Comparative study between transforaminal epidural selective nerve root block versus interlaminar epidural in the treatment of lumbar radicular leg pain

Background: Sciatic neuralgia is a result of nerve root oedema because of the inflammatory, immunological and mechanical factors. Steroid injections play an important role in the management of sciatic radiculopathy. Steroids act by reducing the oedema around the nerve roots and decreasing pain. Locally administered steroids have the advantage of reduced dosage and targeted delivery around the nerve roots. This forms the basis of epidural steroid injections. This can be given around the nerve root in the transforaminal space or in the interlaminar space. There is a paucity of literature comparing the two techniques of epidural steroid injections. We have done a randomized comparative trial, to compare the effectiveness of the two modalities of injection in the management of a single level unilateral foraminal disc herniation.Methods: Patients were randomized in two groups Group A: Transforaminal epidural (SNRB) and Group B: interlaminar epidural. Same dose of steroid was used in each group.Results: Immediate post injection, 2 week and 1 month transforaminal epidural (SNRB) was better compare to interlaminar epidural however at the end of 3 months the difference was not significant (p=0.08).Conclusions: Both transforaminal and interlaminar epidural injection are effective form of treatment in mild to moderate grade of disc disease. Both the technique provide short lasting relief in the symptoms associated with disc pathology, however pain management is better in transforaminal group compared to interlaminar group. Thus these techniques can be considered for delaying surgery and providing intermitant relief.

A study to determine the association of serum uric acid and urine uric acid with different levels of glucose

Introduction: Uric acid is end product of purine metabolism in human beings, possesses both antioxidant and pro-oxidant properties. Uric acid has proven emerging roles in various diseases such as gout, renal dysfunction, hypertension, hyperlipidemia, diabetes and obesity. Material and Methods: This was anobservational and Cross-Sectional Study conducted at ESIC Medical college and hospital, Kalaburagi, Karnataka from April 2019 to September 2019 with a Sample Size of 100 Subjects, which includes 50 cases and 50 controls. Individuals in the age group 30-70 years suffering from type 2 diabetes mellitus, which is defined as fasting serum glucose ≥ 126mg/dl were included.Result: The fasting blood sugars (FBS) of the subjects had mean of 83.9±13.43 mg/dl in control group, in Group I cases had 170.71±19.80 mg/dl and in Group II cases had 307.54±203.68 mg/dl. Uric acid in control group had level of 3.85±1.41 mg/dl, in Group I cases had 7.27±0.35 mg/dl and in Group II cases had 4.9±3.89 mg/dl. The urinary uric acid level 578±82.02 mg/day in control group, in Group I cases had 364.31±40.31 mg/day and in Group II cases had 999.13±899.44md/day. There is statistical significant difference between control and group I cases (p<0.0001). Conclusion: Initial increase in Serum Uric acid and decrease in Urinary Uric acid with hyperglycaemia can be due to hyperinsulinemia, urate redox shuttle, microvascular injury and/or increase generation and activity of Xanthine oxidase. Decrease in Serum Uric acid and increase in Urinary Uric acid with advancing hyperglycaemia can be due to glycosuria causing uricosuria and decrease in sodium reabsorption

Distributed temperature measurements using optical fibre technology in an underground mine environment

This article experimentally examines the applicability of a temperature measuring and monitoring system using distributed temperature sensing by means of an optical fibre in an underground mine environment. The temperature distribution along an optical fibre can be detected by measuring the Raman backscattering of the stokes and anti-stokes lines. The distributed temperature sensing system provided valuable information for the mine safety control and the mine ventilation system. In addition, it proved to be capable of measuring air temperature in the entire mine with an accuracy of 1 degrees C and within the distance resolution of 1 m. The heating and cooling processes could be detected and the rate of heat generation at any location of the mine could be accurately determined from the temperature measurements. This technology has the potential to be linked to other measuring devices of an underground mine environment in order to develop a safer ventilation control syste

Utilizing machine learning techniques to classify network traffic

With in community of internet, it may be essential to recognize whatever programs are flowing via the networks in order to execute particular activities. Network traffic categorization is primarily used by Internet service providers (ISPs) to determine the qualities needed to construct a connection, which in turn influences the cable network current effectiveness. Stream, bandwidth, and machine-learning methods were all used to categorise internet protocol, and each has its own benefits and drawbacks. Because of its widespread use across disciplines as well as the increasing awareness between many investigators of its [5] methodology when especially in comparison to everyone else, the Machine Learning method is popular these times. Nave Bayes as well as K-nearest algorithm results are then compared in this research whenever applied to a networking given dataset taken through live stream feeds using Ethernet program. Python's sklearn module and the pandas and numpy arrays modules are utilised as assist modules to create a machine learning algorithm. Our findings show that K closest approach is more efficient than Nave Bayes, Decision Tree, and Support Vector Machine algorithms