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Hoy — Abril 19th 2024Tus fuentes RSS

The role of orthobiologics in chronic wound healing

Abstract

Chronic wounds, characterized by prolonged healing processes, pose a significant medical challenge with multifaceted aetiologies, including local and systemic factors. Here, it explores the complex pathogenesis of chronic wounds, emphasizing the disruption in the normal phases of wound healing, particularly the inflammatory phase, leading to an imbalance in extracellular matrix (ECM) dynamics and persistent inflammation. Senescent cell populations further contribute to impaired wound healing in chronic lesions. Traditional medical management focuses on addressing underlying causes, but many chronic wounds resist to conventional treatments, necessitating innovative approaches. Recent attention has turned to autologous orthobiologics, such as platelet-rich plasma (PRP), platelet-rich fibrin (PRF) and mesenchymal stem cells (MSCs), as potential regenerative interventions. These biologically derived materials, including bone marrow aspirate/concentrate (BMA/BMAC) and adipose tissue-derived stem cells (ADSCs), exhibit promising cytokine content and regenerative potential. MSCs, in particular, have emerged as key players in wound healing, influencing inflammation and promoting tissue regeneration. This paper reviews relevant scientific literature regarding basic science and brings real-world evidence regarding the use of orthobiologics in the treatment of chronic wounds, irrespective of aetiology. The discussion highlights the regenerative properties of PRP, PRF, BMA, BMAC and SVF, showcasing their potential to enhance wound healing. Despite advancements, further research is essential to elucidate the specific roles of each orthobiologic and determine optimal applications for different wound types. The conclusion underscores the evolving landscape in chronic wound management, with a call for more comprehensive studies to refine treatment strategies and maximize the benefits of regenerative medicine.

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Exploring the terminological validity of ‘chronic pain’ nursing diagnosis: A retrospective descriptive study using nursing diaries

Abstract

Aim

The aim of this study is to generate empirical evidence, drawing from clinical records, with the goal of elevating the level of evidence supporting the nursing diagnosis (ND) of ‘chronic pain’.

Background

Chronic pain is a prevalent condition that affects all age groups. Patients often feel disbelieved about their pain perception, leading to adverse psychological effects, difficulty accessing healthcare and poor rehabilitation outcomes.

Design

Retrospective descriptive study. Standards for Reporting Diagnostic Accuracy Studies guidelines were followed in this study.

Methods

Data were extracted from Electronic Health Records (EHR) of patients admitted to the University Hospital of Perugia, Italy, between March 2016 and December 2022. The study sample comprised individuals without a specific medical diagnosis or high-risk population. Out of 1,048,565 EHR, 43,341 clinical-nursing diaries with the keyword ‘pain’ were identified, from which 283 clinical-nursing notes were selected based on a keyword-based retrieval technique and diagnostic definition for further analysis.

Results

Our study findings support the diagnostic descriptors of the ‘chronic pain’ ND in clinical-nursing diaries. We observed the presence of 9 out of 11 defining characteristics, 7 out of 10 related factors, 4 out of 8 at-risk populations and 11 out of 17 associated conditions.

Conclusions

The study validated diagnostic criteria for chronic pain and proposed ‘haematological pathology’ as a new associated condition. The findings were presented to the Diagnosis Development Committee of NANDA-International for further review. However, limitations of the study prompted the need for further analysis using natural language processing and artificial neural network techniques. As a result, a new research direction using artificial intelligence (AI) tools was initiated.

Relevance to Clinical Practice

The study validates diagnostic descriptors for chronic pain and proposes future directions in semantic analysis and AI tools, aiming to enhance clinical practice and decision-making in nursing care.

Patient or Public Contribution

No patient or public contribution.

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