Background: Temporomandibular joint disorders refer to a group of heterogeneous pain and dysfunction conditions involving the masticatory system, reducing life quality of the sufferers. Arthrocentesis is simple and less invasive surgical procedure for the treatment of internal derangement than arthroscopy and better than other conservative procedures such as drugs, occlusal appliances and physiotherapy. The aim of the study was to evaluate the effect of arthrocentesis with injection of hyaluronic acid in the treatment of internal derangement of temporomandibular joint for the restoration of its function, reducing pain and preventing further deterioration of the temporomandibular joint dysfunction. Materials and methods: This study was performed in Al-Sheed Ghazi Al-Hariri Hospital, Department of Oral and Maxillofacial Surgery, from November 2012 to October 2013, included 60 patients, aged 18 to 45 years with symptoms of temporomandibular joint pain, clicking during function and limited mouth opening. Temporomandibular joint internal derangement was assessed with clinical examination and confirmed with computed tomography scan. Arthrocentesis was done with insertion of two 18 gauge needles in the upper joint compartment, lavaged with ringer’s lactate solution and at the end of the procedure 1ml of hyaluronic acid was injected. Intensity of temporomandibular joint pain was assessed using visual analog scale, maximum mouth opening was assessed with ruler scale and joint clicking was assessed clinically by stethoscope and manual palpation. All the parameters were measured before the procedure then 1 and 3 months later. Results: During 4 months follow-up, clinical examination and comparison of the results showed reduction in pain with success rate 95%, improvement in mouth opening with success rate 100% and clicking disappeared in 95% of patients. Conclusion: The technique of arthrocentesis using Sodium Hyaluronate injection, used in patients who presented with internal derangement, showed therapeutic benefits, simplicity, safety, patients acceptance of the technique and lack of significant side effects and complications.
Background: left ventricular hypertrophy is independent risk factor for cardiovascular morbidity and mortality. The presence of diabetic complications such as autonomic neuropathy and retinopathy may predict cardiac structural changes in diabetic patients. Objective: To explore the chance of occurrence of left ventricular hypertrophy in diabetic patients and whether it is related to the presence of other diabetic complications. Methods: ninty seven (97) normotensive diabetic patients (57) type II with mean duration of diabetes of (12±6 y) and forty (40) type I with mean duration of (8±6 y) were studied by echocardiography and compared with 41 patients as control. Results: The LVMI was significantly higher in type II diabetics compared
... Show MoreIn data transmission a change in single bit in the received data may lead to miss understanding or a disaster. Each bit in the sent information has high priority especially with information such as the address of the receiver. The importance of error detection with each single change is a key issue in data transmission field.
The ordinary single parity detection method can detect odd number of errors efficiently, but fails with even number of errors. Other detection methods such as two-dimensional and checksum showed better results and failed to cope with the increasing number of errors.
Two novel methods were suggested to detect the binary bit change errors when transmitting data in a noisy media.Those methods were: 2D-Checksum me
The current study aims at using non-hatchable artemia eggs of local origin and making use of these eggs by decapsulating and presenting them as food for the larvae of the Cyprinus carpio as a source of animal protein with high nutritional value instead of throwing them away. The results showed that the second parameter (A2) was highly significant at the level (P≤0.05) in the growth rates of the larvae that were fed on decapsulated artemia eggs alone, and it was better than the two control parameters (A1), in which the larvae were fed with feed designated for Cyprinus carpio fish. It also outperformed the third parameter (A3), in which the feed was mixed with artemia eggs with 50% decapsulation, which also outperformed the control paramete
... Show MoreOut of 150 different specimens, 67 S. aureus isolate were isolated. However, 16sRNA gene was located only in 60 isolates. Moreover, mecA gene was located in 48 isolates; thereby MRSA covered 80% of all S. aureus isolates. Of considerable interest, pvl gene was detected in only six isolates (10%). Hence, the present work emphasizes the notion suggested that pvl is not an indicative of CA-MRSA.
The research discusses the obstacles that faced the Iraqi strategic performance in achieving sustainable development after the election of the first Iraqi government in 2005 and the most important strategies to overcome these obstacles.
Emergency vehicle (EV) services save lives around the world. The necessary fast response of EVs requires minimising travel time. Preempting traffic signals can enable EVs to reach the desired location quickly. Most of the current research tries to decrease EV delays but neglects the resulting negative impacts of the preemption on other vehicles in the side roads. This paper proposes a dynamic preemption algorithm to control the traffic signal by adjusting some cycles to balance between the two critical goals: minimal delay for EVs with no stop, and a small additional delay to the vehicles on the side roads. This method is applicable to preempt traffic lights for EVs through an Intelli
In data mining, classification is a form of data analysis that can be used to extract models describing important data classes. Two of the well known algorithms used in data mining classification are Backpropagation Neural Network (BNN) and Naïve Bayesian (NB). This paper investigates the performance of these two classification methods using the Car Evaluation dataset. Two models were built for both algorithms and the results were compared. Our experimental results indicated that the BNN classifier yield higher accuracy as compared to the NB classifier but it is less efficient because it is time-consuming and difficult to analyze due to its black-box implementation.