Objective: Regular retrospective analysis is necessary for potential improvement in clinical practice for the treatment of hard-to-heal wounds. Comorbidities and outcomes have demonstrated spatial and temporal diversity, emphasising the importance of updates in epidemiology. The complexity of healing hard-to-heal wounds has long been known, and so we sought evidence-based improvement on the current principles of treatment.
Method: Demographic and clinical information of patients from the WoundCareLog database was collected. Patients who met the inclusion criteria and completed follow-up after treatment were included. Comorbidities were diagnosed and classified into eight categories based on ICD-10. We compared the demographic and aetiological characteristics between patients with and without comorbidities by t-test and Chi-squared test. The impact of comorbidities on wound healing were evaluated with a multivariate Cox model.
Results: A total of 2163 patients met the inclusion criteria and were enrolled, of whom 37.0% were aged 61-80 years, 36.0% were aged 41-60 years and 60.8% were male. The lower extremities and buttocks were the most commonly affected areas with hard-to-heal wounds. Non-traumatic wounds accounted for 66.6% of cases, and infection, pressure and diabetes were the most common causes. Paralysis and diabetes were the most important factors which led to a prolonged healing process and inferior clinical outcomes.
Conclusion: Comorbidities of hard-to-heal wounds were treated as separate contributors and their weighted effect on outcome was calculated through correlation analysis. Paralysis and diabetes were the most unfavourable comorbidities affecting the treatment of non-traumatic hard-to-heal wounds. Our study highlighted the priority of comorbidity treatment through data-driven approaches. It provides potential value in developing better public health strategies and preventive medicine.
Download full-text PDF |
Source |
---|---|
http://dx.doi.org/10.12968/jowc.2022.31.Sup10.S7 | DOI Listing |
Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!