Prediction Of Diabetic Foot Ulceration Research Articles

Risk assessments and structured care interventions for prevention of foot ulceration in diabetes: development and validation of a prognostic model.

Diabetes-related foot ulcers give rise to considerable morbidity, generate a high monetary cost for health and social care services and precede the majority of diabetes-related lower extremity amputations. There are many clinical prediction rules in existence to assess risk of foot ulceration but few have been subject to validation. Our objectives were to produce an evidence-based clinical pathway for risk assessment and management of the foot in people with diabetes mellitus to estimate cost-effective monitoring intervals and to perform cost-effectiveness analyses and a value-of-information analysis. We developed and validated a prognostic model using predictive modelling, calibration and discrimination techniques. An overview of systematic reviews already completed was followed by a review of randomised controlled trials of interventions to prevent foot ulceration in diabetes mellitus. A review of the health economic literature was followed by the construction of an economic model, an analysis of the transitional probability of moving from one foot risk state to another, an assessment of cost-effectiveness and a value-of-information analysis. The effects of simple and complex interventions and different monitoring intervals for the clinical prediction rules were evaluated. The main outcome was the incidence of foot ulceration. We compared the new clinical prediction rules in conjunction with the most effective preventative interventions at different monitoring intervals with a 'treat-all' strategy. Data from an electronic health record for 26,154 people with diabetes mellitus in one Scottish health board were used to estimate the monitoring interval. The Prediction Of Diabetic foot UlcerationS (PODUS) data set was used to develop and validate the clinical prediction rule. We searched for eligible randomised controlled trials of interventions using search strategies created for Ovid® (Wolters Kluwer, Alphen aan den Rijn, the Netherlands), MEDLINE, EMBASE and the Cochrane Central Register of Controlled Trials. Randomised controlled trials in progress were identified via the International Standard Randomised Controlled Trial Number Registry and systematic reviews were identified via PROSPERO. Databases were searched from inception to February 2019. The clinical prediction rule was found to accurately assess the risk of foot ulceration. Digital infrared thermometry, complex interventions and therapeutic footwear with offloading devices were found to be effective in preventing foot ulcers. The risk of developing a foot ulcer did not change over time for most people. We found that interventions to prevent foot ulceration may be cost-effective but there is uncertainty about this. Digital infrared thermometry and therapeutic footwear with offloading devices may be cost-effective when used to treat all people with diabetes mellitus regardless of their ulcer risk. The threats to the validity of the results in some randomised controlled trials in the review and the large number of missing data in the electronic health record mean that there is uncertainty in our estimates. There is evidence that interventions to prevent foot ulceration are effective but it is not clear who would benefit most from receiving the interventions. The ulceration risk does not change over an 8-year period for most people with diabetes mellitus. A change in the monitoring interval from annually to every 2 years for those at low risk would be acceptable. Improving the completeness of electronic health records and sharing data would help improve our knowledge about the most clinically effective and cost-effective approaches to prevent foot ulceration in diabetes mellitus. This study is registered as PROSPERO CRD42016052324. This project was funded by the National Institute for Health Research (NIHR) Health Technology Assessment programme and will be published in full in Health Technology Assessment; Vol. 24, No. 62. See the NIHR Journals Library website for further project information.

Prediction of Diabetic Foot Ulceration: The Value of Using Microclimate Sensor Arrays.

Accurately predicting the risk of diabetic foot ulceration (DFU) could dramatically reduce the enormous burden of chronic wound management and amputation. Yet, the current prognostic models are unable to precisely predict DFU events. Typically, efforts have focused on individual factors like temperature, pressure, or shear rather than the overall foot microclimate. A systematic review was conducted by searching PubMed reports with no restrictions on start date covering the literature published until February 20, 2019 using relevant keywords, including temperature, pressure, shear, and relative humidity. We review the use of these variables as predictors of DFU, highlighting gaps in our current understanding and suggesting which specific features should be combined to develop a real-time microclimate prognostic model. The current prognostic models rely either solely on contralateral temperature, pressure, or shear measurement; these parameters, however, rarely reach 50% specificity in relation to DFU. There is also considerable variation in methodological investigation, anatomical sensor configuration, and resting time prior to temperature measurements (5-20 minutes). Few studies have considered relative humidity and mean skin resistance. Very limited evidence supports the use of single clinical parameters in predicting the risk of DFU. We suggest that the microclimate as a whole should be considered to predict DFU more effectively and suggest nine specific features which appear to be implicated for further investigation. Technology supports real-time in-shoe data collection and wireless transmission, providing a potentially rich source of data to better predict the risk of DFU.

A systematic review and individual patient data meta-analysis of prognostic factors for foot ulceration in people with diabetes: the international research collaboration for the prediction of diabetic foot ulcerations (PODUS).

Annual foot risk assessment of people with diabetes is recommended in national and international clinical guidelines. At present, these are consensus based and use only a proportion of the available evidence. We undertook a systematic review of individual patient data (IPD) to identify the most highly prognostic factors for foot ulceration (i.e. symptoms, signs, diagnostic tests) in people with diabetes. Studies were identified from searches of MEDLINE and EMBASE. The electronic search strategies for MEDLINE and EMBASE databases created during an aggregate systematic review of predictive factors for foot ulceration in diabetes were updated and rerun to January 2013. One reviewer applied the IPD review eligibility criteria to the full-text articles of the studies identified in our literature search and also to all studies excluded from our aggregate systematic review to ensure that we did not miss eligible IPD. A second reviewer applied the eligibility criteria to a 10% random sample of the abstract search yield to check that no relevant material was missed. This review includes exposure variables (risk factors) only from individuals who were free of foot ulceration at the time of study entry and who had a diagnosis of diabetes mellitus (either type 1 or type 2). The outcome variable was incident ulceration. Our search identified 16 cohort studies and we obtained anonymised IPD for 10. These data were collected from more than 16,000 people with diabetes worldwide and reanalysed by us. One data set was kept for independent validation. The data sets contributing IPD covered a range of temporal, geographical and clinical settings. We therefore selected random-effects meta-analysis, which assumes not that all the estimates from each study are estimates of the same underlying true value, but rather that the estimates belong to the same distribution. We selected candidate variables for meta-analysis using specific criteria. After univariate meta-analyses, the most clinically important predictors were identified by an international steering committee for inclusion in the primary, multivariable meta-analysis. Age, sex, duration of diabetes, monofilaments and pulses were considered most prognostically important. Meta-analyses based on data from the entire IPD population found that an inability to feel a 10-g monofilament [odds ratio (OR) 3.184, 95% confidence interval (CI) 2.654 to 3.82], at least one absent pedal pulse (OR 1.968, 95% CI 1.624 to 2.386), a longer duration of a diagnosis of diabetes (OR 1.024, 95% CI 1.011 to 1.036) and a previous history of ulceration (OR 6.589, 95% CI 2.488 to 17.45) were all predictive of risk. Female sex was protective (OR 0.743, 95% CI 0.598 to 0.922). It was not possible to perform a meta-analysis using a one-step approach because we were unable to procure copies of one of the data sets and instead accessed data via Safe Haven. The findings from this review identify risk assessment procedures that can reliably inform national and international diabetes clinical guideline foot risk assessment procedures. The evidence from a large sample of patients in worldwide settings show that the use of a 10-g monofilament or one absent pedal pulse will identify those at moderate or intermediate risk of foot ulceration, and a history of foot ulcers or lower-extremity amputation is sufficient to identify those at high risk. We propose the development of a clinical prediction rule (CPR) from our existing model using the following predictor variables: insensitivity to a 10-g monofilament, absent pedal pulses and a history of ulceration or lower-extremities amputations. This CPR could replace the many tests, signs and symptoms that patients currently have measured using equipment that is either costly or difficult to use. This study is registered as PROSPERO CRD42011001841. The National Institute for Health Research Health Technology Assessment programme.

A two-phase model of plantar tissue: a step toward prediction of diabetic foot ulceration.

A new computational model, based on the thermodynamically constrained averaging theory, has been recently proposed to predict tumor initiation and proliferation. A similar mathematical approach is proposed here as an aid in diabetic ulcer prevention. The common aspects at the continuum level are the macroscopic balance equations governing the flow of the fluid phase, diffusion of chemical species, tissue mechanics, and some of the constitutive equations. The soft plantar tissue is modeled as a two-phase system: a solid phase consisting of the tissue cells and their extracellular matrix, and a fluid one (interstitial fluid and dissolved chemical species). The solid phase may become necrotic depending on the stress level and on the oxygen availability in the tissue. Actually, in diabetic patients, peripheral vascular disease impacts tissue necrosis; this is considered in the model via the introduction of an effective diffusion coefficient that governs transport of nutrients within the microvasculature. The governing equations of the mathematical model are discretized in space by the finite element method and in time domain using the θ-Wilson Method. While the full mathematical model is developed in this paper, the example is limited to the simulation of several gait cycles of a healthy foot.

The influence of ambient temperature on foot temperature in patients with diabetic foot ulceration

BackgroundPatients with diabetic neuropathy exhibit a higher foot temperature than those without neuropathy and they are at risk for foot ulceration. Ambient temperature and foot ulceration additionally influence foot temperature in such patients. The aim of the study was to assess the influence of ambient temperature on foot temperature in patients with an ulcer on one of the feet. MethodsMiniature temperature data loggers were used for the monitoring of foot skin and ambient temperature. Twenty patients with diabetic neuropathy and ten healthy subjects were monitored for about 24h each. ResultsThe temperature of the foot with an ulcer correlates significantly with ambient temperature, with the slope of the regression line of 0.09. The temperature of the non-ulcerated foot also correlates significantly with ambient temperature, with the slope of 0.31, however the correlation coefficient and the slope are significantly higher than in the case of the foot with an ulcer. The difference of temperature of the foot with an ulcer and temperature of the foot without an ulcer correlates well with ambient temperature with the slope of −0.219. The temperatures of left and right feet were studied as a function of ambient temperature in healthy individuals and there were no statistically significant differences between correlation coefficients and slopes. ConclusionsIt is apparent that ambient temperature influences foot temperature even during foot ulceration. Thus ambient temperature should be taken into consideration in any application when foot temperatures are important, especially in the prediction of diabetic foot ulceration.

Protocol for a systematic review and individual patient data meta-analysis of prognostic factors of foot ulceration in people with diabetes: the international research collaboration for the prediction of diabetic foot ulcerations (PODUS)

BackgroundDiabetes–related lower limb amputations are associated with considerable morbidity and mortality and are usually preceded by foot ulceration. The available systematic reviews of aggregate data are compromised because the primary studies report both adjusted and unadjusted estimates. As adjusted meta-analyses of aggregate data can be challenging, the best way to standardise the analytical approach is to conduct a meta-analysis based on individual patient data (IPD).There are however many challenges and fundamental methodological omissions are common; protocols are rare and the assessment of the risk of bias arising from the conduct of individual studies is frequently not performed, largely because of the absence of widely agreed criteria for assessing the risk of bias in this type of review. In this protocol we propose key methodological approaches to underpin our IPD systematic review of prognostic factors of foot ulceration in diabetes.Review questions;1. What are the most highly prognostic factors for foot ulceration (i.e. symptoms, signs, diagnostic tests) in people with diabetes?2. Can the data from each study be adjusted for a consistent set of adjustment factors?3. Does the model accuracy change when patient populations are stratified according to demographic and/or clinical characteristics?MethodsMEDLINE and EMBASE databases from their inception until early 2012 were searched and the corresponding authors of all eligible primary studies invited to contribute their raw data. We developed relevant quality assurance items likely to identify occasions when study validity may have been compromised from several sources. A confidentiality agreement, arrangements for communication and reporting as well as ethical and governance considerations are explained.We have agreement from the corresponding authors of all studies which meet the eligibility criteria and they collectively possess data from more than 17000 patients. We propose, as a provisional analysis plan, to use a multi-level mixed model, using “study” as one of the levels. Such a model can also allow for the within-patient clustering that occurs if a patient contributes data from both feet, although to aid interpretation, we prefer to use patients rather than feet as the unit of analysis. We intend to only attempt this analysis if the results of the investigation of heterogeneity do not rule it out and the model diagnostics are acceptable.DiscussionThis review is central to the development of a global evidence-based strategy for the risk assessment of the foot in patients with diabetes, ensuring future recommendations are valid and can reliably inform international clinical guidelines.

Simple Screening Tests for Peripheral Neuropathy as a Prediction of Diabetic Foot Ulceration

Results: Foot care practices were followed by 80 (66.6%) of the study population. When compared with NCSs, the monofilament was the most specific at 91%, less sensitive 57%, superficial pain, ankle reflex had lower specificity (36%, 41%) respectively, sensitivity (62%,57%) respectively. Tuning fork had specificity 90%, sensitivity 56%. Conclusion: The study findings show that the simple screening tests (10-g SWME, vibration testing ,superficial pain test and ankle reflex) can be used confidently for annual screening of diabetic neuropathy in diabetic patients.

Monitoring temporal development and healing of diabetic foot ulceration using hyperspectral imaging

This study combines non-invasive hyperspectral imaging with an experimentally validated skin optical model and inverse algorithm to monitor diabetic feet of two representative patients. It aims to observe temporal changes in local epidermal thickness and oxyhemoglobin concentration and to gain insight into the progression of foot ulcer formation and healing. Foot ulceration is a debilitating comorbidity of diabetes that may result in loss of mobility and amputation. Inflammation and necrosis preempt ulceration and can result in changes in the skin prior to ulceration and during ulcer healing that affect oxygen delivery and consumption. Previous studies estimated oxyhemoglobin and deoxyhemoglobin concentrations around pre-ulcerative and ulcer sites on the diabetic foot using commercially available hyperspectral imaging systems. These measurements were successfully used to detect tissue at risk of ulceration and predict the healing potential of ulcers. The present study shows epidermal thickening and decrease in oxyhemoglobin concentration can also be detected prior to ulceration at pre-ulcerative sites. The algorithm was also able to observe reduction in the epidermal thickness combined with an increase in oxyhemoglobin concentration around the ulcer as it healed and closed. This methodology can be used for early prediction of diabetic foot ulceration in a clinical setting.