Diagnosis Of Diabetic Foot Ulcer Research Articles

Integrating bioinformatics and multiple machine learning to identify mitophagy-related targets for the diagnosis and treatment of diabetic foot ulcers: evidence from transcriptome analysis and drug docking.

Diabetic foot ulcers are the most common and serious complication of diabetes mellitus, the high morbidity, mortality, and disability of which greatly diminish the quality of life of patients and impose a heavy socioeconomic burden. Thus, it is urgent to identify potential biomarkers and targeted drugs for diabetic foot ulcers. In this study, we downloaded datasets related to diabetic foot ulcers from gene expression omnibus. Dysregulation of mitophagy-related genes was identified by differential analysis and weighted gene co-expression network analysis. Multiple machine algorithms were utilized to identify hub mitophagy-related genes, and a novel artificial neural network model for assisting in the diagnosis of diabetic foot ulcers was constructed based on their transcriptome expression patterns. Finally, potential drugs that can target hub mitophagy-related genes were identified using the Enrichr platform and molecular docking methods. In this study, we identified 702 differentially expressed genes related to diabetic foot ulcers, and enrichment analysis showed that these genes were associated with mitochondria and energy metabolism. Subsequently, we identified hexokinase-2, small ribosomal subunit protein us3, and l-lactate dehydrogenase A chain as hub mitophagy-related genes of diabetic foot ulcers using multiple machine learning algorithms and validated their diagnostic performance in a validation cohort independent of the present study (The areas under roc curve of hexokinase-2, small ribosomal subunit protein us3, and l-lactate dehydrogenase A chain are 0.671, 0.870, and 0.739, respectively). Next, we constructed a novel artificial neural network model for the molecular diagnosis of diabetic foot ulcers, and the diagnostic performance of the training cohort and validation cohort was good, with areas under roc curve of 0.924 and 0.840, respectively. Finally, we identified retinoic acid and estradiol as promising anti-diabetic foot ulcers by targeting hexokinase-2 (-6.6 and -7.2kcal/mol), small ribosomal subunit protein us3 (-7.5 and -8.3kcal/mol), and l-lactate dehydrogenase A chain (-7.6 and -8.5kcal/mol). The present study identified hexokinase-2, small ribosomal subunit protein us3 and l-lactate dehydrogenase A chain, and emphasized their critical roles in the diagnosis and treatment of diabetic foot ulcers through multiple dimensions, providing promising diagnostic biomarkers and targeted drugs for diabetic foot ulcers.

Residential Address Amplifies Health Disparities and Risk of Infection in Individuals With Diabetic Foot Ulcers.

To determine the association between social determinants of health (SDOH) and a diagnosis of diabetic foot ulcer (DFU) infection. Targeted interrogation of electronic health record data using novel search engines to analyze individuals with a DFU infection during a 5-year period (2013-2017) was performed. We extracted geolocated neighborhood data and SDOH characteristics from the National Neighborhood Data Archive and used univariate and multiple logistic regression to evaluate associations with outcomes in the population with diabetes. Among 4.3 million people overall and 144,564 individuals with diabetes seen between 2013 and 2017, 8,351 developed DFU, of which cases 2,252 were complicated by a DFU infection. Sex interactions occurred, as men who experienced a DFU infection more frequently identified as having nonmarried status than their female counterparts. For the population with DFU infection, there were higher rates for other SDOH, including higher neighborhood disadvantaged index score, poverty, nonmarriage, and less access to physician/allied health professionals (all P < 0.01). In multiple logistic regression, those individuals who developed DFU infection came from neighborhoods with greater Hispanic and/or foreign-born concentrations (odds ratio 1.11, P = 0.015). We found significant differences in neighborhood characteristics driving a higher risk for DFU infection in comparisons with the grouping of individuals with diabetes overall, including increased risk for individuals with Hispanic and/or foreign-born immigration status. These data strongly support the need to incorporate SDOH, particularly ethnic and immigration status, into triage algorithms for DFU risk stratification to prevent severe diabetic foot complications and move beyond biologic-only determinants of health.

The use of intralesional epidermal growth factor in the treatment of diabetic foot ulcers

Aims: The mitogenic and cell protective effects of epidemal growth factor (EGF) in wound healing stimulate the growth, re-covering the surface of the wound area. In this research we tried to elucidate the effectiveness of intradermal EGF application on wound healing in diabetic foot ulcers regarding the fact that EGF can accelerate the formation of skin cover layer on the infected surface, even in relatively ischemic cases.&#x0D; Methods: The data of 68 patients who applied to our institution’s orthopedics and wound care outpatient clinic with the diagnosis of diabetic foot ulcer, who underwent wound care, debridement and follow-up were retrospectively analyzed. All of the patients included in this study were classified as Wagner Stage III and Stage IV diabetic foot ulcers and were followed up with standard wound care. EGF application was initiated if there was not enough bleeding on the wound borders and defect floor after debridement.&#x0D; Results: The rate of patients with 50% or more granulation in the second week of treatment in the groups was 35.7% (n=10) in the standard treatment group, it was 60% (n=24) in the EGF group (p

AESPNet: Attention Enhanced Stacked Parallel Network to improve automatic Diabetic Foot Ulcer identification

Diabetic Foot Ulcer (DFU) is a severe complication of diabetes, and it may cause lower limb amputation. However, the manual diagnosis of DFU is a complicated and expensive process. The primary objective of this work is to design an efficient Convolutional Neural Network (CNN) approach to identify DFU. Therefore, a novel CNN-based approach (AESPNet) is proposed in this paper, where convolution layers are stacked together in a parallel fashion and with an intermediate attention module to perform DFU vs -normal skin classification. The AESPNet consists of 2 blocks, where varying-sized kernel convolution layers are connected in a parallel fashion for better local and global feature abstraction. A bottleneck attention module is associated after every concatenation operation in the network. The Stochastic Gradient Descent (SGD) (with momentum) optimizer with 1e-2 learning rate is used to train the proposed network on a privately accessed DFU dataset. The results of the proposed approach are compared with other standard CNN-based schemes, namely AlexNet, VGG16, DenseNet121, and InceptionV3. It has been found that the proposed AESPNet outperforms state-of-the-art schemes with a sensitivity score of 98.44% and 0.98 F1-Scores.

Network pharmacology-based approach for exploring the biotargets and mechanisms of vitamin A for the treatment of diabetic foot ulcers

Abstract Background In some developing countries, people have little knowledge about the causes of diabetic foot ulcers. Therefore, public health education for patients on these conditions is a prerequisite for effective pharmacological treatment. Diabetic foot ulcers are a complex symptom of diabetes and are hard to cure due to the lack of efficacious medicine and alternative treatment approaches. Vitamin A (VA) is known to have potent biological functions, including skin repair and immunoregulation. However, the potential pharmacological effects and molecular mechanisms of VA on foot ulcers are still to be discovered. Methods By using bioinformatic/computational analyses, including network pharmacology, gene ontology and the Kyoto Encyclopedia of Genes and Genomes enrichment analysis, we aimed to identify and reveal the pharmacological targets, molecular mechanisms, biological functions, and signaling pathways of VA in the treatment of diabetic foot ulcers. Results A total of 66 intersection genes were identified as candidate targets of VA, which are related to diabetic foot ulcers. Therein, 18 core genes/targets, namely JUN, MAPK1, THRB, MAPK14, MTNR1B, CXCR3, ESR1, AR, HDAC1, IL-10, CNR1, DRD2, EGFR, ADRA2A, CCND1, RXRB, RARA, and RXRA, were further identified. Furthermore, the biological processes, cell components, and molecular functions which may underlie the effects of VA against diabetic foot ulcers were characterized. Conclusion Based on our findings, we concluded that the pharmacological effects of VA on diabetic foot ulcers primarily involve the promotion of cellular regeneration and proliferation and the inhibition of inflammatory response. The core genes/targets may potentially serve as promising biomarkers for the diagnosis of diabetic foot ulcers.

Diabetic Foot Ulcer Identification: A Review

Diabetes is a chronic condition caused by an uncontrolled blood sugar levels in the human body. Its early diagnosis may prevent severe complications such as diabetic foot ulcers (DFUs). A DFU is a critical condition that can lead to the amputation of a diabetic patient’s lower limb. The diagnosis of DFU is very complicated for the medical professional as it often goes through several costly and time-consuming clinical procedures. In the age of data deluge, the application of deep learning, machine learning, and computer vision techniques have provided various solutions for assisting clinicians in making more reliable and faster diagnostic decisions. Therefore, the automatic identification of DFU has recently received more attention from the research community. The wound characteristics and visual perceptions with respect to computer vision and deep learning, especially convolutional neural network (CNN) approaches, have provided potential solutions for DFU diagnosis. These approaches have the potential to be quite helpful in current medical practices. Therefore, a detailed comprehensive study of such existing approaches was required. The article aimed to provide researchers with a detailed current status of automatic DFU identification tasks. Multiple observations have been made from existing works, such as the use of traditional ML and advanced DL techniques being necessary to help clinicians make faster and more reliable diagnostic decisions. In traditional ML approaches, image features provide signification information about DFU wounds and help with accurate identification. However, advanced DL approaches have proven to be more promising than ML approaches. The CNN-based solutions proposed by various authors have dominated the problem domain. An interested researcher will successfully be able identify the overall idea in the DFU identification task, and this article will help them finalize the future research goal.

Level of 25-hydroxyvitamin D and vitamin D receptor in diabetic foot ulcer and factor associated with diabetic foot ulcers

BackgroundAt present, there is no clinical study to elucidate the correlation between vitamin D deficiency and the incidence of diabetic foot osteomyelitis (DFO).This study aims to clarify levels of 25-hydroxyvitamin D [25(OH)VD] in peripheral blood and vitamin D receptor (VDR) expression in wound margin tissues (T-VDR) of patients with type 2 diabetes mellitus (T2DM) with diabetic foot ulcer (DFU) and DFO, and to determine its correlation with treatment outcomes of DFU and DFO, and and its value as a potential biomarker for the diagnosis of DFU and DFO.Methods156 T2DM patients with DFU (DFU group), 100 T2DM patients without DFU (T2DM group), and 100 healthy controls (NC group). The DFU group patients were subdivided into DFO (n = 80) and NDFO groups (n = 76). The level of serum 25(OH)VD was measured via chemiluminescence immunoassay, and T-VDR expression level was determined by quantitative real-time PCR.ResultsThe levels of serum 25(OH)VD in the DFU group were significantly lower than the T2DM group [(10.3 (5.8, 18.7) vs 15.7 (8.6, 24.6) ng/mL, P = 0.002)]. Similarly, the levels of serum 25(OH)VD and T-VDR expression in the DFO group were statistically lower than the NDFO group [9.2 (5.2, 20.5) vs 12.8 (6.9, 22.1) ng/mL, P = 0.006)], [1.96 (0.61, 3.97) vs 3.11 (1.36, 5.11), P = 0.004)], respectively. Furthermore, the levels of serum 25(OH)VD and T-VDR expression in DFU patients were positively correlated with the ulcer healing rate of foot ulcer after 8 weeks of treatment ( P = 0.031, P = 0.016, respectively). Multivariate logistic regression analysis showed that low level of serum 25(OH)VD was an independent risk factor for DFU and DFO (ORDFU = 2.42, ORDFO = 3.05, P = 0.008, 0.001, respectively), and decreased T-VDR expression level was an independent risk factor for DFO (OR = 2.83, P = 0.004). Meanwhile, the ROC curve analysis indicated that the AUC of serum 25(OH)VD level for the diagnosis of DFU and DFO was 0.821 (95% CI, 0.754–0.886, P < 0.001) and 0.786 (95%CI, 0.643–0.867, P < 0.001), respectively. When establishing a diagnosis of DFO, the AUC of T-VDR expression level was 0.703 (95%CI: 0.618–0.853, P < 0.001).ConclusionsThe levels of serum 25(OH)VD and T-VDR expression in DFU and DFO decreased. Serum 25(OH)VD and T-VDR are potentially valuable biomarkers for diagnosis and prognosis of DFU and DFO..

Increased Expression of miR-155 in Peripheral Blood and Wound Margin Tissue of Type 2 Diabetes Mellitus Patients Associated with Diabetic Foot Ulcer.

To investigate the correlations of miR-155 expression in the peripheral blood and wound margin tissue of patients with diabetic foot ulcer (DFU) and explore the clinical value of miR-155 as a potential biomarker for the diagnosis and treatment outcomes of DFU. Sixty newly diagnosed T2DM patients without DFU (T2DM group), 112 T2DM patients with DFU (DFU group), and 60 healthy controls (NC group) were included. MiR-155 levels in the peripheral blood and wound margin tissue were determined by quantitative real-time PCR, while clinical features and risk factors of DFU were explored. Multiple stepwise logistic regression analysis was used to determine whether miR-155 expression was an independent risk factor for DFU. The diagnostic effectiveness of miR-155 level on DFU was evaluated using ROC curve analysis. A significant decrease in the expression level of miR-155 was observed in T2DM group compared with NC group (P < 0.05), while a markedly increased miR-155 expression level was noted in DFU group compared with T2DM group (P < 0.01). Moreover, there was a negative correlation between the expression levels of miR-155 with healing rate of DFU. Kaplan-Meier survival curve analysis showed that the cumulative rate of unhealed DFU in miR-155 high expression group is higher than that in miR-155 low expression group, both in peripheral blood and wound margin tissue (log rank, P = 0.004, P < 0.001, respectively). The multivariate logistic regression analysis confirmed that a high expression of miR-155 was an independent risk factor for DFU. The ROC curve analysis indicated that the AUC of miR-155 for the diagnosis of DFU was 0.794, with the optimum sensitivity being 96.82% and the optimum specificity of 95.93%. The increased expression of miR-155 in peripheral blood of T2DM patients is closely related to the occurrence of DFU. MiR-155 is a potentially valuable biomarker for diagnosis and prognosis of DFU.

Microbial Profile and Antimicrobial Susceptibility Pattern in Diabetic Foot Ulcer Patients Attending a Tertiary Care Hospital.

Background This study aimed to assess the bacterial profile of diabetes patients with an infected foot and their antimicrobial susceptibility pattern in a tertiary care hospital. Methodology We conducted a six-month prospective study at a hospital in Peshawar, Pakistan. Demographics and clinical characteristics such as age, sex, type and duration of diabetes, glycemic control, presence of retinopathy, nephropathy, neuropathy, peripheral vascular disease, ulcer size, outcomes, and the number of admitted days at the facility were collected. Pus or discharges from the ulcer base and debrided necrotic tissue were obtained. Gram staining was performed on the samples which were isolated on chocolate agar and MacConkey agar. Incubation was done for 24 hours at a temperature of 37°C, and isolates were identified using standard bacteriological methods. The Kirby-Bauer testing method was used to assess antibiotic susceptibility. Results A total of 200 patients received a diagnosis of diabetic foot ulcer at the hospital during the study period. The age of the patients ranged from 24 to 92 years, with a mean age of 58.12 years (standard deviation (SD) = 12.494). The mean HbA1c level was 9.33% (SD = 2.050). The mean duration of diabetes mellitus was 12.3 years (SD = 6.181). In total, 96 (66.2%) isolates were gram-negative bacteria, while 49 (33.8%) were gram-positive bacteria. Among the gram-negative bacteria, Pseudomonas spp. was the most reported (15.9%), whereas methicillin-resistant Staphylococcus aureus was the most reported gram-positive bacteria (20.7%). Amikacin was found to be the most effective (45%) in treating diabetic foot ulcers, followed by tineam and meropenem being equally effective at a susceptibility of 44%. The highest resistance of the microbes was to the drug trimethoprim (44.5%). Conclusions The pathogens causing diabetic foot ulcers show sensitivity to many of the routinely used medications. However, resistance is being developed to some of the antibiotics such as trimethoprim. Therefore, the culture of the specimen to identify the causative agent and adequate knowledge of the susceptibility pattern are critical for the appropriate management of diabetic foot ulcers.

Racial Disparities in Health Care With Timing to Amputation Following Diabetic Foot Ulcer.

To examine variations in timing of lower-limb amputation (LLA) across race/ethnicity and sex among older adults with a diabetic foot ulcer (DFU). It was hypothesized Black/African Americans were more likely to have LLA post-DFU earlier compared with non-Hispanic/Whites, and more men would receive LLA earlier post-DFU compared with women. This was a retrospective cohort analysis of enrolled Medicare fee-for-service (FFS) beneficiaries with a diagnosis of DFU during the study period (2012-2017), allowing up to 5 years post-DFU. Final analytic sample contained 643,287 individuals; the subsample consisted of 68,633 individuals with LLA only. The primary outcome was mutually exclusive groups based on timing of LLA. Multinomial logistic regression was applied to assess likelihood of membership into a group post-DFU based on characteristics such as sex and race/ethnicity. Black/African American beneficiaries had 1.98 (95% CI 1.93-2.03) times the odds of receiving an LLA within 1 year of DFU diagnosis compared with non-Hispanic/White beneficiaries relative to no amputation. Female beneficiaries had increased odds (odds ratio [OR] 1.07, 95% CI 1.02-1.11] between 1 and 3 years and OR 1.08 [95% CI 1.03-1.12] in ≥3 years) of a delayed LLA compared with men among those that underwent LLA. Notably, these results present novel evidence on timing of LLA between racial groups and sex for Medicare FFS beneficiaries post-DFU. Results may be generalizable to individuals with Medicare FFS and DFU. Clinically more targeted, evidence-based decision making informs care decisions with opportunities to address inequities related to the social determinants of health that may lead to LLA.

Early detection of diabetic foot ulcers from thermal images using the bag of features technique

The most common diabetes complication, diabetic foot ulcer (DFU), can result in amputation if not managed effectively. Early diagnosis is thus critical, yet DFU symptoms cannot be reliably identified in the initial stages of the disease. This work develops an accurate, fast, reliable end-to-end traditional machine learning (ML) model that can be implemented in real-time computer-aided diagnosis (CAD) applications for DFU diagnosis. We selected the plantar thermogram database because it may help detect an increase in plantar temperature and thereby permit early diagnosis. This method is less affected by environmental conditions, such as smoke and weather. To extract features invariant to translation, rotation, and scaling transformation, we use the Scale Invariant Feature Transform (SIFT) and Speeded Up Robust Features (SURF) methods combined with the Bag Of Features (BOF) technique. We used different pretrained deep learning (DL) networks to compare ML models trained with DL and handcrafted features. This research is novel since no previous studies have used traditional ML algorithms for the diagnosis of DFU from thermal images, nor have they used SIFT, SURF, or BOFtechniques. In addition, we use direct temperature files of each foot, later mapping them onto images to obtain accurate temperature distributions. Conventional ML classifiers are preferred in the final stage for binary classification between normal and DFU. The proposed model achieves 97.81% classification accuracy using a support vector machine (SVM) classifier trained with the SURF-BOF technique, along with 97.81% sensitivity, 97.9% precision, and a 0.9995 Area under the ROC curve (AUC) for DFU classification using thermal images.

Fusion of handcrafted and deep convolutional neural network features for effective identification of diabetic foot ulcer

SummaryAmong all diabetic‐related complications, the diabetic foot ulcer (DFU) is severe, demanding serious attention, and timely treatment. The purpose of the present study was to conduct features fusion of machine learning (ML) based handcrafted low‐level and convolutional neural networks (CNNs) based high‐level features for improving automatic diagnosis of DFU. A standard image dataset containing 1038 abnormal (DFU) and 641 normal color skin patches has been used for experimental evaluation. Handcrafted features are extracted to uncover the edge, color, shape, and texture information from the images. Also, a new CNN architecture has been proposed based on deeper residual blocks for extracting high‐level features. Features fusion with several ML classifiers like logistic regression classifier, support vector machine, gradient boosting, and artificial neural network have shown improved DFU identification results compared to the individual feature categories. Thereby, LRC outperformed the state‐of‐the‐art results for all evaluation metrics by achieving 95.23% sensitivity, 95.37% F1‐score, and 96.50% area under the curve (AUC) value. Such impressive experimental observations suggest that the proposed approach is expected to provide efficient decision support to medical practitioners, thereby improving patient care.

Enhanced Expression of miR-34c in Peripheral Plasma Associated with Diabetic Foot Ulcer in Type 2 Diabetes Patients.

ObjectiveTo explore the correlation between the expression of miR-34c in peripheral blood of patients with type 2 diabetes mellitus (T2DM) and the onset of diabetic foot ulcer (DFU) and diabetic foot osteomyelitis (DFO).MethodsSixty newly diagnosed patients with T2DM without DFU (T2DM group), 112 T2DM patients with DFU (DFU group) and 60 controls with normal glucose tolerance (NC group). The DFU group patients were subdivided into DFO (n=64) and NDFO (n=48) groups. Quantitative real-time PCR (qRT-PCR) method was used to determine miR-34c expression levels in the peripheral blood of subjects to analyze the clinical characteristics of DFU and DFO risk factors.ResultsMiR-34c expression level in the T2DM group was marked higher than the NC group [2.99 (1.45–6.22) vs 1.01 (0.89–1.52)] (P < 0.05). However, the expression level of miR-34c in the DFU group was significantly higher than the T2DM group [9.65 (6.15–18.63) vs 2.99 (1.45–6.22)] (P < 0.01). Compared with the NDFO group, the expression level of miR-34c in the DFO group was also obviously increased [13.46 (8.89–19.11) vs 6.02 (5.93–14.72)] (P < 0.01). The expression level of miR-34c in DFU patients was positively correlated with the amputation rate of foot ulcers (P=0.030) and was negatively correlated with the healing rate of foot ulcers after eight weeks (P=0.025). Multifactorial logistic regression analysis showed that increased expression of miR-34c was an independent risk factor for DFU and DFO (ORDFU=3.47, ORDFO=4.25, P < 0.01). Meanwhile, the ROC curve analysis indicated that the AUC of miR-34c for the diagnosis of DFU and DFO was 0.803 and 0.904, the optimum sensitivity being was 100% and 98.7%, the optimum specificity was 98.4% and 98.4%, respectively.ConclusionThe increased expression of miR-34c in peripheral blood of T2DM patients is closely related to the occurrence, development and prognosis of DFU and DFO.

Sedentary behaviour is an independent predictor of diabetic foot ulcer development: An 8-year prospective study

AimsTo prospectively explore the association between sedentary time (SED-time) and the development of diabetic foot ulcer (DFU) in people with diabetic peripheral neuropathy (DPN). Methods175 DPN individuals who attended the annual evaluation for the SAMBA Study (2012–2019) were included. Main outcome measure was the first diagnosis of DFU. SED-time was measured by the PAS 2.1 questionnaire. Nerve function was evaluated by nerve conduction studies. Vascular function was assessed by Ankle-brachial index (ABI) and pedal pulses. Foot deformity and skin dryness were examined by visual inspection. Results62 participants (35.5%) developed a DFU during the study. SED-time was significantly higher in people who developed DFUs (12.8 ± 3.0 vs 9.4 ± 3.1 h/day). Logistic regression showed that among several nervous (motor amplitude, OR 0.33, 95% CI, 0.18–0.60; sensory amplitude, 0.85, 0.77–0.94) and vascular parameters (ABI, 0.23, 0.1–0.61; pedal pulses, 2.81, 0.12–0.63) and foot characteristics (deformity, 2.63, 1.30–5.32; skin dryness, 2.04, 0.95–4.37), SED-time was one of the strongest variables contributing to the development of DFUs (2.95, 1.45–6.44). ConclusionsSED-time is an independent predictor of the risk of DFU in people with DPN. The monitoring of SED-time with strategies aimed at reducing it should be included in the standard care of diabetic patients.

Serum and exosomal hsa_circ_0000907 and hsa_circ_0057362 as novel biomarkers in the early diagnosis of diabetic foot ulcer.

Diabetic foot ulcer (DFU) is a serious chronic complication leading to disability and death in patients suffering from diabetes. Currently, there is no effective marker for its early diagnosis. The aim of this study is to analyze the difference of circRNA expression profiles between DFU and normal human wounds (NHW) and to screen serum biomarkers for the early diagnosis of DFU. Differentially expressed circRNAs were screened by bioinformatics analysis, using GSE114248 chip data downloaded from GEO database, including 5 pairs of tissue samples from DFU patients and NHW cases. Accordingly, 20 cases of DFU (Wagner grade 0~2), 20 non-DFU diabetes and 20 healthy controls were selected in the screening test, and the total RNAs of serum and serum-derived exosomes were extracted. The screened circRNAs were verified in the third largest cohort, and the ROC curves were drawn to assess the diagnostic efficiency. As discovered by experiment, there were a total of 67 circRNAs presented differential expressions between the two groups, with 28 circRNAs upregulated and 39 circRNAs downregulated in DFU group. Two types of circRNAs, hsa_circ_0000907 and hsa_circ_0057362, were selected as candidate biomarkers in current study and validated in a large cohort. The AUCs of serum hsa_circ_0000907 and hsa_circ_0057362 to diagnose early DFU were 0.9389 and 0.8792, respectively, and the AUCs of exosomal hsa_circ_0000907 and hsa_circ_0057362 to diagnose early DFU were 0.8783 and 0.8481, respectively. Furthermore, the expressions of serum hsa_circ_0000907 and hsa_circ_0057362 were negatively correlated with ankle brachial index (ABI) and transcutaneous oxygen pressure (TcPO2) in DFU patients. Serum and exosomal hsa_circ_0000907 and hsa_circ_0057362, especially hsa_circ_0000907, have novel diagnostic capabilities in the early diagnosis of DFU.

Evaluation of Factors Affecting the Severity of Diabetic Foot Ulcer in Patients with Diabetes Referred to a Diabetes Centre in Kermanshah.

IntroductionDiabetes mellitus is a metabolic disease characterized by high blood sugar (BS) levels and the change in the metabolism of lipids, carbohydrates, and insulin resistance, and is one of the main causes of disability and mortality worldwide. Among the different types of complications, which have many negative effects on personal and social life, diabetic foot ulcer (DFU) is very important. This study aims to investigate the factors affecting the severity of DFU among patients with diabetes.MethodsThe study participants included 190 diabetic patients with a diagnosis of DFU. Data were collected using a two-part questionnaire for self-care awareness and functions in diabetic patients and Wagner’s scale. The questionnaire was answered in cooperation with patients and the Wagner’s score was estimated by a wound supervisor in the diabetes center.ResultsThere was 109 women (57.4%). Twenty-six patients had other diabetic complications as well as DFU. The average score of awareness in patients was 6.99±2.76 and the function was 62.22±9.92. The results found a direct relation between the age and the duration of illness with the score of the patient’s awareness (P=0.008, P=0.000). There was also a direct relation between the level of education with score of awareness and the score of function in self-care (P=0.000, P=0.000), but the statistical results did not find any relation between awareness and the function in self-care of patients with the severity of DFU (P>0.05).DiscussionThere was no relation between the self-care awareness and function with severity of DFU (P>0.05) that can be due to the more relation between DFU severity with hygiene and physical factors after the disease and the effect of awareness and function would be only in the incidence of the DFU.ConclusionAwareness and function of patients in self-care is less than average. Increasing awareness of patients and empowering them through appropriate training can be effective in preventing diabetic foot ulcers.

To compare the efficacy of topical phenytoin over conventional wound care (5% povidone-iodine) in diabetic ulcer

Background: Diabetic foot ulcers is one of the common complication of diabetes mellitus. It has become a significant health care problem affecting 15%. In this study Phenytoin is used for diabetic foot ulcers comparing its efficacy over conventional dressing. Methodology: This is a prospective study of 70 patients admitted in JSS hospital, with diagnosis of Diabetic foot ulcer between 2017-2019. They were divided into two group after a detailed clinical examination, and appropriate work up satisfying inclusion and exclusion criteria. One group underwent phenytoin dressing and other group conventional dressing and were assessed on 14th day. Results: This study observed that group for which Phenytoin dressing was done underwent SSG or secondary suturing in

Non-Targeted Metabolomic Analysis Reveals Serum Phospholipid Alterations in Patients with Early Stages of Diabetic Foot Ulcer.

Diabetic foot ulcer (DFU) is a common complication of type 2 diabetes mellitus (T2DM) characterized by ulcer formation, which can lead to the amputation of lower extremities. However, the metabolic alterations related to this complication are not completely elucidated. Therefore, we carried out a metabolomic analysis of serum samples obtained from T2DM adult patients diagnosed with diabetic foot ulcer in a cross-sectional, observational, and comparative study. Eighty-four volunteers were classified into the following groups: without T2DM (control group, n = 30) and with T2DM and different stages of diabetic foot ulcer according to Wagner-Meggitt classification system: DFU G0 (n = 11), DFU G1 (n = 14), DFU G2 (n = 16), and DFU G3 (n = 13). The non-target metabolomic profile followed by chemometric analysis revealed that lysophosphatidylethanolamine (16:1) could be proposed as key metabolite related to the onset of diabetic foot ulcer; however, this phospholipid was not affected by diabetic foot ulcer progression. Therefore, further studies are necessary to validate these phospholipids as biomarker candidates for the early diagnosis of diabetic foot ulcer in T2DM patients.

Pro-Calcitonin, Erythrocyte Sedimentation Rate and C - reactive Protein in Predicting Diabetic Foot Ulcer Characteristics; a Cross Sectional Study.

Considering the importance of early diagnosis of diabetic foot ulcers and its complications, this study aimed to evaluate the accuracy of erythrocyte sedimentation rate (ESR), C - reactive protein (CRP), and pro-calcitonin (PCT) in predicting the ulcer class, osteomyelitis, and peripheral arterial disease (PAD). This cross-sectional study was performed on 200 consecutive patients suffering from diabetic foot ulcer who were referred to Infectious Disease Ward. The levels of PCT, ESR, and CRP were measured for all patients and the screening performance characteristics of each marker in predicting the ulcer class, osteomyelitis, and PAD was calculated. The levels of PCT, ESR and CRP were significantly higher in patients with class IV foot ulcer compared to those with class III ulcers (p<0.001). Patients with evidence of osteomyelitis had significantly higher level of PCT, ESR and CRP. The best cutoff points of PCT, ESR and CRP in predicting osteomyelitis were 0.35 ng/ml (86.1% sensitivity, 45.3% specificity), 56.5 mm/hours (95.8% sensitivity, and 50.0% specificity) and 44 mg/ml (90.3% sensitivity, 57.0% specificity), respectively. The presence of PAD was significantly associated with increased levels of the three biomarkers. The best cutoff values for PCT, ESR and CRP in predicting PAD were 0.45 (70.8% sensitivity, 71.7% specificity), 61.5 (83.3% sensitivity, 52.0% specificity) and 49 (83.3% sensitivity, 63.8% specificity), respectively. Based on the findings of the present study, although the accuracy of PCT, ESR, and CRP in predicting the severity of diabetic foot ulcers was fair, increase in the three parameters can predict the occurrence of osteomyelitis and PAD following diabetic food development with good accuracy and acceptable sensitivity.

A study of risk factors for patients with Diabetic foot ulcer

Background: Peripheral neuropathy and peripheral vascular diseases are the important causes of non-traumatic lower limb amputation. The risk of amputation among diabetic patients increases by two to four folds with the advancement of age and duration of diabetes.It has also been proven by many longitudinal epidemiological studies that among diabetic patients, the life time foot ulcer risk is about 25%, thereby accounting for two thirds of all non-traumatic amputations. Clinical guidelines recommend that all patients with diabetes should be screened annually to establish their risk of foot ulceration. Aim: To ascertain the risk factors leading to amputation for patients with diabetic foot ulcer. Materials and method: The present study was conducted in the Department of General Surgery of Melmaruvathur Adhiparasakthi institute of medical sciences. Melmaruvathur. For our study, we selected 200 patients admitted to the surgical ward with diagnosis of diabetic foot ulcer. History of diabetic status of patient, whether patient was a undetected case or a known diabetic, if known the duration of the disease, whether patient was on regular or irregular treatment (diet/oral/drugs/insulin) were recorded. Lab tests of each patient were conducted for hemoglobin, TLC, DLC, ESR, blood urea, serum creatinine and blood sugar. All the cases were managed following conservative and surgical approach. Results: A total of 200 patients were present in the study group. The mean of the subjects was 49.28 + 6.88 years. Out of 200 patients, 46 were females and 154 were males. We observed that 54 patients were undetected at the time of admission at hospital. Majority of patients (n=46) had duration of diabetes from 5-10 years. 38 patients had duration of diabetes less than 4 years, 10 patients had duration of diabetes from 11-15 years. Most of the patients present with more than one lesion. Only major lesion is considered here. Ulcer was the major lesion seen in present series being present in 144 patients. Conclusion: We conclude that Routine foot care should be available to every patient with diabetes ideally, but the reality of most of these patient slack adequate knowledge and resources resulting in the absence of such care.