Petra Jones

Dr. Petra Jones


Research Focus & Metrics

Academic Career Length

10Years (2017-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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1 October 2021 in Gait & Posture
Verified
Journal Article
Closed access
PJPetra Jones
Petra Jones
MCMike Catt
Mike Catt
MDMelanie J. Davies
Melanie J. Davies
CECharlotte L. Edwardson
Charlotte L. Edwardson
EMEvgeny M. Mirkes
Evgeny M. Mirkes
ARAlex V. Rowlands
Alex V. Rowlands

1 April 2020 in Journal of Biomedical Informatics
Verified
Journal Article
Closed access
PJPetra Jones
Petra Jones
MJMatthew K. James
Matthew K. James
MDMelanie J Davies
Melanie J Davies
KKKamlesh Khunti
Kamlesh Khunti
MCMike Catt
Mike Catt
EMEvgeny M. Mirkes
Evgeny M. Mirkes

1 March 2021 in Journal of Diabetes and its Complications
Verified
Journal Article
Closed access
PJPetra Jones
Petra Jones
MDMelanie J. Davies
Melanie J. Davies
KKKamlesh Khunti
Kamlesh Khunti
DFDaniel T.P. Fong
Daniel T.P. Fong
DWDavid Webb
David Webb

9 October 2019 in Journal of Diabetes Science and Technology
Verified
Journal Article
Open access
PDF file
PJPetra Jones
Petra Jones
RBRichard Bibb
Richard Bibb
MDMelanie J Davies
Melanie J Davies
KKKamlesh Khunti
Kamlesh Khunti
MMMatthew McCarthy
Matthew McCarthy
FZFrancesco Zaccardi
Francesco Zaccardi
Background: Accurately predicting the risk of diabetic foot ulceration (DFU) could dramatically reduce the enormous burden of chronic wound management and amputation. Yet, the current prognostic models are unable to precisely predict DFU events. Typically, efforts have focused on individual factors like temperature, pressure, or shear rather than the overall foot microclimate. Methods: A systematic review was conducted by searching PubMed reports with no restrictions on start date covering the literature published until February 20, 2019 using relevant keywords, including temperature, pressure, shear, and relative humidity. We review the use of these variables as predictors of DFU, highlighting gaps in our current understanding and suggesting which specific features should be combined to develop a real-time microclimate prognostic model. Results: The current prognostic models rely either solely on contralateral temperature, pressure, or shear measurement; these parameters, however, rarely reach 50% specificity in relation to DFU. There is also considerable variation in methodological investigation, anatomical sensor configuration, and resting time prior to temperature measurements (5-20 minutes). Few studies have considered relative humidity and mean skin resistance. Conclusion: Very limited evidence supports the use of single clinical parameters in predicting the risk of DFU. We suggest that the microclimate as a whole should be considered to predict DFU more effectively and suggest nine specific features which appear to be implicated for further investigation. Technology supports real-time in-shoe data collection and wireless transmission, providing a potentially rich source of data to better predict the risk of DFU.

1 August 2019 in Diabetes Research and Clinical Practice
Verified
Journal Article
Closed access
PJPetra Jones
Petra Jones
RBRichard J. Bibb
Richard J. Bibb
MDMelanie J Davies
Melanie J Davies
KKKamlesh Khunti
Kamlesh Khunti
MMMatthew McCarthy
Matthew McCarthy
DWDavid Webb
David Webb

16 July 2024 in Diabetic Medicine
Verified
Journal Article
Closed access
PJPetra Jones
Petra Jones
David ArmstrongDavid Armstrong
David Armstrong
RFRobert Frykberg
Robert Frykberg
MDMelanie J Davies
Melanie J Davies
ARAlex Rowlands
Alex Rowlands