scholarly journals Invisible Color Variations of Facial Erythema: A Novel Early Marker for Diabetic Complications?

2019 ◽  
Vol 2019 ◽  
pp. 1-7 ◽  
Author(s):  
Victoria Blanes-Vidal ◽  
Tomas Majtner ◽  
Luis David Avendaño-Valencia ◽  
Knud B. Yderstraede ◽  
Esmaeil S. Nadimi

Aim. (1) To quantify the invisible variations of facial erythema that occur as the blood flows in and out of the face of diabetic patients, during the blood pulse wave using an innovative image processing method, on videos recorded with a conventional digital camera and (2) to determine whether this “unveiled” facial red coloration and its periodic variations present specific characteristics in diabetic patients different from those in control subjects. Methods. We video recorded the faces of 20 diabetic patients with peripheral neuropathy, retinopathy, and/or nephropathy and 10 nondiabetic control subjects, using a Canon EOS camera, for 240 s. Only one participant presented visible facial erythema. We applied novel image processing methods to make the facial redness and its variations visible and automatically detected and extracted the redness intensity of eight facial patches, from each frame. We compared average and standard deviations of redness in the two groups using t-tests. Results. Facial redness varies, imperceptibly and periodically, between redder and paler, following the heart pulsation. This variation is consistently and significantly larger in diabetic patients compared to controls (p value < 0.001). Conclusions. Our study and its results (i.e., larger variations of facial redness with the heartbeats in diabetic patients) are unprecedented. One limitation is the sample size. Confirmation in a larger study would ground the development of a noninvasive cost-effective automatic tool for early detection of diabetic complications, based on measuring invisible redness variations, by image processing of facial videos captured at home with the patient’s smartphone.

2019 ◽  
Author(s):  
Cedar Warman ◽  
John E Fowler

AbstractHigh-throughput phenotyping systems are becoming increasingly powerful, dramatically changing our ability to document, measure, and detect phenomena. Unfortunately, taking advantage of these trends can be difficult for scientists with few resources, particularly when studying nonstandard biological systems. Here, we describe a powerful, cost-effective combination of a custom-built imaging platform and open-source image processing pipeline. Our maize ear scanner was built with off-the-shelf parts for <$80. When combined with a cellphone or digital camera, videos of rotating maize ears were captured and digitally flattened into projections covering the entire surface of the ear. Segregating GFP and anthocyanin seed markers were clearly distinguishable in ear projections, allowing manual annotation using ImageJ. Using this method, statistically powerful transmission data can be collected for hundreds of maize ears, accelerating the phenotyping process.


1982 ◽  
Vol 48 (03) ◽  
pp. 289-293 ◽  
Author(s):  
B A van Oost ◽  
B F E Veldhuyzen ◽  
H C van Houwelingen ◽  
A P M Timmermans ◽  
J J Sixma

SummaryPlatelets tests, acute phase reactants and serum lipids were measured in patients with diabetes mellitus and patients with peripheral vascular disease. Patients frequently had abnormal platelet tests and significantly increased acute phase reactants and serum lipids, compared to young healthy control subjects. These differences were compared with multidiscriminant analysis. Patients could be separated in part from the control subjects with variables derived from the measurement of acute phase proteins and serum lipids. Platelet test results improved the separation between diabetics and control subjects, but not between patients with peripheral vascular disease and control subjects. Diabetic patients with severe retinopathy frequently had evidence of platelet activation. They also had increased acute phase reactants and serum lipids compared to diabetics with absent or nonproliferative retinopathy. In patients with peripheral vascular disease, only the fibrinogen concentration was related to the degree of vessel damage by arteriography.


Author(s):  
Muhammad Nadeem Ashraf ◽  
Muhammad Hussain ◽  
Zulfiqar Habib

Diabetic Retinopathy (DR) is a major cause of blindness in diabetic patients. The increasing population of diabetic patients and difficulty to diagnose it at an early stage are limiting the screening capabilities of manual diagnosis by ophthalmologists. Color fundus images are widely used to detect DR lesions due to their comfortable, cost-effective and non-invasive acquisition procedure. Computer Aided Diagnosis (CAD) of DR based on these images can assist ophthalmologists and help in saving many sight years of diabetic patients. In a CAD system, preprocessing is a crucial phase, which significantly affects its performance. Commonly used preprocessing operations are the enhancement of poor contrast, balancing the illumination imbalance due to the spherical shape of a retina, noise reduction, image resizing to support multi-resolution, color normalization, extraction of a field of view (FOV), etc. Also, the presence of blood vessels and optic discs makes the lesion detection more challenging because these two artifacts exhibit specific attributes, which are similar to those of DR lesions. Preprocessing operations can be broadly divided into three categories: 1) fixing the native defects, 2) segmentation of blood vessels, and 3) localization and segmentation of optic discs. This paper presents a review of the state-of-the-art preprocessing techniques related to three categories of operations, highlighting their significant aspects and limitations. The survey is concluded with the most effective preprocessing methods, which have been shown to improve the accuracy and efficiency of the CAD systems.


2020 ◽  
Vol 33 (4/5) ◽  
pp. 323-331
Author(s):  
Mohsen pakdaman ◽  
Raheleh akbari ◽  
Hamid reza Dehghan ◽  
Asra Asgharzadeh ◽  
Mahdieh Namayandeh

PurposeFor years, traditional techniques have been used for diabetes treatment. There are two major types of insulin: insulin analogs and regular insulin. Insulin analogs are similar to regular insulin and lead to changes in pharmacokinetic and pharmacodynamic properties. The purpose of the present research was to determine the cost-effectiveness of insulin analogs versus regular insulin for diabetes control in Yazd Diabetes Center in 2017.Design/methodology/approachIn this descriptive–analytical research, the cost-effectiveness index was used to compare insulin analogs and regular insulin (pen/vial) for treatment of diabetes. Data were analyzed in the TreeAge Software and a decision tree was constructed. A 10% discount rate was used for ICER sensitivity analysis. Cost-effectiveness was examined from a provider's perspective.FindingsQALY was calculated to be 0.2 for diabetic patients using insulin analogs and 0.05 for those using regular insulin. The average cost was $3.228 for analog users and $1.826 for regular insulin users. An ICER of $0.093506/QALY was obtained. The present findings suggest that insulin analogs are more cost-effective than regular insulin.Originality/valueThis study was conducted using a cost-effectiveness analysis to evaluate insulin analogs versus regular insulin in controlling diabetes. The results of study are helpful to the government to allocate more resources to apply the cost-effective method of the treatment and to protect patients with diabetes from the high cost of treatment.


2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Sung-Hee Oh ◽  
Hyemin Ku ◽  
Kang Seo Park

Abstract Background Diabetes leads to severe complications and imposes health and financial burdens on the society. However, currently existing domestic public health studies of diabetes in South Korea mainly focus on prevalence, and data on the nationwide burden of diabetes in South Korea are lacking. The study aimed to estimate the prevalence and economic burden of diabetes imposed on the South Korean society. Methods A prevalence-based cost-of-illness study was conducted using the Korean national claims database. Adult diabetic patients were defined as those aged ≥20 years with claim records containing diagnostic codes for diabetes (E10-E14) during at least two outpatient visits or one hospitalization. Direct costs included medical costs for the diagnosis and treatment of diabetes and transportation costs. Indirect costs included productivity loss costs due to morbidity and premature death and caregivers’ costs. Subgroup analyses were conducted according to the type of diabetes, age (< 65 vs. ≥65), diabetes medication, experience of hospitalization, and presence of diabetic complications or related comorbidities. Results A total of 4,472,133 patients were diagnosed with diabetes in Korea in 2017. The average annual prevalence of diabetes was estimated at 10.7%. The diabetes-related economic burden was USD 18,293 million, with an average per capita cost of USD 4090 in 2019. Medical costs accounted for the biggest portion of the total cost (69.5%), followed by productivity loss costs (17.9%), caregivers’ costs (10.2%), and transportation costs (2.4%). According to subgroup analyses, type 2 diabetes, presence of diabetic complications or related comorbidities, diabetes medication, and hospitalization represented the biggest portion of the economic burden for diabetes. As the number of complications increased from one to three or more, the per capita cost increased from USD 3991 to USD 11,965. In inpatient settings, the per capita cost was ~ 10.8 times higher than that of outpatient settings. Conclusions South Korea has a slightly high prevalence and economic burden of diabetes. These findings highlight the need for effective strategies to manage diabetic patients and suggest that policy makers allocate more health care resources to diabetes. This is the first study on this topic, conducted using a nationally representative claims database in South Korea.


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