. Canadian Prosthetics & Orthotics Journal. 2024; Volume 7, Issue 2, No.3. https://doi.org/10.33137/cpoj.v7i2.43716 Corresponding Author: Professor Arjan Buis, PhDDepartment of Biomedical Engineering, Faculty of Engineering, University of Strathclyde, Glasgow, Scotland.E-Mail: arjan.buis@strath.ac.ukORCID ID: https://orcid.org/0000-0003-3947-293X

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 distillée sur la base complète

Imitation des enseignants

Ni prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.

score de la tête « metaresearch » (Codex)0,001
score de la tête « metaresearch » (Gemma)0,000
Version: codex-gemma-dda1882f352aStatut de validation: machine_predicted_unvalidated
Catégories candidatesMéta-épidémiologie (sens strict)
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Revue systématique · Signal consensuel: Revue systématique
GenreSignal candidat: Synthèse · Signal consensuel: Synthèse
Score de désaccord entre enseignants0,443
Score d'incertitude au seuil1,000

Scores Codex et Gemma par catégorie

CatégorieCodexGemma
Métarecherche0,0010,000
Méta-épidémiologie (sens strict)0,0010,001
Méta-épidémiologie (sens large)0,0020,001
Bibliométrie0,0010,001
Études des sciences et des technologies0,0000,000
Communication savante0,0000,000
Science ouverte0,0000,000
Intégrité de la recherche0,0000,001
Charge utile insuffisante (le modèle a refusé de juger)0,0000,000

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.

Tête enseignante Opus0,017
Tête enseignante GPT0,297
Écart entre enseignants0,280 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_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 découle

Classification

machine, non validée

Prédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.

Devis d'étudeRevue systématique
Domainenon disponible
GenreSynthèse

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations1
Publié2024
Routes d'admission2
Résumé présentoui

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