Can a combination of lifestyle and clinical characteristics explain the presence of foot ulcer in patients with diabetes?

The relationship between dietary phytochemical index and novel anthropometric indices and the severity of diabetic foot ulcers in adults with type 2 diabetes: a cross-sectional study

BACKGROUND

Research on the relationship between dietary phytochemical intake and the anthropometric indices as well as the diabetic foot ulcers (DFUs) remains inconsistent. We aimed to investigate the associations of dietary phytochemical index (DPI) with the novel anthropometric indices and the severity of DFUs.

METHODS

This cross-sectional study was conducted on 339 adults with type 2 diabetes. Dietary intake was assessed using three 24-hour dietary recalls. To quantify the phytochemical content of the diet, the DPI estimation was done through an equation proposed by McCarty. The International Working Group on the Diabetic Foot (IWGDF) criteria and Wagner classification system were applied to assess DFUs. New anthropometric indices including a body shape index (ABSI), body roundness index (BRI) and abdominal volume index (AVI) were calculated based on formulas. We employed analysis of variance (ANOVA), analysis of covariance (ANCOVA) and logistic regression to explore associations between DPI and the anthropometric indices and DFU variables.

RESULTS

Our results revealed no significant association between DPI and the foot ulcer indices, following adjusting for the possible covariates. Furthermore, we also examined the relationship between diabetic neuropathy, as measured by monofilament score, and the DPI. Similarly, we did not find any substantial relationship between the DPI and monofilament score (OR: 1.18; 95% CI: 0.66-2.09; Ptrend = 0.56), as well as biochemical indices. Our analysis did not reveal any significant associations between the DPI and ABSI (OR: 0.70; 95% CI: 0.35-1.38; Ptrend = 0.30), BRI (OR: 0.80; 95% CI: 0.33-1.95; Ptrend = 0.59), and AVI (OR: 1.99; 95% CI: 0.92-4.33; Ptrend = 0.08).

CONCLUSIONS

Our study revealed no significant links between the DPI and foot ulcer indices, neuropathy measures, and anthropometric indices. These findings imply that factors beyond dietary phytochemical intake may exert greater influence on the development of foot ulcers in diabetes.

Understanding and treating diabetic foot ulcers: Insights into the role of cutaneous microbiota and innovative therapies

Background

Notoriously known as the silent pandemic, chronic, non-healing diabetic foot ulcers (DFUs), pose a significant rate of incidence for amputation and are a major cause of morbidity. Alarmingly, the treatment and management strategies of chronic wounds represent a significant economic and health burden as well as a momentous drain on resources with billions per annum being spent in the US and UK alone. Defective wound healing is a major pathophysiological condition which propagates an acute wound to a chronic wound, further propelled by underlying conditions such as diabetes and vascular complications which are more prevalent amongst the elderly. Chronic wounds are prone to infection, which can exacerbate the condition, occasionally resulting in amputation for the patient, despite the intervention of modern therapies. However, amputation can only yield a 5-year survival rate for 50% of patients, highlighting the need for new treatments for chronic wounds.

Findings

The dynamic cutaneous microbiota is comprised of diverse microorganisms that often aid wound healing. Conversely, the chronic wound microbiome consists of a combination of common skin commensals such as Staphylococcus aureus and Staphylococcus epidermidis, as well as the opportunistic pathogen Pseudomonas aeruginosa. These bacteria have been identified as the most prevalent bacterial pathogens isolated from chronic wounds and contribute to prolific biofilm formation decreasing the efficiency of antimicrobials and further perpetuating a hyper-inflammatory state.

Discussion and Conclusion

Here, we review recent advances and provide a new perspective on alternative treatments including phage and microbiome transplant therapies and how the definitive role of the cutaneous microbiota impacts the aetiology of DFUs.

What characteristics are most important in stratifying patients into groups with different risk of diabetic foot ulceration?

AIMS/INTRODUCTION

This study aimed to assess if patients can be divided into different strata, and to explore if these correspond to the risk of diabetic foot complications.

MATERIALS AND METHODS

A set of 28 demographic, vascular, neurological and biomechanical measures from 2,284 (1,310 men, 974 women) patients were included in this study. A two-step cluster analysis technique  was utilised to divide the patients into groups, each with similar characteristics.

RESULTS

Only two distinct groups: group 1 (n = 1,199; 669 men, 530 women) and group 2 (n = 1,072; 636 men, 436 women) were identified. From continuous variables, the most important predictors of grouping were: ankle vibration perception threshold (16.9 ± 4.1 V vs 31.9 ± 7.4 V); hallux vibration perception threshold (16.1 ± 4.7 V vs 33.1 ± 7.9 V); knee vibration perception threshold (18.2 ± 5.1 V vs 30.1 ± 6.5 V); average temperature sensation threshold to cold (29.2 ± 1.1°C vs 26.7 ± 0.7°C) and hot (35.4 ± 1.8°C vs 39.5 ± 1.0°C) stimuli, and average temperature tolerance threshold to hot stimuli at the foot (43.4 ± 0.9°C vs 46.6 ± 1.3°C). From categorical variables, only impaired sensation to touch was found to have importance at the highest levels: 87.4% of those with normal sensation were in group 1; whereas group 2 comprised 95.1%, 99.3% and 90.5% of those with decreased, highly-decreased and absent sensation to touch, respectively. In addition, neuropathy (monofilament) was a moderately important predictor (importance level 0.52) of grouping with 26.2% of participants with neuropathy in group 1 versus 73.5% of participants with neuropathy in group 2. Ulceration during follow up was almost fivefold higher in group 2 versus group 1.

CONCLUSIONS

Impaired sensations to temperature, vibration and touch were shown to be the strongest factors in stratifying patients into two groups with one group having almost 5-fold risk of future foot ulceration compared to the other.

Prevalence and risk factors for diabetic foot complications among people living with diabetes in Harare, Zimbabwe: a cross-sectional study

BACKGROUND

Diabetic foot disease (DF) is a common diabetes-related complication; however, the prevalence and associated risk factors for DF are not well characterised among people living with diabetes (PLWD) in Zimbabwe. This may suggest the unavailability of adequate strategies to diagnose and treat DF in the country. This study aimed to determine the prevalence of DF and associated risk factors for PLWD in Harare, Zimbabwe.

METHODS

This was a cross-sectional study, employing a quantitative approach. In total, 352 PLWD were recruited from 16 primary care clinics in Harare. Sociodemographic and clinical data were collected via face-to-face interviews and clinical records reviews. The DF screening included an evaluation for peripheral neuropathy, ankle-brachial index (ABI), ulceration, and amputation. Self-administered questionnaires were used to assess knowledge, attitudes, and practices (KAPs), and KAP was scored using Bloom's cut-off. Chi-Square goodness-of-fit tests were performed, and regression analyses were used for association analysis. The threshold for significance was p < 0.05.

RESULTS

This group included 82 men and 279 women, with a combined mean age of 57.9 ± 14 years. Twenty one (~ 26%) men and 41 (15%) women had type 1 diabetes. The diabetes type distribution significantly differed by gender (p < 0.001). Oral hypoglycaemics (71%) were most commonly administered for management. DF was observed in 53% (95% CI = 50-56) of PLWD. Other DF symptoms observed were abnormal ABI (53%), peripheral neuropathy (53%), foot ulceration (17%) and amputation (3%). Peripheral neuropathy increased the risk of ulceration (OR = 1.7; 95% CI = 1.1-2.6; p = 0.019), while insulin use was protective against amputation (OR = 0.1; 95% CI = 0.1-0.9; p = 0.049). Most (87%) of the participants demonstrated good DF knowledge and the importance of adhering to medication to prevent DF. However, 96% did not know that smoking was a risk factor for DF. Nearly two-thirds (63%) demonstrated poor attitudes and practices. Poor attitudes and practices were not predictors of DF ulceration risk (p > 0.05).

CONCLUSION

This study showed that there was a high prevalence of DF (53%) in PLWD in Zimbabwe, and insulin use was protective against DF. There is an urgent need for policy revisions to include foot screening in routine primary care and increasing insulin use for PLWD to prevent complications such as DF as an integral part of primary care.

Development of predictive nomograms clinical use to quantify the risk of diabetic foot in patients with type 2 diabetes mellitus

Objective

The aim of the study was to explore the risk factors for diabetic foot disease in patients with type 2 diabetes mellitus and to establish and verify the nomogram model of DF risk in patients with T2DM.

Methods

The clinical data of 705 patients with type 2 diabetes who were hospitalized in our hospital from January 2015 to December 2022 were analyzed retrospectively. According to random sampling, the patients were divided into two groups: the training set (DF = 84; simple T2DM = 410) and the verification set (DF = 41; simple T2DM = 170). Univariate and multivariate logistic regression analysis was used to screen the independent risk factors for DF in patients with T2DM in the training set. According to the independent risk factors, the nomogram risk prediction model is established and verified.

Results

Logistic regression analysis showed age (OR = 1.093, 95% CI 1.062-1.124, P <0.001), smoking history (OR = 3.309, 95% CI 1.849-5.924, P <0.001), glycosylated hemoglobin (OR = 1.328, 95% CI 1.173-1.502, P <0.001), leukocyte (OR = 1.203, 95% CI 1.076-1.345, and LDL-C (OR = 2.002, 95% CI 1.463-2.740), P <0.001) was independent risk factors for T2DM complicated with DF. The area of the nomogram model based on the above indexes under the ROC curve of the training set and the verification set is 0.827 and 0.808, respectively; the correction curve shows that the model has good accuracy; and the DCA results show that when the risk threshold is between 0.10-0.85 (training set) and 0.10-0.75 (verification set), the clinical practical value of the model is higher.

Conclusion

The nomogram model constructed in this study is of high value in predicting the risk of DF in patients with T2DM and is of reference value for clinicians to identify people at high risk of DF and provide them with early diagnosis and individual prevention.

Prediction of Foot Ulcers Using Artificial Intelligence for Diabetic Patients at Cairo University Hospital, Egypt

Introduction

In Egypt, diabetic foot ulcers markedly contribute to the morbidity and mortality of diabetic patients. Accurately predicting the risk of diabetic foot ulcers could dramatically reduce the enormous burden of amputation.

Objective

The aim of this study is to design an artificial intelligence-based artificial neural network and decision tree algorithms for the prediction of diabetic foot ulcers.

Methods

A case-control study design was utilized to fulfill the aim of this study. The study was conducted at the National Institute of Diabetes and Endocrine Glands, Cairo University Hospital, Egypt. A purposive sample of 200 patients was included. The tool developed and used by the researchers was a structured interview questionnaire including three parts: Part I: demographic characteristics; Part II: medical data; and Part III: in vivo measurements. Artificial intelligence methods were used to achieve the aim of this study.

Results

The researchers used 19 significant attributes based on medical history and foot images that affect diabetic foot ulcers and then proposed two classifiers to predict the foot ulcer: a feedforward neural network and a decision tree. Finally, the researchers compared the results between the two classifiers, and the experimental results showed that the proposed artificial neural network outperformed a decision tree, achieving an accuracy of 97% in the automated prediction of diabetic foot ulcers.

Conclusion

Artificial intelligence methods can be used to predict diabetic foot ulcers with high accuracy. The proposed technique utilizes two methods to predict the foot ulcer; after evaluating the two methods, the artificial neural network showed a higher improvement in performance than the decision tree algorithm. It is recommended that diabetic outpatient clinics develop health education and follow-up programs to prevent complications from diabetes.

Diabetic foot ulcer disease in African continent: 'From clinical care to implementation' - Review of diabetic foot in last 60 years - 1960 to 2020

The prevalence of diabetes mellitus is increasing globally and the greatest potential increases in diabetes will occur in Africa. Data suggest that these increases is associated with rapid demographic, sociocultural and economic transitions. There will be a parallel increase in the complications of diabetes and among the various complications those related to diabetic foot disease are associated with the highest morbidity and mortality. Diabetic Peripheral neuropathy (DPN) is the most common cause of diabetic foot complications in African countries; however, peripheral arterial disease (PAD) appears to increase, possibly a result of rising urbanization. Search done for the past six decades (1960 to 2020) on all foot complications. Rates of complications of diabetic foot in last six decades varied by country as follow: DPN: 4-90%; PAD: 0-77%; foot ulcers: 4-61%; amputation rates: 3-61% and high mortality rates reaching to 55%, patients who presented late with infection and gangrene. Educational and prevention programmes are required to curb the growing complications of diabetic foot ulcers in Africa among patients and health care workers. Secondly, it is imperative that governments across the African continent recognise the clinical and public health implications of diabetic foot disease in persons with diabetes.

Predictors of Foot Ulcers Among Diabetic Patients at a Tertiary Care Center, Egypt

BACKGROUND AND PURPOSE

Diabetic foot ulcers (DFUs) markedly contribute to morbidity and mortality of diabetic patients. Hence, this study was conducted to investigate the predictors of foot ulcers among Egyptian diabetic patients.

METHODS

A case-control study was conducted among 488 diabetic patients attending the inpatient departments and outpatient clinics at the National Diabetes Institute in Egypt. A pretested data collection sheet was designed to collect and record the following: socio-demographic data, diabetic history and lifestyle characteristics, recorded comorbidities, and the results of foot examination.

RESULTS

Significant positive predictors of DFUs on multivariate logistic regression analysis included presence of three or more comorbidities; two or more diabetic complications; callus; and flatfoot. Significant protective (negative) predictors were management of diabetes by diet, oral hypoglycemic drugs (OHGs), and insulin; and intact vibration sense.

CONCLUSION

Significant positive predictors of DFUs on multivariate analysis were presence of three or more comorbidities, two or more diabetic complications, callus and flatfoot, while protective predictors were management of diabetes by diet, OHGs, and insulin; and intact vibration sense. Hence, close monitoring should be provided to diabetic patients with comorbidities and complications to reduce the risk of DFUs.

Predicting the risk of future diabetic foot ulcer occurrence: a prospective cohort study of patients with diabetes in Tanzania

OBJECTIVES

The aim of this study was to identify the parameters that predict the risk of future foot ulcer occurrence in patients with diabetes.

RESEARCH DESIGN AND METHODS

1810 (male (M)/female (F): 1012/798) patients, with no foot ulcer at baseline, participated in this study. Data from a set of 28 parameters were collected at baseline. During follow-up, 123 (M/F: 68/55) patients ulcerated. Survival analyses together with logistic regression were used to identify the parameters that could predict the risk of future diabetic foot ulcer occurrence.

RESULTS

A number of parameters (HR (95% CI)) including neuropathy (2.525 (1.680 to 3.795)); history of ulceration (2.796 (1.029 to 7.598)); smoking history (1.686 (1.097 to 2.592)); presence of callus (1.474 (0.999 to 2.174)); nail ingrowth (5.653 (2.078 to 15.379)); foot swelling (3.345 (1.799 to 6.218)); dry skin (1.926 (1.273 to 2.914)); limited ankle (1.662 (1.365 to 2.022)) and metatarsophalangeal (MTP) joint (2.745 (1.853 to 4.067)) ranges of motion; and decreased (3.141 (2.102 to 4.693)), highly decreased (5.263 (1.266 to 21.878)), and absent (9.671 (5.179 to 18.059)) sensation to touch; age (1.026 (1.010 to 1.042)); vibration perception threshold (1.079 (1.060 to 1.099)); duration of diabetes (1.000 (1.000 to 1.000)); and plantar pressure at the first metatarsal head (1.003 (1.001 to 1.005)), temperature sensation (1.019 (1.004 to 1.035)) and temperature tolerance (1.523 (1.337 to 1.734)) thresholds to hot stimuli and blood sugar level (1.027 (1.006 to 1.048)) were all significantly associated with increased risk of ulceration. However, plantar pressure underneath the fifth toe (0.990 (0.983 to 0.998)) and temperature sensation (0.755 (0.688 to 0.829)) and temperature tolerance (0.668 (0.592 to 0.0754)) thresholds to cold stimuli showed to significantly decrease the risk of future ulcer occurrence. Multivariate survival model indicated that nail ingrowth (4.42 (1.38 to 14.07)); vibration perception threshold (1.07 (1.04 to 1.09)); dry skin status (4.48 (1.80 to 11.14)); and temperature tolerance threshold to warm stimuli (1.001 (1.000 to 1.002)) were significant predictors of foot ulceration risk in the final model. The mean time to ulceration was significantly (p<0.05) shorter for patients with: dry skin (χ²=11.015), nail ingrowth (χ²=14.688), neuropathy (χ²=21.284), or foot swelling (χ²=16.428).

CONCLUSION

Nail ingrowth and dry skin were found to be strong indicators of vulnerability of patients to diabetic foot ulceration. Results highlight that assessments of neuropathy in relation to both small and larger fiber impairment need to be considered for predicting the risk of diabetic foot ulceration.

Incidence of Diabetic Foot Ulcer and Its Predictors Among Diabetes Mellitus Patients at Felege Hiwot Referral Hospital, Bahir Dar, Northwest Ethiopia: A Retrospective Follow-Up Study

AIM

The incidence of a diabetic foot ulcer (DFU) is increasing over the previous decade with an increasing prevalence of diabetes mellitus (DM). Despite the increasing incidence of DFU, there is limited information about the problem in Ethiopia. Hence, this study aimed to investigate the incidence of DFU and its predictors among newly diagnosed DM patients who were on follow-up at Felege Hiwot Referral Hospital.

METHODS

Institution-based retrospective follow-up study was conducted at Felege Hiwot Referral Hospital among newly diagnosed DM patients from January 1, 2009, to December 31, 2018. A simple random sampling method was used to select 401 study participants from a total of 723 eligible population. Data was entered using Epi-Data version 3.1 and exported to STATA version 14 for analysis. The incidence rate was estimated using person-years of observation and Nelson-Aalen cumulative hazard function, showing the cumulative probability of diabetic foot ulcer, was done. The best model (Gompertz) was selected using the AIC and log-likelihood method. Hazard ratio (HR) with its 95% confidence interval was computed and variables having a p-value less than 0.05 in the multivariable model were considered to be significantly associated with DFU.

RESULTS

A total of 387 patients were followed retrospectively for a median follow-up time of 95 months. Out of all, 66 (17.05%) patients developed DFU with an incidence rate of 4 cases per 100 person-years of observation. Diabetic nephropathy (adjusted hazard ratio (AHR) = 2.37, 95% CI: 1.33-54.24), diabetic retinopathy (AHR = 5.56, 95% CI: 2.64-11.74), and increased body mass index (AHR = 1.13, 95% CI: 1.01-1.27) were found to increase the hazard of DFU.

CONCLUSION

The incidence of DFU was relatively high. Diabetic nephropathy, diabetic retinopathy, and body mass index were its significant predictors. Therefore, close monitoring of patients with co-morbidities and increased body mass index should be considered to reduce DFU.