Assessment Of Diabetic Foot Ulcers Research Articles

Assessment of diabetic foot ulcers: back to basics.

Diabetic foot ulceration affects up to 34% of the global diabetic population as a result of poor glycaemic control. Complications resulting from diabetic foot ulceration can be complex, expensive and challenging. It is important for risk factors to be recognised early and for regular assessment to take place. Streamlining a coordinated approach that enhances communication and guides treatment approaches can help to improve wound outcomes.

A Survey on Impact of Internet of Medical Things Against Diabetic Foot Ulcer

INTRODUCTION: In this study, we explore the intricate domain of Diabetic Foot Ulcers (DFU) through the development of a comprehensive framework that encompasses diverse operational scenarios. The focus lies on the identification and classification assessment of diabetic foot ulcers, the implementation of smart health management strategies, and the collection, analysis, and intelligent interpretation of data related to diabetic foot ulcers. The framework introduces an innovative approach to predicting diabetic foot ulcers and their key characteristics, offering a technical solution for forecasting. The exploration delves into various computational strategies designed for intelligent health analysis tailored to patients with diabetic foot ulcers.
 OBJECTIVES: The primary objective of this paper is to present a technical solution for forecasting diabetic foot ulcers, utilizing computational strategies for intelligent health analysis.
 METHODS: Techniques derived from social network analysis are employed to conduct this research, focusing on diverse computational strategies geared towards intelligent health analysis for patients with diabetic foot ulcers. The study highlights methodologies addressing the unique challenges posed by diabetic foot ulcers, with a central emphasis on the integration of Internet of Medical Things (IoMT) in prediction strategies.
 RESULTS: The main results of this paper include the proposal of IoMT-based computing strategies covering the entire spectrum of DFU analysis, such as localization, classification assessment, intelligent health management, and detection. The study also acknowledges the challenges faced by previous research, including low classification rates and elevated false alarm rates, and proposes automatic recognition approaches leveraging advanced machine learning techniques to enhance accuracy and efficacy.
 CONCLUSION: The proposed IoMT-based computing strategies present a significant advancement in addressing the challenges associated with predicting diabetic foot ulcers. The integration of advanced machine learning techniques demonstrates promise in improving accuracy and efficiency in diabetic foot ulcer localization, marking a positive stride towards overcoming existing limitations in previous research.

517-P: Machine Learning Algorithms Using Electronic Medical Record and Ultrasonography of Lower Extremities for 10-Year Risk Assessment of Diabetic Foot Ulcer in China

Objective: Accurate prediction of diabetic foot ulcer (DFU) occurrence in patients with type 2 diabetes mellitus (T2DM) is crucial for determining appropriate treatment strategy and avoiding amputation and infection. Here, we explored machine learning algorithms (ML) of electronic medical record (EMR) for predicting the incident of DFU. Methods: In this retrospective longitudinal observational cohort, 26579 cases from T2DM database of The Third Affiliated Hospital of Sun Yatsen University from Jan 2011 to Dec 2019 were screened and finally 2770 patients without DFU were enrolled. During 5.6 years of follow-up, 178 patients occurred DFU. 44 clinical parameters including EMR and imaging finding were used to develop a DFU risk prediction model using XGBoost, RF, and LR. Results: ML models were established in 178 patients with DFU (110 male, mean 61.1±12.4 years), and 2591 patients without DFU (1424 male, mean 59.0±12.1 years). XGBoost model achieved the best performance in predicting DFU occurrence with an AUC of 0.94, which is better than the performance of RF with AUC of 0.91and LR with AUC of 0.89. A DFU incident significantly increased in high-risk patients (>10%) in the next 10 years. Conclusion: Our study provided a simple and effective risk tool for the prediction of 10-year DFU risk, which can help professionals clinical screening and decision-making for T2DM patients. Disclosure L.Wu: None. Y.Liang: None. X.He: None. Y.Chen: None.

Validity and reliability of Chinese version of the new diabetic foot ulcer assessment scale.

A specific assessment tool is urgently needed to guide effective wound care for diabetic foot ulcers. However, the tool has not been available in Chinese. We aimed to culturally translate and verify the validity and reliability of the new Diabetic Foot Ulcer Assessment Scale (DFUAS). The original scale was translated into Chinese according to the Brislin guidelines. Patients satisfying the inclusion and exclusion criteria were recruited. Each of the included foot ulcers was evaluated independently by two wound care specialists using the new DFUAS and by the third wound care specialists at the same time using the Bates-Jensen Wound Assessment Tool according to per guidelines. 210 diabetic foot ulcers were included for data analysis. The S-CVI of the Chinese version of the DFUAS was 0.96, and the I-CVIs ranged from 0.89 to 0.98. The total Cronbach's Alpha of the scale was 0.709, and the corrected item-total correlation of the items ranged from 0.4 to 0.872. The DFUAS had high inter-observer reliability of 0.997, and there were weak, moderate, and strong correlations between each pair of the items. The Bland-Altman plots showed a good agreement between the scale and the Bates-Jensen Wound Assessment Tool. We concluded that the Chinese version of the DFUAS showed good validity and reliability and is a reliable instrument for the assessment of diabetic foot ulcers.

Comparison of area measurement methods in the routine assessment of diabetic foot ulcers-A consistency analysis method.

Ulcer area is a critical parameter in diabetic foot ulcer assessment but existing methods have deficiencies for routine measurement. We hypothesized that the Image J-based Computer Analysis method has a high level of agreement with the commonly used Maximum Length and Width and the Transparent Dressing-based Square Grid methods and aimed to test the consistency and verify the feasibility of the Image J-based Computer Analysis method in the routine assessment of ulcers. Outpatient attendees with diabetic foot ulcers at the Department of Endocrinology of Sun Yat-sen Memorial Hospital were enrolled between October 2020 and October 2021. The three methods sequentially assessed the area of 65 included ulcers. Results were analysed using one-way analysis of variance and Bland-Altman plots to perform consistency analysis. The mean ± standard deviation ulcer area measured using the three methods were 14.79 ± 5.39, 14.35 ± 5.26, and 14.30 ± 5.26 cm2 , respectively. The measurement differences among the three groups or between any two were not statistically significant. Bland-Altman plots showed good consistency between the Image J-based Computer Analysis and the other two methods. The Image J-based Computer Analysis method can be interchanged with the other methods to assess ulcer areas. It is freely accessible, accurate and home-operable, thus worth consideration by nurses for routine ulcer area assessment.

Clinical Assessment of Diabetic Foot Ulcers Using GWO-CNN based Hyperspectral Image Processing Approach

ABSTRACT Diabetes Mellitus has turned out to be a complicated disease and as of 2016 one out of eleven humans suffer from this disease leading to Diabetic Foot Ulcers (DFU). When not treated, DFUs lead to amputation and in this work, a novel image processing method is proposed for the efficient assessment and classification of DFU images. Initially, pre-processing is done by cascaded fuzzy filter followed by nonlinear partial differential equation (NPDE) based segmentation that segments the foot ulcer regions. Consequently, the local binary pattern (LBP) is employed to extract the useful features. Then the proposed hybrid Grey Wolf Optimization-Convolutional Neural Network (GWO-CNN) model uses these features to identify the DFU regions. The performance evaluation is done by the estimation of the performance metrics and the results are compared with existing algorithms indicating the efficacy of the proposed technique. The obtained results reveal that the proposed work generates an accuracy of 98.5% with a reduced error percentage of 1.4%.

Predictive risk factors for lower limb amputations in patients with diabetic foot ulcer in correlation with Wagner’s grading

Background: Lower extremity amputation in diabetic patients results in high morbidity causing poor quality of life despite high medical expenses. A correlate of risk factors with Wagner‘s grading of foot ulcers and their improvement with multidisciplinary team approach would form a basis for preventive diabetic foot care guidelines in health care policy. Objectives of current study were to assess the risk factors and role of multidisciplinary team approach in patients undergoing lower extremity amputations with diabetic footulcer with different Wagner‘s grading.Methods: Prospective data of diabetic patients above eighteen years with foot ulcers admitted in departments of general surgery/general medicine at Vydehi Institute of medical sciences and research centre, between October 2017 to October 2019 were included. Multi-disciplinary treatment approach was adopted and treated accordingly. Patients were followed up for three months to reassess the risk factors for lower extremity amputation and correlated with Wagner‘s grading system and analyzed using descriptive statistical analysis, SPSS-21.Results: fifty patients with Wagner’s grade 1-4 of which forty four (88%) males and six (12%) females. Four (8%) of the patients underwent major limb amputation. 18% underwent minor amputation and 16% SSG. 54% were grade 3,4 on day 1 and 24% patients were grade 3, 4 and 5 after 3 months of follow up (p=0.034).Conclusions: Clinical assessment of diabetic foot ulcer and identification of risk factors for the nonhealing predicts the favourable outcome in the management of diabetic foot combined with multi-disciplinary team approach strategy.

Using DIRECT Wound Assessment to Predict Limb Salvage and Provide Prognosis of Diabetic Foot Ulcers

Background: Many wound assessment systems including the Wagner classification and University of Texas (UT) grading system have been previously described. The authors of this study applied the DIRECT (Debridement of necrosis, Infection control, Revascularization, Exudate control, Chronicity, and Top surface) wound coding system for initial assessment of diabetic foot ulcers (DFUs) to predict limb salvage and prognosis.<br/>Methods: From January 2016 to February 2020, a total of 169 first-time DFU patients were retrospectively evaluated using the DIRECT wound coding assessment system. DFUs were followed up for at least 6 months, and scores in each component of the coding system according to final limb status were statistically evaluated. The coding assessment’s ability to predict major amputation was compared to those of the Wagner classification and the UT grading system.<br/>Results: Subjects were divided into complete healing (n=80, 47.3%), not healed (n=71, 42%), and amputation (n=18, 10.7%) groups. The mean values of each component of DIRECT assessment for the complete healing/amputation groups were D 0.86/1.56 (P<0.001), I 0.46/0.89 (P=0.001), R 0.65/0.94 (P=0.014), E 1.15/1.56 (P=0.049), C 0.69/0.89 (P=0.086), T 0.53/0.72 (P=0.13) and the sum was 3.140/4.741 (P<0.001). The area under the receiver operating characteristic curve of the DIRECT, Wagner, and UT grading systems was 0.722, 0.603, and 0.663, respectively.<br/>Conclusion: The DIRECT coding system shows a greater association with prediction of amputation or complete healing, compared with the Wagner and UT wound classification systems. This more accurate wound assessment system will be helpful in predicting prognosis and planning treatments.

Assessment of diabetic foot ulcers based on pictorial material: an interobserver study.

The frequent change in clinicians, and the emerging use of photographic documentation in wound management, could require a more diverse treatment of patients due to poor interobserver agreement. The aim of this study was to assess the interobserver agreement of a commonly used classification system for diabetic foot ulcers (DFUs), the Meggitt-Wagner classification, and to compare the agreement on classification with the agreement in treatment recommendations. An interobserver study was conducted based on a questionnaire linked to 30 photographs of DFUs. Different groups of observers were tested to investigate whether there was a difference between professions or level of education: experienced orthopaedic wound care doctors (n=7); nurses specialised in wound care (n=8) and untrained nurses assigned to a diabetic wound care training course (n=23). Krippendorff's alpha was used to calculate interobserver agreement, and an agreement of >0.67 was defined as substantial. The Krippendorff's alpha value for interobserver agreement on the Meggitt-Wagner classification was 0.52 for the doctors group, 0.67 for the specialised nurses and 0.61 for the untrained nurses. The corresponding values regarding agreement on recommendation of surgical revision of the wound were 0.35, 0.22 and 0.15, respectively. The choice of dressing type or antibiotic treatment had even lower interobserver agreement. The interobserver agreement on the Meggitt-Wagner classification was substantial in the specialised nurse group, but the evaluation and treatment of DFUs should not be exclusively based on pictorial materials.

Performance Assessment of Low-Cost Thermal Cameras for Medical Applications.

Thermal imaging is a promising technology in the medical field. Recent developments in low-cost infrared (IR) sensors, compatible with smartphones, provide competitive advantages for home-monitoring applications. However, these sensors present reduced capabilities compared to more expensive high-end devices. In this work, the characterization of thermal cameras is described and carried out. This characterization includes non-uniformity (NU) effects and correction as well as the thermal cameras’ dependence on room temperature, noise-equivalent temperature difference (NETD), and response curve stability with temperature. Results show that low-cost thermal cameras offer good performance, especially when used in temperature-controlled environments, providing evidence of the suitability of such sensors for medical applications, particularly in the assessment of diabetic foot ulcers on which we focused this study.

A Review of Wearable Sensor Systems to Monitor Plantar Loading in the Assessment of Diabetic Foot Ulcers.

Diabetes is highly prevalent throughout the world and imposes a high economic cost on countries at all income levels. Foot ulceration is one devastating consequence of diabetes, which can lead to amputation and mortality. Clinical assessment of diabetic foot ulcer (DFU) is currently subjective and limited, impeding effective diagnosis, treatment and prevention. Studies have shown that pressure and shear stress at the plantar surface of the foot plays an important role in the development of DFUs. Quantification of these could provide an improved means of assessment of the risk of developing DFUs. However, commercially-available sensing technology can only measure plantar pressures, neglecting shear stresses and thus limiting their clinical utility. Research into new sensor systems which can measure both plantar pressure and shear stresses are thus critical. Our aim in this paper is to provide the reader with an overview of recent advances in plantar pressure and stress sensing and offer insights into future needs in this critical area of healthcare. Firstly, we use current clinical understanding as the basis to define requirements for wearable sensor systems capable of assessing DFU. Secondly, we review the fundamental sensing technologies employed in this field and investigate the capabilities of the resultant wearable systems, including both commercial and research-grade equipment. Finally, we discuss research trends, ongoing challenges and future opportunities for improved sensing technologies to monitor plantar loading in the diabetic foot.

Utility of Tetrahydrobiopterin Pathway in the Assessment of Diabetic Foot Ulcer: Significant and Complex Interrelations.

Objectives Tetrahydrobiopterin (BH4) pathway that included generation of neopterin (Neop), biopterin (Biop), and nitric oxide (NO) is altered in type 2 diabetes (T2D). The aim of this study was to assess the biomarkers of BH4 pathway in noninfected DFUs and to relate these levels to the variables of diabetes as well as to the hematological indices. Methods We performed a cross-sectional investigating study in a Kurdish people including 30 healthy subjects (group I), 66 T2D patients (group II), and 57 DFUs patients (group III). Hematological indices including red cell distribution width (RDW), mean platelet volume (MPV), and platelet distribution width (PDW) were determined by Coulter hematological analysis. Serum BH4 markers including NO, Neop, and Biop were determined by using an enzyme-linked immunosorbent assay (ELISA) technology. The relationship between BH4 markers with glycemic and hematological indices was assessed by Spearman's correlation and multivariable regression analysis. Results Neop was significantly increased while PDW was significantly decreased in group III compared with group II patients. Nitric oxide was found to be inversely correlated with age (r = −0.382), duration of diabetes (r = −0.264), mean arterial blood pressure (r = −0.532), body mass index (r = −0.321), RDW (r = −0.322), and PDW (r = −0.284) in group III patients. Circulating Neop and Biop significantly correlated with RDW and erythrocyte sedimentation rate. Multivariable regression analysis revealed that serum Neop predicted the DFUs in 92.5% of group III patients. Conclusion Tetrahydrobiopterin biomarkers are predictors of DFUs and the significant correlation of neopterin with red distribution width and erythrocyte sedimentation rate indicating the role of neopterin in the vascular and inflammation concerns of noninfected DFUs.

High-Resolution Spectral Analysis Accurately Identifies the Bacterial Signature in Infected Chronic Foot Ulcers in People With Diabetes.

Diabetic foot infections are a major cause of hospitalization, and delayed treatment can lead to numerous complications. The aim of this research was to investigate high-resolution spectroscopy of the wound center and periwound area for real-time estimation of multispectral signature of bacteria at the base of diabetic foot ulcers. We investigated the spectrum of the reflected visual light from diabetic foot ulcers and developed a method that identifies the presence of bacteria in the wound infections. We undertook a prospective pilot study on 18 patients with type 1 and type 2 diabetes and chronic diabetic foot ulcers. The spectral coefficients were directly compared with the results from the wound swab. The results of the multispectral analysis demonstrated 100% sensitivity, with 100% negative predictive values of identifying the presence of the bacteria, which was the cause of the infection in the wound. The results of our study suggest that the changes in the multispectral properties of the wound can be used to identify the presence of bacteria in the infected area using a noninvasive device without any contact with the wound. This technique holds great promise for real-time objective evaluation of the wound infection status beyond the standard visual assessment of diabetic foot ulcers.

A review of Wagner classification and current concepts in management of diabetic foot

Diabetic foot is a common complication of diabetes mellitus which affects 15% of diabetic patients in their lifetime. Effective management of diabetic foot can reduce severity of complications such as preventable amputations and possible mortality, and can also improve overall quality of life. The Wagner classification is most commonly used for grading diabetic foot ulcers. Wagner developed a classification system and a treatment algorithm for each grade of ulcer. He asserted that ischemic index derived from Doppler flow pressures is an essential baseline test to predict ulcer healing. The aim of this study was to evaluate and manage different lesions of diabetic foot according to Wagner classification. We propose a treatment-oriented assessment of diabetic foot ulcers based on a cross-examination of the medical, foot, and wound history; a systemized and detailed physical examination; and the results of complementary diagnostic procedures. The pathophysiology and treatment of diabetic foot ulcers are reviewed. While these guidelines cannot dictate the care of all affected patients, they provide evidence based guidance for general patters of practice.

The validity and reliability of remote diabetic foot ulcer assessment using mobile phone images

Despite their potential for telemedicine in diabetic foot ulcer treatment, diagnostic accuracy of assessment of diabetic foot ulcers using mobile phone images is unknown. Our aim was to determine the validity and reliability of remote diabetic foot ulcer assessment using mobile phone images. Fifty diabetic foot ulcers were assessed live and photographed. Five independent observers remotely assessed the mobile phone images twice for presence of nine clinical characteristics and three treatment decisions. Positive likelihood (LLR+) and negative likelihood (LLR−) ratios were calculated for validity. Multirater Randolph’s and bi-rater Bennet kappa values were calculated for reliability. LLR+ ranged from 1.3–4.2; LLR− ranged from 0.13–0.88; the treatment decision ‘peri-wound debridement’ was the only item with ‘strong diagnostic evidence’. Inter-observer reliability kappa ranged from 0.09–0.71; test-retest reliability from 0.45–0.86; the treatment decision ‘peri-wound debridement’ was the only item with ‘adequate agreement’. In conclusion, mobile phone images had low validity and reliability for remote assessment of diabetic foot ulcers and should not be used as a stand-alone diagnostic instrument. Clinicians who use mobile phone images in clinical practice should obtain as much additional information as possible when making treatment decisions based on these images, and be cautious of the low diagnostic accuracy.

Quantitative assessment of wound healing using high-frequency ultrasound image analysis.

We aimed to develop a method for quantitative assessment of wound healing in ulcerated diabetic feet. High-frequency ultrasound (HFU) images of 30 wounds were acquired in a controlled environment on post-debridement days 7, 14, 21, and 28. Meaningful features portraying changes in structure and intensity of echoes during healing were extracted from the images, their relevance and discriminatory power being verified by analysis of variance. Relative analysis of tissue healing was conducted by developing a features-based healing function, optimised using the pattern-search method. Its performance was investigated through leave-one-out cross-validation technique and reconfirmed using principal component analysis. The constructed healing function could depict tissue changes during healing with 87.8% accuracy. The first principal component derived from the extracted features demonstrated similar pattern to the constructed healing function, accounting for 86.3% of the data variance. The developed wound analysis technique could be a viable tool in quantitative assessment of diabetic foot ulcers during healing.

Interobserver Reliability of Three Validated Scoring Systems in the Assessment of Diabetic Foot Ulcers.

Scoring systems for diabetic foot ulcers may be used for clinical purposes, research or audit, to help assess disease severity, plan management, and even predict outcomes. While many have been validated in study populations, little is known about their interobserver reliability. This prospective study aimed to evaluate interobserver reliability of 3 scoring systems for diabetic foot ulceration. After sharp debridement, diabetic foot ulcers were classified by a multidisciplinary pool of trained observers, using the PEDIS (Perfusion, Extent, Depth, Infection, Sensation), SINBAD (Site, Ischemia, Neuropathy, Bacterial infection, Depth), and University of Texas (UT) wound classification systems. Interobserver reliability was assessed using intraclass correlations (0 = no agreement; 1 = complete agreement). Thirty-seven patients (78.4% male) were assessed by a pool of 12 observers. Single observer reliability was slight to moderate for all scoring systems (UT 0.53; SINBAD 0.44; PEDIS 0.23-0.42), but multiple observer reliability was almost perfect (UT 0.94; SINBAD 0.91; PEDIS 0.80-0.90). The worst agreement for single observers was when scoring infection (SINBAD 0.28; PEDIS 0.28), ischemia (SINBAD 0.26; PEDIS 0.23), or both (UT 0.25); however, this improved to almost perfect agreement for multiple observers (infection: 0.83; ischemia: 0.80-0.82; both: 0.81). These classification systems may be reliably used by multiple observers, for example, when conducting research and audit. However, they demonstrate only slight to moderate reliability when used by a single observer on an individual subject and may therefore be less helpful in the clinical setting, when documenting ulcer characteristics or communicating between colleagues.

Remote assessment of diabetic foot ulcers using a novel wound imaging system

Telemedicine allows experts to assess patients in remote locations, enabling quality convenient, cost-effective care. To help assess foot wounds remotely, we investigated the reliability of a novel optical imaging system employing a three-dimensional camera and disposable optical marker. We first examined inter- and intraoperator measurement variability (correlation coefficient) of five clinicians examining three different wounds. Then, to assess of the system's ability to identify key clinically relevant features, we had two clinicians evaluate 20 different wounds at two centers, recording observations on a standardized form. Three other clinicians recorded their observations using only the corresponding three-dimensional images. Using the in-person assessment as the criterion standard, we assessed concordance of the remote with in-person assessments. Measurement variation of area was 3.3% for intraoperator and 11.9% for interoperator; difference in clinician opinion about wound boundary location was significant. Overall agreement for remote vs. in-person assessments was good, but was lowest on the subjective clinical assessments, e.g., value of debridement to improve healing. Limitations of imaging included inability to show certain characteristics, e.g., moistness or exudation. Clinicians gave positive feedback on visual fidelity. This pilot study showed that a clinician viewing only the three-dimensional images could accurately measure and assess a diabetic foot wound remotely.

Near Infrared Wound Monitor Helps Clinical Assessment of Diabetic Foot Ulcers

The efficacy of using diffuse near infrared spectroscopy (NIRS) in predicting wound healing in diabetic foot ulcers was demonstrated by conducting a pilot human study. Sixteen chronic diabetic wounds were followed and assessed for subsurface oxyhemoglobin concentration using the NIRS device. Weekly measurements were conducted until there was wound closure, limb amputation, or 20 completed visits without healing. Wound size and degree of wound contraction were measured by image analysis of digital photographs, and results were compared to NIRS results. In the 16 patients followed, seven wounds healed, six limbs were amputated, and three wounds remained opened after 20 visits. Initial values of subsurface hemoglobin concentration, in all wounds, were higher than in nonwound control sites. Healed wounds exhibited a consistent reduction of hemoglobin concentration several weeks prior to closure, and the absolute hemoglobin concentration approached the value at the control site. In wounds that did not heal or ended in amputations, the hemoglobin concentration remained elevated throughout the study. A negative slope for the rate of change of hemoglobin concentration was indicative of healing across all wounds. Evaluation of diabetic foot ulcers using NIRS may provide an effective and more complete measurement of wound healing compared to current clinical approaches.

Noninvasive assessment of diabetic foot ulcers with diffuse photon density wave methodology: pilot human study

A pilot human study is conducted to evaluate the potential of using diffuse photon density wave (DPDW) methodology at near-infrared (NIR) wavelengths (685 to 830 nm) to monitor changes in tissue hemoglobin concentration in diabetic foot ulcers. Hemoglobin concentration is measured by DPDW in 12 human wounds for a period ranging from 10 to 61 weeks. In all wounds that healed completely, gradual decreases in optical absorption coefficient, oxygenated hemoglobin concentration, and total hemoglobin concentration are observed between the first and last measurements. In nonhealing wounds, the rates of change of these properties are nearly zero or slightly positive, and a statistically significant difference (p<0.05) is observed in the rates of change between healing and nonhealing wounds. Differences in the variability of DPDW measurements over time are observed between healing and nonhealing wounds, and this variance may also be a useful indicator of nonhealing wounds. Our results demonstrate that DPDW methodology with a frequency domain NIR device can differentiate healing from nonhealing diabetic foot ulcers, and indicate that it may have clinical utility in the evaluation of wound healing potential.