Interconnections between diabetic corneal neuropathy and diabetic retinopathy:diagnostic and therapeutic implications

Diabetic corneal neuropathy and diabetic retinopathy are ocular complications occurring in the context of diabetes mellitus.Diabetic corneal neuropathy refers to the progressive damage of corneal nerves.Diabetic retinopathy has traditionally been considered as damage to the retinal microvasculature.However,growing evidence suggests that diabetic retinopathy is a complex neurovascular disorder resulting from dysfunction of the neurovascular unit,which includes both the retinal vascular structures and neural tissues.Diabetic retinopathy is one of the leading causes of blindness and is frequently screened for as part of diabetic ocular screening.However,diabetic corneal neuropathy is commonly overlooked and underdiagnosed,leading to severe ocular surface impairment.Several studies have found that these two conditions tend to occur together,and they share similarities in their pathogenesis pathways,being triggered by a status of chronic hyperglycemia.This review aims to discuss the interconnection between diabetic corneal neuropathy and diabetic retinopathy,whether diabetic corneal neuropathy precedes diabetic retinopathy,as well as the relation between the stage of diabetic retinopathy and the severity of corneal neuropathy.We also endeavor to explore the relevance of a corneal screening in diabetic eyes and the possibility of using corneal nerve measurements to monitor the progression of diabetic retinopathy.

Diabetic peripheral neuropathy and neuromodulation techniques:a systematic review of progress and prospects

Neuromodulation for diabetic peripheral neuropathy represents a significant area of interest in the management of chronic pain associated with this condition.Diabetic peripheral neuropathy,a common complication of diabetes,is characterized by nerve damage due to high blood sugar levels that lead to symptoms,such as pain,tingling,and numbness,primarily in the hands and feet.The aim of this systematic review was to evaluate the efficacy of neuromodulatory techniques as potential therapeutic interventions for patients with diabetic peripheral neuropathy,while also examining recent developments in this domain.The investigation encompassed an array of neuromodulation methods,including frequency rhythmic electrical modulated systems,dorsal root ganglion stimulation,and spinal cord stimulation.This systematic review suggests that neuromodulatory techniques may be useful in the treatment of diabetic peripheral neuropathy.Understanding the advantages of these treatments will enable physicians and other healthcare providers to offer additional options for patients with symptoms refractory to standard pharmacologic treatments.Through these efforts,we may improve quality of life and increase functional capacity in patients suffering from complications related to diabetic neuropathy.

Association of autoimmune thyroid disease with type 1 diabetes mellitus and its ultrasonic diagnosis and management

As a common hyperglycemic disease,type 1 diabetes mellitus(T1DM)is a complicated disorder that requires a lifelong insulin supply due to the immunemediated destruction of pancreaticβcells.Although it is an organ-specific autoimmune disorder,T1DM is often associated with multiple other autoimmune disorders.The most prevalent concomitant autoimmune disorder occurring in T1DM is autoimmune thyroid disease(AITD),which mainly exhibits two extremes of phenotypes:hyperthyroidism[Graves'disease(GD)]and hypothyroidism[Hashimoto's thyroiditis,(HT)].However,the presence of comorbid AITD may negatively affect metabolic management in T1DM patients and thereby may increase the risk for potential diabetes-related complications.Thus,routine screening of thyroid function has been recommended when T1DM is diagnosed.Here,first,we summarize current knowledge regarding the etiology and pathogenesis mechanisms of both diseases.Subsequently,an updated review of the association between T1DM and AITD is offered.Finally,we provide a relatively detailed review focusing on the application of thyroid ultrasonography in diagnosing and managing HT and GD,suggesting its critical role in the timely and accurate diagnosis of AITD in T1DM.

Association of age at diagnosis of diabetes with subsequent risk of age-related ocular diseases and vision acuity

BACKGROUND The importance of age on the development of ocular conditions has been reported by numerous studies.Diabetes may have different associations with different stages of ocular conditions,and the duration of diabetes may affect the development of diabetic eye disease.While there is a dose-response relationship between the age at diagnosis of diabetes and the risk of cardiovascular disease and mortality,whether the age at diagnosis of diabetes is associated with incident ocular conditions remains to be explored.It is unclear which types of diabetes are more predictive of ocular conditions.AIM To examine associations between the age of diabetes diagnosis and the incidence of cataract,glaucoma,age-related macular degeneration(AMD),and vision acuity.METHODS Our analysis was using the UK Biobank.The cohort included 8709 diabetic participants and 17418 controls for ocular condition analysis,and 6689 diabetic participants and 13378 controls for vision analysis.Ocular diseases were identified using inpatient records until January 2021.Vision acuity was assessed using a chart.RESULTS During a median follow-up of 11.0 years,3874,665,and 616 new cases of cataract,glaucoma,and AMD,respectively,were identified.A stronger association between diabetes and incident ocular conditions was observed where diabetes was diagnosed at a younger age.Individuals with type 2 diabetes(T2D)diagnosed at<45 years[HR(95%CI):2.71(1.49-4.93)],45-49 years[2.57(1.17-5.65)],50-54 years[1.85(1.13-3.04)],or 50-59 years of age[1.53(1.00-2.34)]had a higher risk of AMD independent of glycated haemoglobin.T2D diagnosed<45 years[HR(95%CI):2.18(1.71-2.79)],45-49 years[1.54(1.19-2.01)],50-54 years[1.60(1.31-1.96)],or 55-59 years of age[1.21(1.02-1.43)]was associated with an increased cataract risk.T2D diagnosed<45 years of age only was associated with an increased risk of glaucoma[HR(95%CI):1.76(1.00-3.12)].HRs(95%CIs)for AMD,cataract,and glaucoma associated with type 1 diabetes(T1D)were 4.12(1.99-8.53),2.95(2.17-4.02),and 2.40(1.09-5.31),respectively.In multivariable-adjusted analysis,individuals with T2D diagnosed<45 years of age[β95%CI:0.025(0.009,0.040)]had a larger increase in LogMAR.Theβ(95%CI)for LogMAR associated with T1D was 0.044(0.014,0.073).CONCLUSION The younger age at the diagnosis of diabetes is associated with a larger relative risk of incident ocular diseases and greater vision loss.

Guidelines and standards for comprehensive clinical diagnosis and interventional treatment for diabetic foot in China(Issue 7.0)

Diabetic foot(DF)is one of the most common complications of diabetes and is associated with high morbidity,disability,lethality and low cure-rate.The clinical diagnosis and treatment of DF need to be standardized.The Chinese Diabetic Foot Cell and Interventional Therapy Technology Alliance has released six editions of guidelines and standards for clinical diagnosis and interventional treatment of DF,which filled the gap in the domestic DF treatment standard and played an important role in improving the level of diagnosis and treatment in China.In line with the latest developments in diagnosis and treatment,the Alliance,along with other 89 institutions,developed and issued the new edition based on the sixth edition to help standardize the clinical diagnosis and treatment of DF in China.

Research progress in artificial intelligence assisted diabetic retinopathy diagnosis

Diabetic retinopathy(DR)is one of the most common retinal vascular diseases and one of the main causes of blindness worldwide.Early detection and treatment can effectively delay vision decline and even blindness in patients with DR.In recent years,artificial intelligence(AI)models constructed by machine learning and deep learning(DL)algorithms have been widely used in ophthalmology research,especially in diagnosing and treating ophthalmic diseases,particularly DR.Regarding DR,AI has mainly been used in its diagnosis,grading,and lesion recognition and segmentation,and good research and application results have been achieved.This study summarizes the research progress in AI models based on machine learning and DL algorithms for DR diagnosis and discusses some limitations and challenges in AI research.

An Optimal Deep Learning Based Computer-Aided Diagnosis System for Diabetic Retinopathy

Diabetic Retinopathy(DR)is a significant blinding disease that poses serious threat to human vision rapidly.Classification and severity grading of DR are difficult processes to accomplish.Traditionally,it depends on ophthalmoscopically-visible symptoms of growing severity,which is then ranked in a stepwise scale from no retinopathy to various levels of DR severity.This paper presents an ensemble of Orthogonal Learning Particle Swarm Optimization(OPSO)algorithm-based Convolutional Neural Network(CNN)Model EOPSO-CNN in order to perform DR detection and grading.The proposed EOPSO-CNN model involves three main processes such as preprocessing,feature extraction,and classification.The proposed model initially involves preprocessing stage which removes the presence of noise in the input image.Then,the watershed algorithm is applied to segment the preprocessed images.Followed by,feature extraction takes place by leveraging EOPSO-CNN model.Finally,the extracted feature vectors are provided to a Decision Tree(DT)classifier to classify the DR images.The study experiments were carried out using Messidor DR Dataset and the results showed an extraordinary performance by the proposed method over compared methods in a considerable way.The simulation outcome offered the maximum classification with accuracy,sensitivity,and specificity values being 98.47%,96.43%,and 99.02%respectively.

Diabetic Retinopathy Diagnosis Using ResNet with Fuzzy Rough C-Means Clustering

Diabetic Retinopathy(DR)is a vision disease due to the long-term prevalenceof Diabetes Mellitus.It affects the retina of the eye and causes severedamage to the vision.If not treated on time it may lead to permanent vision lossin diabetic patients.Today’s development in science has no medication to cureDiabetic Retinopathy.However,if diagnosed at an early stage it can be controlledand permanent vision loss can be avoided.Compared to the diabetic population,experts to diagnose Diabetic Retinopathy are very less in particular to local areas.Hence an automatic computer-aided diagnosis for DR detection is necessary.Inthis paper,we propose an unsupervised clustering technique to automatically clusterthe DR into one of its five development stages.The deep learning based unsupervisedclustering is made to improve itself with the help of fuzzy rough c-meansclustering where cluster centers are updated by fuzzy rough c-means clusteringalgorithm during the forward pass and the deep learning model representationsare updated by Stochastic Gradient Descent during the backward pass of training.The proposed method was implemented using python and the results were takenon DGX server with Tesla V100 GPU cards.An experimental result on the publicallyavailable Kaggle dataset shows an overall accuracy of 88.7%.The proposedmodel improves the accuracy of DR diagnosis compared to the existingunsupervised algorithms like k-means,FCM,auto-encoder,and FRCM withalexnet.

Transfer Learning-based Computer-aided Diagnosis System for Predicting Grades of Diabetic Retinopathy

Diabetic retinopathy(DR)diagnosis through digital fundus images requires clinical experts to recognize the presence and importance of many intricate features.This task is very difficult for ophthalmologists and timeconsuming.Therefore,many computer-aided diagnosis(CAD)systems were developed to automate this screening process ofDR.In this paper,aCAD-DR system is proposed based on preprocessing and a pre-train transfer learningbased convolutional neural network(PCNN)to recognize the five stages of DR through retinal fundus images.To develop this CAD-DR system,a preprocessing step is performed in a perceptual-oriented color space to enhance the DR-related lesions and then a standard pre-train PCNN model is improved to get high classification results.The architecture of the PCNN model is based on three main phases.Firstly,the training process of the proposed PCNN is accomplished by using the expected gradient length(EGL)to decrease the image labeling efforts during the training of the CNN model.Secondly,themost informative patches and images were automatically selected using a few pieces of training labeled samples.Thirdly,the PCNN method generated useful masks for prognostication and identified regions of interest.Fourthly,the DR-related lesions involved in the classification task such as micro-aneurysms,hemorrhages,and exudates were detected and then used for recognition of DR.The PCNN model is pre-trained using a high-end graphical processor unit(GPU)on the publicly available Kaggle benchmark.The obtained results demonstrate that the CAD-DR system outperforms compared to other state-of-the-art in terms of sensitivity(SE),specificity(SP),and accuracy(ACC).On the test set of 30,000 images,the CAD-DR system achieved an average SE of 93.20%,SP of 96.10%,and ACC of 98%.This result indicates that the proposed CAD-DR system is appropriate for the screening of the severity-level of DR.

New approaches in the diagnosis and management of diabetic retinopathy

Diabetic retinopathy(DR)presents one of the greatest challenges currently faced in ophthalmology by both patients and clinicians.Simply by virtue of the number of people impacted and the acceleration in the development of diabetes in larger populations throughout the world,the problem of diabetic complications has taken on new urgency in recent years.Because of the immediate impact on quality of life,activities of daily living,and a person’s ability to work and live independently,DR tops the list of concerns about the damage wrought by the explosive growth of diabetes.

Frequency, Risk Factors and Clinical Forms of Neuropathies in Diabetics in Hospitals in Burkina Faso

Introduction: Diabetic neuropathy is one of the most common chronic complications of diabetes. Most of the studies on the subject in the sub region, particularly in Burkina Faso, dealt it with the study of the complications of diabetes, or one of its components. Our study was designed to study in particular in all its aspects, by searching for its peculiarities in our context, for improvement of its support. Methodology: This is a cross-sectional descriptive study carried out in 150 diabetic patients aged at least 15 years followed in the Department of Internal Medicine at Yalgado Ouedraogo University Teaching Hospital. All patients included had agreed to participate in our survey after informed consent. We collected the data during the period from 2015 November to 2016 June. Each patient was evaluated by the DN4 questionnaire and clinically by a neurological examination. We determinated the frequency, the sociodemographic, clinical and therapeutic characteristics of diabetes neuropathy and its related factors. Results: The frequency of diabetic neuropathy was 80.7%. Peripheral neuropathies were seen in 81.8% of cases and autonomic neuropathies in 72.7% of cases. Autonomic neuropathy was dominated by the DAN (59.1%), and erectile dysfunction (44%). There was a high comorbidity with physical inactivity (66.9%), obesity (49.4%) and hypertension (38.8%). There were poorly controlled patients in 38.8%. A link was found between T2DM and neuropathy (p = 0.014). Painful diabetes was related to the quality of glycemic control (p = 0.007), and hypertension (p = 0.021). A link was also found between tobacco consumption (p < 0.001), male (p < 0.001), and urogenital autonomic neuropathy. Conclusion: Diabetic neuropathies are very common in our context and could be a haunting to the practitioner with the progression of diabetes and its corollary of degenerative complications. There was a significant association between Type 2 Diabetes mellitus and the presence of peripheral diabetic neuropathy.

Cell metabolism pathways involved in the pathophysiological changes of diabetic peripheral neuropathy

Diabetic peripheral neuropathy is a common complication of diabetes mellitus.Elucidating the pathophysiological metabolic mechanism impels the generation of ideal therapies.However,existing limited treatments for diabetic peripheral neuropathy expose the urgent need for cell metabolism research.Given the lack of comprehensive understanding of energy metabolism changes and related signaling pathways in diabetic peripheral neuropathy,it is essential to explore energy changes and metabolic changes in diabetic peripheral neuropathy to develop suitable treatment methods.This review summarizes the pathophysiological mechanism of diabetic peripheral neuropathy from the perspective of cellular metabolism and the specific interventions for different metabolic pathways to develop effective treatment methods.Various metabolic mechanisms(e.g.,polyol,hexosamine,protein kinase C pathway)are associated with diabetic peripheral neuropathy,and researchers are looking for more effective treatments through these pathways.

Advances in the treatment of diabetic peripheral neuropathy by modulating gut microbiota with traditional Chinese medicine

Diabetic peripheral neuropathy(DPN)is one of the strongest risk factors for diabetic foot ulcers(neuropathic ulcerations)and the existing ulcers may further deteriorate due to the damage to sensory neurons.Moreover,the resulting numbness in the limbs causes difficulty in discovering these ulcerations in a short time.DPN is associated with gut microbiota dysbiosis.Traditional Chinese medicine(TCM)compounds such as Shenqi Dihuang Decoction,Huangkui Capsules and Qidi Tangshen Granules can reduce the clinical symptoms of diabetic nephropathy by modulating gut microbiota.The current review discusses whether TCM compounds can reduce the risk of DPN by improving gut microbiota.

Diabetes and cardiac autonomic neuropathy: Clinical manifestations, cardiovascular consequences, diagnosis and treatment

Cardiac autonomic neuropathy(CAN) is a frequent chronic complication of diabetes mellitus with potentially life-threatening outcomes. CAN is caused by the impairment of the autonomic nerve fibers regulating heart rate, cardiac output, myocardial contractility, cardiac electrophysiology and blood vessel constriction anddilatation. It causes a wide range of cardiac disorders, including resting tachycardia, arrhythmias, intraoperative cardiovascular instability, asymptomatic myocardial ischemia and infarction and increased rate of mortality after myocardial infarction. Etiological factors associated with autonomic neuropathy include insufficient glycemic control, a longer period since the onset of diabetes, increased age, female sex and greater body mass index. The most commonly used methods for the diagnosis of CAN are based upon the assessment of heart rate variability(the physiological variation in the time interval between heartbeats), as it is one of the first findings in both clinically asymptomatic and symptomatic patients. Clinical symptoms associated with CAN generally occur late in the disease process and include early fatigue and exhaustion during exercise, orthostatic hypotension, dizziness, presyncope and syncope. Treatment is based on early diagnosis, life style changes, optimization of glycemic control and management of cardiovascular risk factors. Medical therapies, including aldose reductase inhibitors, angiotensin-converting enzyme inhibitors, prostoglandin analogs and alpha-lipoic acid, have been found to be effective in randomized controlled trials. The following article includes the epidemiology, clinical findings and cardiovascular consequences, diagnosis, and approaches to prevention and treatment of CAN.

Entrapment neuropathies in diabetes mellitus

Neuropathy is a common complication of diabetes mellitus(DM) with a wide clinical spectrum that encompasses generalized to focal and multifocal forms. Entrapment neuropathies(EN), which are focal forms, are so frequent at any stage of the diabetic disease, that they may be considered a neurophysiological hallmarkof peripheral nerve involvement in DM. Indeed, EN may be the earliest neurophysiological abnormalities in DM,particularly in the upper limbs, even in the absence of a generalized polyneuropathy, or it may be superimposed on a generalized diabetic neuropathy. This remarkable frequency of EN in diabetes is underlain by a peculiar pathophysiological background. Due to the metabolic alterations consequent to abnormal glucose metabolism,the peripheral nerves show both functional impairment and structural changes, even in the preclinical stage,making them more prone to entrapment in anatomically constrained channels. This review discusses the most common and relevant EN encountered in diabetic patient in their epidemiological, pathophysiological and diagnostic features.

Non-alcoholic fatty liver disease and diabetes: From physiopathological interplay to diagnosis and treatment

Non-alcoholic fatty liver disease(NAFLD)is highly prevalent in patients with diabetes mellitus and increasing evidence suggests that patients with type 2diabetes are at a particularly high risk for developing the progressive forms of NAFLD,non-alcoholic steatohepatitis and associated advanced liver fibrosis.Moreover,diabetes is an independent risk factor for NAFLD progression,and for hepatocellular carcinoma development and liver-related mortality in prospective studies.Notwithstanding,patients with NAFLD have an elevated prevalence of prediabetes.Recent studies have shown that NAFLD presence predicts the development of type2 diabetes.Diabetes and NAFLD have mutual pathogenetic mechanisms and it is possible that genetic and environmental factors interact with metabolic derangements to accelerate NAFLD progression in diabetic patients.The diagnosis of the more advanced stages of NAFLD in diabetic patients shares the same challenges as in non-diabetic patients and it includes imaging and serological methods,although histopathological evaluation is still considered the gold standard diagnostic method.An effective established treatment is not yet available for patients with steatohepatitis and fibrosis and randomized clinical trials including only diabetic patients are lacking.We sought to outline the published data including epidemiology,pathogenesis,diagnosis and treatment of NAFLD in diabetic patients,in order to better understand the interplay between these two prevalent diseases and identify the gaps that still need to be fulfilled in the management of NAFLD in patients with diabetes mellitus.

Significance of Nueroelectrophysiological Tests in the Early Diagnosis of Sub-clinical Neuropathay with Diabetes Mellitus

Summary： To evaluate the application of nueroelectrophysiological tests in early diagnosis of sub-clinical neuropathy in diabetes mellitus （DM）, The routine nerve conductive velocity （NCV）, F-wave and sympathetic skin response （SSR） were detected in 27 patients with diabetes mellitus but without symptoms and signs of lesions of nerve system. Our results showed that 48.1%, 44.4 %, 51. 9 % of the patients were found to have abnormal NCV, F-wave and SSR respectively, The abnormalities were mainly characterized by prolonged latency, reduced velocity and absence of wave-form. There were significant differences between the controls and the DM group （P〈0,05）. Both the distal and proximal segments of nerves were affected and the distal lesions took place earlier than proximal ones and the changes in low extremities were more severe than those of upper extremities, F-wave can be used as a sensitive indicator for the early diagnosis of peripheral neuropathy and it can help to detect the subclincial lesions, SSR can be used for the evaluation of functional status of autonomic nerves in DM patients.

Fuzzy expert system for diagnosing diabetic neuropathy

AIM To design a fuzzy expert system to help detect and diagnose the severity of diabetic neuropathy. METHODS The research was completed in 2014 and consisted of two main phases. In the first phase, the diagnostic parameters were determined based on the literature review and by investigating specialists' perspectives(n= 8). In the second phase, 244 medical records related to the patients who were visited in an endocrinology and metabolism research centre during the first six months of 2014 and were primarily diagnosed with diabetic neuropathy, were used to test the sensitivity, specificity, and accuracy of the fuzzy expert system.RESULTS The final diagnostic parameters included the duration of diabetes, the score of a symptom examination based on the Michigan questionnaire, the score of a sign examination based on the Michigan questionnaire, the glycolysis haemoglobin level, fasting blood sugar, blood creatinine, and albuminuria. The output variable was the severity of diabetic neuropathy which was shown as a number between zero and 10, had been divided into four categories: absence of the disease,(the degree of severity) mild, moderate, and severe. The interface of the system was designed by ASP.Net(Active Server Pages Network Enabled Technology) and the system function was tested in terms of sensitivity(true positive rate)(89%), specificity(true negative rate)(98%), and accuracy(a proportion of true results, both positive and negative)(93%).CONCLUSION The system designed in this study can help specialistsand general practitioners to diagnose the disease more quickly to improve the quality of care for patients.

Diagnosis,treatment and prevention of type 2 diabetes mellitus in children and adolescents

During the last two decades,there have been several reports of an increasing incidence of type 2 diabetes mellitus(T2 DM) in children and adolescents,especially among those belonging to minority ethnic groups.This trend,which parallels the increases in prevalence and degree of pediatric obesity,has caused great concern,even though T2 DM remains a relatively rare disease in children.Youth T2 DM differs not only from type 1 diabetes in children,from which it is sometimes difficult to differentiate,but also from T2 DM in adults,since it appears to be an aggressive disease with rapidly progressive β-cell decline,high treatment failure rate,and accelerated development of complications.Despite the recent research,many aspects of youth T2 DM still remain unknown,regarding both its pathophysiology and risk factor contribution,and its optimal management and prevention.Current management approaches include lifestyle changes,such as improved diet and increased physical activity,together with pharmacological interventions,including metformin,insulin,and the recently approved glucagonlike peptide-1 analog liraglutide.What is more important for everyone to realize though,from patients,families and physicians to schools,health services and policy-makers alike,is that T2 DM is a largely preventable disease that will be addressed effectively only if its major contributor(i.e.,pediatric obesity) is confronted and prevented at every possible stage of life,from conception until adulthood.Therefore,relevant comprehensive,coordinated,and innovative strategies are urgently needed.

Validation of neuropathic pain assessment tools among Chinese patients with painful diabetic peripheral neuropathy

Objective:This study aims to evaluate the reliability and validity of neuropathic pain assessment tools among Chinese patients with painful diabetic peripheral neuropathy(PDPN).Methods:One hundred patients with PDPN and 70 patients with non-neuropathic pain were recruited from five grade III general hospitals in Guangzhou.Pain was assessed using the Leeds Assessment of Neuropathic Symptoms and Signs(LANSS),Douleur Neuropathique 4 questionnaire(DN4),and Brief Pain Inventory for Painful Diabetic Peripheral Neuropathy(BPI-DPN).Reliability was evaluated by internal consistency of the Cronbach's a coefficient and Guttman split-half.Construct validity was analyzed by factor analysis and Spearman correlation coefficients.Sensitivity and specificity were also assessed.Results:The Cronbach's a coefficients of the LANSS,DN4,and BPI-DPN were 0.735,0.750,and 0.898,respectively.The Guttman split-half coefficients of the LANSS,DN4,and BPIDPN were 0.660,0.726,and 0.849,respectively.The cumulative contributions of the LANSS,DN4,and BPI-DPN to the total variance were 61.945%,57.010%,and 66.056%,respectively.The items of the LANSS,DN4,and BPI-DPN presented high factorial loads,ranging from 0.387 to 0.841,0.137 to 0.948,and 0.487 to 0.953,respectively.The LANSS and DN4 exhibited sensitivities of 58.0%and 82.7%,respectively,and specificity of 97.1%.Conclusions:The LANSS or DN4 can be used to detect neuropathic pain in Chinese patients with PDPN.The BPI-DPN can be employed to monitor the effectiveness of pain intervention.