Literature DB >> 1773693

Contact thermography of painful diabetic neuropathic foot.

A W Chan1, I A MacFarlane, D R Bowsher.   

Abstract

OBJECTIVE: To investigate regional differences in skin blood flow (measured by contact thermography) in the diabetic neuropathic foot and to examine the effect of foot temperature on the severity of neuropathic pain. RESEARCH DESIGN AND METHODS: Thirty-five diabetic patients with painful polyneuropathy (PPN) and 33 healthy age- and sex-matched control subjects comprised the study. Mean foot temperature (MFT) in PPN (mean +/- SE 28.3 +/- 0.3 degrees C) was significantly higher (P less than 0.001) than in the control subjects (25.9 +/- 0.5 degrees C), with the highest temperatures over the metatarsal areas and heel. Visual analogue scale pain score (mean +/- SD 5.3 +/- 1.9 cm) did not correlate with MFT (r = -0.14, P = 0.52). In 10 patients with PPN followed for 2-8 mo (mean 4.6), MFT fell by 1.6 degrees C (P = 0.05), but pain scores did not alter.
CONCLUSIONS: Neuropathic pain is unaffected by alterations in skin temperature. Elevated skin temperatures at recognized sites of weight bearing (metatarsal heads and heels) are common in the diabetic neuropathic foot and may indicate tissue injury or inflammation induced by pressure trauma or increased arteriovenous shunting. Follow-up studies will determine whether thermographic hot spots are more susceptible to ulceration.

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Mesh:

Year:  1991        PMID: 1773693     DOI: 10.2337/diacare.14.10.918

Source DB:  PubMed          Journal:  Diabetes Care        ISSN: 0149-5992            Impact factor:   19.112


  5 in total

1.  Morphological pattern classification system for plantar thermography of patients with diabetes.

Authors:  Taketoshi Mori; Takashi Nagase; Kimie Takehara; Makoto Oe; Yumiko Ohashi; Ayumi Amemiya; Hiroshi Noguchi; Kohjiro Ueki; Takashi Kadowaki; Hiromi Sanada
Journal:  J Diabetes Sci Technol       Date:  2013-09-01

2.  A Novel Machine Learning Approach for Severity Classification of Diabetic Foot Complications Using Thermogram Images.

Authors:  Amith Khandakar; Muhammad E H Chowdhury; Mamun Bin Ibne Reaz; Sawal Hamid Md Ali; Serkan Kiranyaz; Tawsifur Rahman; Moajjem Hossain Chowdhury; Mohamed Arselene Ayari; Rashad Alfkey; Ahmad Ashrif A Bakar; Rayaz A Malik; Anwarul Hasan
Journal:  Sensors (Basel)       Date:  2022-06-02       Impact factor: 3.847

3.  Segmentation of Plantar Foot Thermal Images Using Prior Information.

Authors:  Asma Bougrine; Rachid Harba; Raphael Canals; Roger Ledee; Meryem Jabloun; Alain Villeneuve
Journal:  Sensors (Basel)       Date:  2022-05-18       Impact factor: 3.847

4.  Deep Learning Classification for Diabetic Foot Thermograms.

Authors:  Israel Cruz-Vega; Daniel Hernandez-Contreras; Hayde Peregrina-Barreto; Jose de Jesus Rangel-Magdaleno; Juan Manuel Ramirez-Cortes
Journal:  Sensors (Basel)       Date:  2020-03-22       Impact factor: 3.576

5.  Thermal Change Index-Based Diabetic Foot Thermogram Image Classification Using Machine Learning Techniques.

Authors:  Amith Khandakar; Muhammad E H Chowdhury; Mamun Bin Ibne Reaz; Sawal Hamid Md Ali; Tariq O Abbas; Tanvir Alam; Mohamed Arselene Ayari; Zaid B Mahbub; Rumana Habib; Tawsifur Rahman; Anas M Tahir; Ahmad Ashrif A Bakar; Rayaz A Malik
Journal:  Sensors (Basel)       Date:  2022-02-24       Impact factor: 3.576

  5 in total

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