Background: Diabetes mellitus is a metabolic disorder affecting people worldwide, which require constant monitoring of their glucose levels. Commonly employed procedures include collection of blood or urine samples causing discomfort to the patients. Necessity arises to find alternative non invasive technique is required to monitor glucose levels. Saliva is one of most abundant secretions in the human body and its collection is easy, noninvasive and painless technique. Objective: The aim of this study was to determine the efficacy of saliva as a diagnostic tool by study the correlation between blood and salivary glucose levels and glycosylated hemoglobin (HbA1c%) in diabetes and non diabetes, and the comparison of salivary glucose level and blood HbA1c% with serum glucose level in healthy and diabetic subjects. Type of study: cross- sectional study.Method: Saliva and blood samples were collected from 40 patients visited the Baghdad hospital in Iraq who were previously diagnosed with non-insulin-dependent (type 2) diabetes mellitus and 10 healthy as control (male and female) in age group of 30-65 years. The samples were examined to determine blood and salivary glucose level by the glucose oxidase- peroxidase method and blood HbA1c% by the ion exchange resin method. Results: Our results showed significantly higher salivary and serum glucose level in diabetes compared to control and significantly positive correlation between salivary and serum glucose in diabetes, control, and both groups together; the blood HbA1c% in diabetes was significantly higher compared to control and found a positive correlation between blood HbA1c% and salivary and serum glucose level in diabetes and control. Conclusion: salivary glucose appears to be an indicator of serum glucose concentration in diabetes.
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Background: Oral tumors are one of the most challenging
tumors regarding their good prognosis in early diagnosis and
very difficult control in advancing stages.
Objectives: To study the prevalence, types and clinical
presentation of oral tumors in comparison to other oral
lesions among patients attending ENT clinic.
Al-Kindy Col Med J 2008 Vol.5(1) Original Article 11
Methods: This study included 534 patients with different
oral complains attending ENT clinics in AI-Yarmouk
Teaching Hospital, and AI-Kindy Teaching Hospital -
Baghdad, in the period from 1st jan1999 till 31th des 2006 (8
years interval).
Results: The results of this study showed that the prevalence
of malignant lesions was 13.5% (72 o
Breast tumors patients generally have more oxidative stress than normal females. This was clear from a highly significant elevation (P<0.05) in malondialdehyde level in RBCs, serum and tissue of all patients groups with breast cancer as compared with control group. In this study we had found that free radicals in malignant breast tumors were higher than benign tumors, therefore the MDA might be used as a marker for prognosis of the disease.
The engagement of pharmacists in research activities is pivotal in the advancement of the pharmacy practice. The study aims to evaluate the confidence and competence of Malaysian hospital pharmacists in conducting clinical and practice-based research.
A cross-sectional study was carried out between September 2019 and April 2020 using an online survey. Pharmacists from eight different hospitals in Malaysia were involved in the study. The survey link was sent to all pharmacists of the included hospitals via email. Data were analysed using SPSS version 25.
A total of 226 pharmacists participated in this study, and their average age was 28 years old. About 82 % of the participants reported that they did not have any previous re
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Nonalcoholic fatty liver disease in a group of Iraqi obese children attending children welfare teaching hospital
This paper presents a robust algorithm for the assessment of risk priority for medical equipment based on the calculation of static and dynamic risk factors and Kohnen Self Organization Maps (SOM). Four risk parameters have been calculated for 345 medical devices in two general hospitals in Baghdad. Static risk factor components (equipment function and physical risk) and dynamics risk components (maintenance requirements and risk points) have been calculated. These risk components are used as an input to the unsupervised Kohonen self organization maps. The accuracy of the network was found to be equal to 98% for the proposed system. We conclude that the proposed model gives fast and accurate assessment for risk priority and it works as p
... Show MoreIn this study, performance characteristics such as power take off (PTO) power consumption, fuel consumption, fuel consumption for the unit field-unit product were determined at different working speeds with two different PTO applications (540 and 540E) in a single row disc type silage machine. In particular, the 540E PTO application greatly reduces fuel consumption for unit work. The best results in terms of hourly fuel consumption were achieved in 540E PTO application and V1 working speed. When the field - product fuel consumption is evaluated, the best results were obtained with the 540E PTO application at the V3 working speed. When an evaluation is made considering all the parameters, it is concluded that the 540E PTO application will p
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The problem of medical waste over the past tow decades has emerged as one of the most important issues.
Which have negative effects on health and the environment ,and as a result specialists looked into the field.
Public health and research issues . This phenomenon in all its dimensions and efforts made For their containment through the development of health and environmental controls for the disposal of such wastes.
In a safe manner starting form the source of these wastes and the various health organizations are finished The final treatment ,and this is why the producers of hazardous medical waste. &nb
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<span lang="EN-US">Diabetes is one of the deadliest diseases in the world that can lead to stroke, blindness, organ failure, and amputation of lower limbs. Researches state that diabetes can be controlled if it is detected at an early stage. Scientists are becoming more interested in classification algorithms in diagnosing diseases. In this study, we have analyzed the performance of five classification algorithms namely naïve Bayes, support vector machine, multi layer perceptron artificial neural network, decision tree, and random forest using diabetes dataset that contains the information of 2000 female patients. Various metrics were applied in evaluating the performance of the classifiers such as precision, area under the c
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