Advances in skin & wound care · 2011
Improving the detection of pressure ulcers using the TMI ImageMed system.
Сравнительное исследованиеСтатьяПоддержка исследования: вне правительства СШАНазвание и аннотация: Перевод в очереди
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Judy David, Brooks Brian, Fennie Kristopher, Lyder Courtney, Burton Claude
Аннотация
OBJECTIVE: The aim of the study was to evaluate a novel infrared imaging device coupled with an intelligent software interface that may provide a more objective means of identifying anatomical sites at risk for pressure ulcer (PrU) development as compared with the Braden Scale for Predicting Pressure Sore Risk.
DESIGN: Repeated-measures design.
SETTING: Duke University Medical Center.
PARTICIPANTS: One hundred patients admitted to a medical unit at risk for PrUs.
MAIN RESULTS: Only 5 participants developed early stage PrUs (Stages I and II). However, the infrared imaging device not only predicted all 5 participants to be at risk, but also predicted the anatomical location where the ulcer would develop. The Braden Scale correctly identified 3 of 5 participants who developed PrUs. It was also determined that a temperature variance of 1.5° C was able to accurately predict PrU development.
CONCLUSION: Infrared imaging using intelligent software may become a promising, objective method for identifying incipient PrUs and provide clinicians with specific anatomical locations for increased preventive interventions.
DESIGN: Repeated-measures design.
SETTING: Duke University Medical Center.
PARTICIPANTS: One hundred patients admitted to a medical unit at risk for PrUs.
MAIN RESULTS: Only 5 participants developed early stage PrUs (Stages I and II). However, the infrared imaging device not only predicted all 5 participants to be at risk, but also predicted the anatomical location where the ulcer would develop. The Braden Scale correctly identified 3 of 5 participants who developed PrUs. It was also determined that a temperature variance of 1.5° C was able to accurately predict PrU development.
CONCLUSION: Infrared imaging using intelligent software may become a promising, objective method for identifying incipient PrUs and provide clinicians with specific anatomical locations for increased preventive interventions.