Abstract Background: Timely diagnosis of periodontal disease is crucial for restoring healthy periodontal tissue and improving patients’ prognosis. There is a growing interest in using salivary biomarkers as a noninvasive screening tool for periodontal disease. This study aimed to investigate the diagnostic efficacy of two salivary biomarkers, lactate dehydrogenase (LDH) and total protein, for periodontal disease by assessing their sensitivity in relation to clinical periodontal parameters. Furthermore, the study aimed to explore the impact of systemic disease, age, and sex on the accuracy of these biomarkers in the diagnosis of periodontal health. Materials and methods: A total of 145 participants were categorized into three groups based on their basic periodontal examination index, with 20 in the periodontally healthy group, 50 in the gingivitis group, and 75 in the periodontitis group. Salivary LDH was measured using the rate of nicotinamide adenine dinucleotide (NADH) oxidation, to measure the kinetics of LDH activity, while total protein was measured using the Lowry method. Descriptive and analytical statistical analyses were performed to examine the associations between the variables and biomarkers. Results: The results of the study demonstrated that salivary LDH was 72% sensitive, while salivary total protein was 78% sensitive in correlation to clinical periodontal parameters. The accuracy of the test was not influenced by sex, but age had a significant effect on both biomarkers, particularly LDH. Systemic disease was another factor that significantly affected the accuracy of the test. Conclusions: Although salivary LDH and total protein show promise as biomarkers for screening periodontal disease, their interpretation may be impacted by age and systemic disease.
Abstract
The research aims to study the problem of high production costs and low quality and the use of total quality management tools to detect problems of the high cost of failure and low quality products, diagnosis, and developing appropriate solutions.
To achieve the goal, we studied the overall quality tools and its relationship with the costs and the possibility of improving quality through the use of these tools.
Was limited to these tools and study the relation to the reduction of costs and improving quality have been studied serially by the possibility of the reduction.
To achieve the goal, the study of the concept of total quality management
Background Bloodstream infection (BSI) is a life-threatening condition caused by the presence of microorganisms, generally caused by a range of bacteria in the blood. Objectives The aim of this study was to evaluate the possible role of procalcitonin (PCT) and C-reactive protein (CRP) as biomarkers of pediatric BSI. Methodology The study was conducted on 150 blood samples collected from the patient who admitted to Children Welfare Teaching Hospital, Medical City, Baghdad. During the period from November 2020 to March 2021, ninety blood samples from them were positive culture and 60 blood samples were negative culture (control group). The isolates were identified depending on the morphological, microscopic examination, and biochemical tests.
... Show MoreEndometriosis is a common women health disorder that occurs when Endometrial-like tissue grows outside the uterus. This may lead to irregular bleeding , pelvic pain, infertility and other complications. Metformin, because of its activity to improve insulin sensitivity, it is used for the treatment of diabetes; it also has a modulatory effect on ovarian steroid production and has anti-inflammatory properties, all may suggest its possible effect in treatment of endometriosis. This study was planned to determine the effect of metformin on serum levels of&nbs
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Background: Drawing blood to measure total serum bilirubin is painful & time consuming. Transcutaneous bilirubinometer working by multiwavelength spectral reflectance from the skin surface on forehead or upper sternum is a quick & painless technique. Objectives: to compare the effectiveness of transcutaneous (over the upper sternum and forehead) and serum bilirubin measurement of neonate with jaundice. Subjects and Methods: This is a cross sectional prospective study. It enrolled 175 jaundiced neonates & excluded those exposed to phototherapy. It was conducted at Child Central Teaching Hospi |
Objectives : This study was seeks to determine the IgG and IgM in serum mothers and their babies of Iraqi patient suffering from congenital anomalies toward some microorganisms such as Cytomegalovirus (CMV), Congenital toxoplasmosis , Congenital rubella and Genital herpes simplex virus (HSV) correlated with age and babies gender the sample was collected from AL- Alwayia hospital for children / Baghdad . Methodology : Fifth blood sample have been collected from mothers and their babies suffering from congenital anomalies to detection IgG and IgM of some viruses including as Cytomegalovirus (CMV), congenital tox
The logistic regression model is one of the oldest and most common of the regression models, and it is known as one of the statistical methods used to describe and estimate the relationship between a dependent random variable and explanatory random variables. Several methods are used to estimate this model, including the bootstrap method, which is one of the estimation methods that depend on the principle of sampling with return, and is represented by a sample reshaping that includes (n) of the elements drawn by randomly returning from (N) from the original data, It is a computational method used to determine the measure of accuracy to estimate the statistics, and for this reason, this method was used to find more accurate estimates. The ma
... Show MoreMost of the medical datasets suffer from missing data, due to the expense of some tests or human faults while recording these tests. This issue affects the performance of the machine learning models because the values of some features will be missing. Therefore, there is a need for a specific type of methods for imputing these missing data. In this research, the salp swarm algorithm (SSA) is used for generating and imputing the missing values in the pain in my ass (also known Pima) Indian diabetes disease (PIDD) dataset, the proposed algorithm is called (ISSA). The obtained results showed that the classification performance of three different classifiers which are support vector machine (SVM), K-nearest neighbour (KNN), and Naïve B
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