Open AccessImproved detection of clinically relevant wound bacteria using autofluorescence image‐guided sampling in diabetic foot ulcers
Author(s) -
OttolinoPerry Kathryn,
Chamma Emilie,
Blackmore Kristina M,
LindvereTeene Liis,
Starr Danielle,
Tapang Kim,
Rosen Cheryl F,
Pitcher Bethany,
Panzarella Tony,
Linden Ron,
DaCosta Ralph S
Publication year - 2017
Publication title -
international wound journal
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.867
H-Index - 63
eISSN - 1742-481X
pISSN - 1742-4801
DOI - 10.1111/iwj.12717
Subject(s) - medicine , debridement (dental) , diabetic foot , sampling (signal processing) , autofluorescence , pathology , surgery , diabetes mellitus , physics , filter (signal processing) , quantum mechanics , fluorescence , computer science , computer vision , endocrinology
Clinical wound assessment involves microbiological swabbing of wounds to identify and quantify bacterial species, and to determine microbial susceptibility to antibiotics. The Levine swabbing technique may be suboptimal because it samples only the wound bed, missing other diagnostically relevant areas of the wound, which may contain clinically significant bacteria. Thus, there is a clinical need to improve the reliability of microbiological wound sampling. To address this, a handheld portable autofluorescence ( AF ) imaging device that detects bacteria in real time, without contrast agents, was developed. Here, we report the results of a clinical study evaluating the use of real‐time AF imaging to visualise bacteria in and around the wound bed and to guide swabbing during the clinical assessment of diabetic foot ulcers, compared with the Levine technique. We investigated 33 diabetic foot ulcers ( n = 31 patients) and found that AF imaging more accurately identified the presence of moderate and/or heavy bacterial load compared with the Levine technique (accuracy 78% versus 52%, P = 0·048; adjusted diagnostic odds ratio 7·67, P < 0·00022 versus 3·07, P = 0·066) and maximised the effectiveness of bacterial load sampling, with no significant impact on clinical workflow. AF imaging may help clinicians better identify the wound areas with clinically significant bacteria, and maximise sampling of treatment‐relevant pathogens.