Early Detection Of Diabetic Peripheral Neuropathy Research Articles

Early Detection of Diabetic Peripheral Neuropathy in Diabetic Patients: A Cross-Sectional Study.

Diabetic Peripheral Neuropathy (DPN) is a chronic complication in Type 2 Diabetes Mellitus (T2DM) patients and is characterized by paresthesia, pain, and hypoesthesia of the extremities. The Diabetic Neuropathy Symptom-Score (DNS) is a quick, inexpensive, and easy-to-perform tool to detect DPN in clinical practice. Biochemical markers like Nitric Oxide (NO) and Vascular Endothelial Growth Factor (VEGF) play a role in the early detection of DPN. This study aims to investigate the relationship between risk factors and these biomarkers. So, it is expected to improve the prevention and treatment of diabetic neuropathy more effectively. A cross-sectional method was used for this study. The sample size was 85 patients with T2DM who visited several primary healthcare in Medan, selected by consecutive sampling method based on eligibility criteria. Data collected included DNS, assessment of NO, VEGF, Glycated Hemoglobin (HbA1C), plasma blood glucose (PBG), and lipid profile. The collected data were analyzed using an independent T-test. The results showed that most T2DM patients, namely 73 people (85.9%), experienced DPN. From the bivariate analysis results, the risk factors associated with the prevalence of DPN in T2DM patients were found to be increased levels of total cholesterol, HbA1c, NO, and VEGF (p < 0.05). Meanwhile, blood pressure, fasting BGL, HDL-C, LDL-C, and triglycerides were not related to the occurrence of DPN in this study (p> 0.05). DNS can be used as a quick and easy initial screening tool implemented in clinical practice for screening DPN. Diabetic patients with DPN tend to have lower NO and increased VEGF; besides, NO levels are also associated with the progression of DPN. Furthermore, education, blood sugar control, and physical exercise, especially leg exercises, can prevent progressive DPN.

A study on prevalence of diabetic peripheral neuropathy in diabetic patients attending a rural health and training centre.

Diabetic neuropathy is a common complication, affecting up to half the diabetics. Diabetic peripheral neuropathy (DPN) predominantly affects the hands and lower limbs. It leads to loss of protective sensation, resulting in continuous injury to insensitive feet. The early detection of DPN using an objective screening test followed by its appropriate management is important, as up to 50% of diabetic peripheral neuropathies may be asymptomatic. To screen diabetic patients attending a Rural Health and Training Centre of a medical college in Tamil Nadu for DPN. To assess the association between DPN and sociodemographic factors, duration of diabetes, glycemic control, physical activity, body mass index, smoking and habit of alcohol consumption. The study was conducted among 206 diabetic patients attending a Rural Health and Training Centre. Participants were assessed using the Michigan Neuropathy Screening Instrument (MNSI), which involves using a questionnaire followed by a physical examination. Of the 206 patients, 61.2% were male, and 38.8% were female. The mean age was 50.86 years (standard deviation [SD] = 12.26 years). The mean duration of diabetes was 8.3 years (SD = 5.5 years). The proportion of diabetics who were screened positive for peripheral neuropathy was 16.5% and 21.8% using the MNSI questionnaire and examination, respectively. Age of 60 years and above was significantly associated with DPN.(OR = 3.982, P value = 0.0001). Duration of more than 5 years of diabetes was also significantly associated with DPN.(OR = 6.01, P value = 0.003). A high proportion of diabetics were screened positive for peripheral neuropathy, and many of them were unaware of having the complication. Many risk factors associated with DPN were reported in this study. Thus, early diagnosis and management with MNSI or any other validated screening tool in health care institutions is essential.

Machine learning models for diabetic neuropathy diagnosis using microcirculatory parameters in type 2 diabetes patients.

Diabetic peripheral neuropathy (DPN) is a primary cause of diabetic foot, early detection of DPN is essential. This study aimed to construct a machine learning model for DPN diagnosis based on microcirculatory parameters, and identify the most predictive parameters for DPN. Our study involved 261 subjects, including 102 diabetics with neuropathy (DMN), 73 diabetics without neuropathy (DM), and 86 healthy controls (HC). DPN was confirmed by nerve conduction velocity and clinical sensory tests. Microvascular function was measured by postocclusion reactive hyperemia (PORH), local thermal hyperemia (LTH), and transcutaneous oxygen pressure (TcPO<inf>2</inf>). Other physiological information was also investigated. Logistic regression (LR) and other machine learning (ML) algorithms were used to develop the model for DPN diagnosis. Kruskal-Wallis Test (non-parametric) were performed for multiple comparisons. Several performance measures, such as accuracy, sensitivity and specificity, were used to access the efficacy of the developed model. All the features were ranked based on the importance score to find features with higher DPN predictions. There was an overall decrease in microcirculatory parameters in response to PORH and LTH, as well as TcPO<inf>2</inf>, in DMN group compared to DM group and HC group. Random forest (RF) was found to be the best model, and achieved 84.6% accuracy along with 90.2% sensitivity and 76.7% specificity. RF_PF% of PORH was the main predictor of DPN. In addition, diabetic duration was also an important risk factor. PORH Test is a reliable screening tool for DPN, which can accurately distinguish DPN from diabetics using RF.

Early Detection of Diabetic Peripheral Neuropathy by fMRI: An Evidence-Based Review.

With the significant rise in the prevalence of diabetes worldwide, diabetic peripheral neuropathy (DPN) remains the most common complication among type 1 and 2 diabetics. The adverse sequelae of DPN, which include neuropathic pain, diabetic foot ulcers and lower-limb amputations, significantly impact quality of life and are major contributors to the biopsychosocial and economic burden of diabetes at the individual, societal and health system levels. Because DPN is often diagnosed in the late stages of disease progression by electromyography (EMG), and neuropathic pain as a result of DPN is difficult to treat, the need for earlier detection is crucial to better ascertain and manage the condition. Among the various modalities available to aid in the early detection of DPN, functional magnetic resonance imaging (fMRI) has emerged as a practical tool in DPN imaging due to its noninvasive radiation-free nature and its ability to relate real-time functional changes reflecting the local oxygen consumption of regions of the CNS due to external stimuli. This review aims to summarize the current body of knowledge regarding the utility of fMRI in detecting DPN by observing central nervous system (CNS) activity changes among individuals with DPN when compared to controls. The evidence to date points toward a tendency for increased activity in various central neuroanatomical structures that can be detected by fMRI and positively correlates with diabetic neuropathic pain.

Diabetic peripheral neuropathy in diabetic patients attending an urban health and training centre.

Introduction:Diabetic neuropathy is a complication affecting almost 50% of the diabetic patients. Diabetic Peripheral Neuropathy (DPN) predominantly affects the hands and lower limbs. It leads to loss of protective sensation resulting in continuous injury to insensitive feet. The early detection of DPN using an objective screening test followed by its appropriate management is important as up to 50% of the patients may be asymptomatic.Objectives:To screen Diabetic patients attending an Urban Health and Training Centre of a medical college in Tamilnadu for Diabetic Peripheral Neuropathy. To assess the association between DPN and selected variables such as socio-demographic factors, glycaemic control, duration of diabetes, physical activity, body mass index, smoking and consumption of alcohol.Methods:The study was conducted among 204 diabetic patients attending an Urban Health and Training Centre. Participants were assessed using Michigan Neuropathy Screening Instrument (MNSI), which involves using a questionnaire followed by a physical examination.Results:Of the 204 patients, 58.8% were male. The mean age was 54.8 years (SD = 8.8 years). About 79.9% were employed of which 29.4% were skilled labourers. Mean duration of diabetes was 6.2 years (SD = 5.3 years). The proportion of diabetics who screened positive for Peripheral Neuropathy was 23% and 45.6% using MNSI questionnaire and examination, respectively. An age of 60 years and above was significantly associated with DPN (OR = 2.505, P value = 0.003). A duration of more than 4 years of diabetes was also significantly associated with DPN (OR = 1.872, P value = 0.02820).Conclusion:A high proportion of diabetics with peripheral neuropathy did not express symptoms specific for diabetics. Thus, a simple tool like MNSI would be useful in primary care settings to screen for peripheral neuropathy, and hence prevent disability”.

Prevalence and Determinants of Diabetic Peripheral Neuropathy/Foot Syndrome in the Rural Population of North India

Introduction: Diabetic peripheral neuropathy (DPN), a common and troublesome complication of diabetes mellitus (DM), leads to a higher risk of diabetic foot ulcers and lower limb amputation. This study aimed to assess the prevalence of DPN among patients of type 2 DM from rural North India and associated risk factors for the condition. Materials and Methods: A facility-based cross-sectional study was carried out among type 2 diabetic patients attending the Non-Communicable Diseases (NCD) clinic of a secondary care hospital in rural North India. A questionnaire that included sociodemographic details, clinical and laboratory parameters, and the Michigan Neuropathy Screening Instrument (MNSI) for detecting peripheral neuropathy was administered to 100 consecutive eligible patients. Statistical Package for Social Sciences (SPSS) version 25.0 was used for entering and analyzing data. Bivariate analysis was performed to determine the factors significantly associated with the presence of DPN. Results: The prevalence of DPN was found to be 42.0%. Male gender, advancing age (≥60 years), longer duration of diabetes (&gt;10 years), smoking, physical inactivity, obesity, uncontrolled blood pressure, poor glycemic control and altered lipid profile were found to be significantly associated with the presence of DPN. Conclusions: The prevalence of DPN among type 2 diabetes patients from rural northern India is alarmingly high. There is a need for essential screening of all diabetic patients by their primary care provider for early detection of DPN, particularly in rural India.

Applications of current perception threshold evaluations in discovering early diabetic peripheral neuropathy

Diabetic neuropathy is one of the common long-term complications of diabetes, which occurs in the peripheral nervous system and the central nervous system, and its most common type is diabetic peripheral neuropathy (DPN). Diabetic peripheral neuropathy can not only cause pain, numbness and limitation of activity in limbs, but also lead to diabetic foot ulcers even amputations due to hypoesthesia and anesthesia, ultimately affects the quality of life of patients with diabetes and increases the mortality. Nearly half of patients with DPN do not have any clinical symptoms, thus the early detection and diagnosis of diabetic peripheral neuropathy are particularly critical. Current perception threshold (CPT) evaluation is considered as a mean of early detection of DPN, which gains more and more attentions because of its non-invasive feature, simple operation and high sensitivity. So far, there is scarcely any article summarizing CPT evaluations′ applications in researching the relationships between DPN and its risk factors. This review will discuss the principles and advantages of CPT evaluations, and its relationship with DPN will also be summarized as follows. Key words: Transcutaneous electric nerve stimulation; Sensory thresholds; Diabetic neuropathies; Peripheral nervous system diseases; Review