Home Monitoring of Foot Skin Temperatures to Prevent Ulceration

NewsBot · Aug 12, 2023

Prescribing Home Digital Thermometry Coupled with Activity Dosing and Optimized Offloading to Prolong Diabetic Foot Remission: A Case Report
Malindu E Fernando et al
Int J Low Extrem Wounds. 2023 Jul 4

People with a history of diabetic foot ulcers (DFUs) experience diminished health-related quality of life and are at a 40% annual risk of DFU recurrence. Due to a fear of DFU recurrence, people in DFU remission participate less in physical activity and moderate-intensity exercise when compared to people with diabetes who have not had wounds. There is novel evidence to suggest that too little activity during DFU remission contributes to only low magnitudes of repetitive tissue loading creating a higher susceptibility to skin trauma during inadvertent high-activity bouts. Conversely, a hasty return to too much activity could lead to rapid recurrence. There is now high-level evidence from multiple meta-analyses to indicate that home-based foot temperature monitoring, coupled with activity modification and daily inspection of the feet for impending signs of ulceration, could reduce the risk of ulcer recurrence by 50%. There is little evidence, however, to guide the decision-making regarding the appropriate quantity and frequency of physical activity during DFU remission and the acceptability from the patient perspective. This has resulted in limited uptake of this novel intervention in clinical practice. Earlier, we proposed that activity can be dosed for people in foot ulcer remission, just like insulin or medication is dosed. Here, we describe a patient-centered approach to implementing home foot temperature monitoring coupled with daily foot checks and dosage-based return to physical activity in a patient in DFU remission, including his perspective. We believe using such an approach could maximize ulcer-free days in remission, thereby improving quality of life.
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NewsBot · Sep 8, 2023

Automatic Diabetic Foot Ulcer Recognition Using Multi-Level Thermographic Image Data
Ikramullah Khosa et al
Diagnostics (Basel). 2023 Aug 10;13(16):2637

Lower extremity diabetic foot ulcers (DFUs) are a severe consequence of diabetes mellitus (DM). It has been estimated that people with diabetes have a 15% to 25% lifetime risk of acquiring DFUs which leads to the risk of lower limb amputations up to 85% due to poor diagnosis and treatment. Diabetic foot develops planter ulcers where thermography is used to detect the changes in the planter temperature. In this study, publicly available thermographic image data including both control group and diabetic group patients are used. Thermograms at image level as well as patch level are utilized for DFU detection. For DFU recognition, several machine-learning-based classification approaches are employed with hand-crafted features. Moreover, a couple of convolutional neural network models including ResNet50 and DenseNet121 are evaluated for DFU recognition. Finally, a CNN-based custom-developed model is proposed for the recognition task. The results are produced using image-level data, patch-level data, and image-patch combination data. The proposed CNN-based model outperformed the utilized models as well as the state-of-the-art models in terms of the AUC and accuracy. Moreover, the recognition accuracy for both the machine-learning and deep-learning approaches was higher for the image-level thermogram data in comparison to the patch-level or combination of image-patch thermograms.
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NewsBot · Oct 31, 2023

Diabetic Plantar Foot Segmentation in Active Thermography Using a Two-Stage Adaptive Gamma Transform and a Deep Neural Network
Zhenjie Cao et al
Sensors (Basel). 2023 Oct 17;23(20):8511

Pathological conditions in diabetic feet cause surface temperature variations, which can be captured quantitatively using infrared thermography. Thermal images captured during recovery of diabetic feet after active cooling may reveal richer information than those from passive thermography, but diseased foot regions may exhibit very small temperature differences compared with the surrounding area, complicating plantar foot segmentation in such cold-stressed active thermography. In this study, we investigate new plantar foot segmentation methods for thermal images obtained via cold-stressed active thermography without the complementary information from color or depth channels. To better deal with the temporal variations in thermal image contrast when planar feet are recovering from cold immersion, we propose an image pre-processing method using a two-stage adaptive gamma transform to alleviate the impact of such contrast variations. To improve upon existing deep neural networks for segmenting planar feet from cold-stressed infrared thermograms, a new deep neural network, the Plantar Foot Segmentation Network (PFSNet), is proposed to better extract foot contours. It combines the fundamental U-shaped network structure, a multi-scale feature extraction module, and a convolutional block attention module with a feature fusion network. The PFSNet, in combination with the two-stage adaptive gamma transform, outperforms multiple existing deep neural networks in plantar foot segmentation for single-channel infrared images from cold-stressed infrared thermography, achieving an accuracy of 97.3% and 95.4% as measured by Intersection over Union (IOU) and Dice Similarity Coefficient (DSC) respectively.
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NewsBot · Dec 28, 2023

Plantar Thermography in High-Risk Patients With Diabetes Mellitus Compared to Nondiabetic Individuals
Gabriela Verónica Carro et al
Int J Low Extrem Wounds. 2023 Dec 19

Diabetic foot (DF) is one of the most devastating complications of diabetes mellitus (DM). Infrared thermography has been studied for its potential in early diagnosis and preventive measures against DF ulcers, although its role in the management and prevention of DF complications remains uncertain. The objective of this study was to determine the average temperatures of different points of the plantar foot using infrared thermography in patients with DM and history of DF (DFa group, at the highest risk of developing foot ulcers) and compare them to people without DM (NoDM group). One hundred and twenty-three feet were included, 63 of them belonged to DFa Group and the other 60 to NoDM Group. The average temperature in the NoDM Group was 27.4 (26.3-28.5) versus 28.6 (26.8-30.3) in the DFa Group (p = .002). There were differences between both groups in temperatures at the metatarsal heads and heels, but not in the arch. Average foot temperatures did not relate to sex, ankle-brachial index, and age, and had a mild correlation with daily temperature (Spearman 0.51, p < .001). Data provided in our study could be useful in establishing a parameter of normal temperatures for high-risk patients. This could serve as a foundational framework for future research and provide reference values, not only for preventative purposes, as commonly addressed in most studies, but also to assess the applicability of thermography in clinical scenarios particularly when one foot cannot serve as a reference, suspected osteomyelitis of the remaining bone, or instances of increased temperature in specific areas which may necessitate adjustments to the insoles in secondary prevention.
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NewsBot · Jan 4, 2024

Telemedical Monitoring of Plantar Temperature in Diabetic Patients at Risk of Foot Ulcers—The Randomized Smart Prevent Diabetic Feet Trial
Antao Ming, Ahmad Alhajjar, Isabell Walter, Claudia Piehler, Jacqueline Hoetzsch, Martin Leuckert, Vera Clemens, Andreas Petrow, Istiyak M Siddiquee, Florian G Scurt, Berend Isermann, Peter R Mertens
Dtsch Arztebl Int. 2023 Dec 21

Background: The worldwide prevalence of diabetic foot ulcers (DFUs) among persons with diabetes is estimated at 6.3%, with an annual incidence of 9.1 to 26.1 million persons. The early detection of asymmetrical plantar temperature elevation, followed by reduction of weight-bearing on the affected foot, may be an effective mode of prevention.

Methods: Patients with diabetes and peripheral neuropathy (DFU risk groups 2/3) were monitored for plantar abnormalities with a telemedical system consisting of sole inserts with temperature sensors and photographic documentation. An open, prospective, randomized controlled trial was performed to determine whether this system prevented DFUs. The intervention and control groups were also trained in ulcer prevention and observed in follow-up at 6-month intervals for 24 months.

Results: 283 patients were recruited. In 85 137 observation days, DFUs arose in five patients in the control group (n = 143) and in no patient in the intervention group (n = 140). The primary outcome measure was the hazard ratio, which was calculated to be 0.015 (95% confidence interval [0; 19,717]; p = 0.25) after adjustment for age, sex, severity of neuropathy, and risk class. There were 239 alarms and 75 instructions to reduce weight-bearing on the foot. The subjects carried out the telemedical application on about 70% of the days of observation. Quality of life improved in both groups.

Conclusion: The tele-health system used in this trial is practical and enables the early detection of morbidity. Likely explanations for the unexpectedly low ulceration rate in this trial (and, in turn, for the lack of statistical significance) include the availability of a training program and regular follow-up examinations to patients in both arms of the trial, along with lower mobility levels due to the COVID pandemic.
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NewsBot · Jan 31, 2024

Effectiveness of a Continuous Remote Temperature Monitoring Program to Reduce Foot Ulcers and Amputations: Multicenter Postmarket Registry Study
Chia-Ding Shih et al
JMIR Diabetes. 2024 Jan 29:9:e46096

Background: Neuropathic foot ulcers are the leading cause of nontraumatic foot amputations, particularly among patients with diabetes. Traditional methods of monitoring and managing these patients are periodic in-person clinic visits, which are passive and may be insufficient for preventing neuropathic foot ulcers and amputations. Continuous remote temperature monitoring has the potential to capture the critical period before the foot ulcers develop and to improve outcomes by providing real-time data and early interventions. For the first time, the effectiveness of such a strategy to prevent neuropathic foot ulcers and related complications among high-risk patients in a real-world commercial setting is reported.

Objective: This study aims to evaluate the effectiveness of a real-world continuous remote temperature monitoring program in preventing neuropathic foot ulcers and amputations in patients with diabetes.

Methods: In this retrospective analysis of a real-world continuous remote temperature monitoring program, 115 high-risk patients identified by clinical providers from 15 geographically diverse private podiatry offices were analyzed. Patients received continuous remote monitoring socks as part of the program. The enrollment was based on medical necessity as decided by their managing physician. We evaluated data from up to 2 years before enrollment and up to 3 years during the program. The primary outcome was the rate of wound development. Secondary outcomes included amputation rate, the severity of the foot ulcers, and the number of visits to an outpatient podiatry clinic after enrolling in the program.

Results: We observed significantly lower rates of foot ulceration (relative risk reduction [RRR] 0.68; 95% CI 0.52-0.79; number needed to treat [NNT] 5.0; P<.001), less moderate to severe ulcers (RRR 0.86; 95% CI 0.70-0.93; NNT 16.2; P<.001), less amputations (RRR 0.83; 95% CI 0.39-0.95; NNT 41.7; P=.006), and less hospitalizations (RRR 0.63; 95% CI 0.33-0.80; NNT 5.7; P<.002). We found a decrease in outpatient podiatry office visits during the program (RRR 0.31; 95% CI 0.24-0.37; NNT 0.46; P<.001).

Conclusions: Our findings suggested that a real-world continuous remote temperature monitoring program was an effective strategy to prevent foot ulcer development and nontraumatic foot amputation among high-risk patients.
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NewsBot · Feb 20, 2024

Automated Prediction of Diabetes Mellitus using Infrared Thermal Foot Images: Recurrent Neural Network Approach
Gulshan Kumar, Ajat Shatru Arora
Biomed Phys Eng Express. 2024 Jan 31.

Millions of people worldwide are affected by Diabetes Mellitus (DM), which is a chronic disease. Evaluation of the DM indicator, namely blood glucose level, requires invasive methods such as glucometer or blood tests, which cause discomfort to the patient. Automated noninvasive monitoring methods are urgently needed to ensure consistency and better treatment. The regular monitoring of DM can prevent or delay the onset of complications. Thermal foot images have been proposed as noninvasive methods for the prediction of DM. Thermograms were acquired at Mittal Eye Hospital, Sangrur, India, from 50 participants in the diabetic (without neuropathic conditions) and non-diabetic groups using a thermal camera (FLIR E-60). This study proposes an automated prediction system for DM using thermal foot images and Recurrent Neural Network (RNN) approach. The proposed system processes the thermal images and extracts relevant features using a CNN (Convolutional Neural Network). The extracted features were then fed to the RNN to predict the presence or absence of the DM. The experimental results demonstrate that the proposed framework attains an accuracy of (97.14 ± 1.5) %, surpassing the predictive capabilities of light-weight convolutional neural network (Lw-CNN), which only achieves an accuracy of (82.9 ± 3) % in predicting DM. This performance outperformed other state-of-the-art methods in the field. Our approach has the potential to be used as prediction tool for DM. Therefore, the proposed system has the potential for prediction of DM and improve patient outcomes by enabling timely intervention. Future work should focus on evaluating the proposed system on a larger dataset and integrating it with clinical decision support systems for personalized care. This study holds the promise of transforming DM screening and diagnosis, leading to enhanced patient outcomes.
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NewsBot · Mar 2, 2024

Clinical value of foot thermometry in patients with acute limb ischemia
Dumitru Casian et al
Vascular. 2024 Mar 1

Objective: We hypothesized that the severity of foot poikilothermy can be used for better differentiation of grades of acute limb ischemia. Thus, the study aim was evaluation of the value of non-contact foot thermometry, performed using a low-cost infrared medical thermometer, as an adjunct for clinical diagnosis of immediately threatened acute limb ischemia.

Methods: It was a single-center observational prospective study performed over 3 years. Patients with acute limb ischemia of lower limbs grade I-IIB Rutherford treated with urgent revascularization were included. Grade of ischemia was determined independently by two experienced vascular surgeons. Thermometry of the ischemic foot was performed using a medical digital infrared non-contact thermometer (CK-T1501, Cooligg, China) with measuring accuracy of ±0.2°C. Temperature was measured in three points: the dorsal surface of the foot, plantar surface of the foot (both in the metatarsal region), and forehead. The maximal temperature gradient between patient's forehead and foot (∆Tmax F-F) was calculated. Measurements were repeated 6-12 h after revascularization.

Results: A total of 147 patients were included. Only 3 (2%) patients presented rest pain without sensory loss and motor deficit, while the majority were diagnosed with mild (63/147, 42.8%) or moderate (27/147, 18.3%) motor deficit. The temperature of the ischemic foot varied from 20 to 36.1°C, while median value of the temperature was 26.7 [24.5-29.9] °C on the dorsal surface and 26.8 [24.5-29.6] °C on the plantar surface of the foot (p = 0.85). Patients with Grade IIB ischemia had significantly lower dorsal foot temperature, plantar foot temperature, and larger ∆Tmax F-F than the patients with grades I-IIA: 25.1 [23.9-26.8] °C versus 29.9 [27.6-30.8] °C; 25.2 [23.8-27.5] °C versus 29.6 [28-31.1] °C; and 11.6 [9.7-12.8] °C versus 7.2 [6-9] °C (p < 0.0001). Areas under ROC curve for diagnosis of Grade IIB ischemia were similar for dorsal foot temperature (0.82), plantar temperature (0.81), and ∆Tmax F-F (0.82). The best cutoff value by Youden was ≥9.5°C for ∆Tmax F-F, ≤26.8°C for dorsal, and ≤27.7°C for plantar temperature. Criterion ∆Tmax F-F offered the highest specificity of 86% (95%CI 74.2-93.7) and positive predictive value of 89.2% (95%CI 79.5-93.2), while plantar temperature offered sensitivity of 82.5% (95%CI 70.1-91.3) and negative predictive value of 69.1% (95%CI 57.6-83.2). In multivariate analysis including age, gender, and etiology of arterial occlusion, the criterion ∆Tmax F-F of ≥9.5°C was a unique variable significantly associated with risk of amputation (adjusted OR 2.6, 95%CI 1.2-5.9, p = 0.01).

Conclusion: Current study demonstrated that patients with immediately threatening ALI have significantly lower foot temperature than those with viable and marginally threatened limbs. Severe foot poikilothermy at admission is associated with poor outcomes of revascularization, mostly with limb loss.
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Home Monitoring of Foot Skin Temperatures to Prevent Ulceration

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Diabetic foot ulcer prevention by home monitoring of temperature

Smart insole for continuous monitoring of frail people at home

Homeopathy for Diabetic Foot Ulcers

Podiatrist wanted for home visit round in Wigan area

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Home Monitoring of Foot Skin Temperatures to Prevent Ulceration

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Diabetic foot ulcer prevention by home monitoring of temperature

Smart insole for continuous monitoring of frail people at home

Homeopathy for Diabetic Foot Ulcers

Podiatrist wanted for home visit round in Wigan area

contracting for nursing home help!

Pp from home

Nursing home gigs

Share This Page

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