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جستجوی مقالات مرتبط با کلیدواژه "chi-square distribution" در نشریات گروه "پزشکی"

جستجوی chi-square distribution در مقالات مجلات علمی
  • Hamid Hashemi Beni, Zahra Shafiei, Ahmad Ghadami
    Background

    Cleaning is one of the most important steps in preparing surgical instruments for reuse. Thorough cleaning can ensure more effective sterilization, protect treatment teams and patients from transmissible infections, and extend the life of surgical instruments. This study was conducted to compare the manual, automated, and ultrasonic methods of cleaning surgical instruments. 

    Methods

    In this quasi-experimental study, three types of surgical instruments, namely curved hemostats, suction tips, and Metzenbaum scissors, (n=90) from among 20 surgical sets were randomly selected and assigned to three cleaning groups viz manual, automated, and ultrasonic. After the instruments were cleaned, surface protein and blood residue swab tests were conducted and the results were recorded on a data-registration form. Data were analyzed using SPSS version 16 and descriptive and inferential statistical methods.

    Results

    According to the research results, in manually cleaned instruments group, 8 (26.7%) tested positive for blood and 10 (33.3%) tested positive for protein. Of the 30 automatically cleaned instruments, 6 (20%) tested positive for blood and 7 (23.3%) tested positive for protein and of the 30 ultrasonically cleaned instruments, 1 (3.3%) tested positive for blood and protein. The chi-square test showed a statistically significant difference between the three methods of cleaning residual blood and protein from the surgical instruments (p<0.05).

    Conclusion

    The results revealed that according to the research results, of the three cleaning methods, ultrasonic cleaning was by far the most effective in removing blood and protein residues from the surgical instruments. Hence, we suggest that ultrasonic cleaning can be routinely utilized as an efficient cleaning method in medical centers.

    Keywords: Chi-square distribution, Humans, Membrane proteins, Sterilization, Suction, Surgical instruments, Ultrasonics
  • F Fattahi, S Haghighat*, N Babaei, Z Amirkhaki, F Khajavi, K Torabi
    Background and Aim

    Temporomandibular disorder (TMD) is a multifactorial problem caused by many reasons. There is still controversy about the effect of different types of occlusal disorder on TMD. This study was designed to determine the effects of centric and assisted and unassisted non-working interferences on TMD.

    Materials and Methods

    In this cross-sectional study, 100 dental students, including 64 males and 36 females with the age range of 18 to 24 years old, were examined. Subjects with a history of systemic or muscular diseases and orthodontic treatment were excluded. TMD signs and symptoms including maximum mandibular opening limitation, maximum lateral movement limitation, maximum protrusion limitation, deviation and deflection, joint pain and tenderness, joint sounds, and masticatory muscle tenderness were examined. Subjects were also examined for having centric interferences and eccentric interferences including assisted and unassisted non-working interferences. Data were analyzed using the chi-square test and independent-sample T-test.

    Results

    Subjects with centric interference had a significantly higher number of clicks (P=0.02), medial pterygoid tenderness (P=0.009), and right medial pterygoid tenderness (P=0.007). We could also find a significantly higher number of clicking in subjects with assisted non-working interference (P=0.002).

    Conclusion

    The findings of the present study suggest that different types of occlusal interference, specially centric and assisted non-working interferences, can lead to TMD signs and symptoms.

    Keywords: Temporomandibular Joint Disorders, Traumatic Dental Occlusions, Chi-Square Distribution
  • فرزاد فیروزی جهانتیغ *، راضیه علیزاده
    مقدمه
    تنگی شریان کاروتید بدون علامت یکی از عواملی است که سکته مغزی ایجاد می کند. عوامل دیگر مانند فشار خون بالا، بیماری های قلبی، استعمال دخانیات، دیابت و عدم فعالیت بدنی ممکن است همچنین موجب بیماری شوند. فهمیدن و تشخیص عواملی که موجب تنگی شریان کاروتید می شوند در پیشگیری از سکته مغزی حاد، کمک خواهد کرد. با استفاده از روش های داده کاوی، این مطالعه به منظور کشف قوانین و روابطی که در شناسایی تنگی شریان کاروتید بدون علامت موثر هستند انجام شد.
    مواد و روش ها
    برای پیدا کردن بهترین روش، رگرسیون لجستیک، الگوریتم ژنتیک و آزمون مجذور کای به منظور پیش بینی تنگی شریان کاروتید در بیماران استفاده شدند.
    یافته ها
    372 شرکت کننده، 173 زن (46/5 درصد) و 199 مرد (53/5 درصد) با میانگین سنی 5/29 ± 70/74 مورد بررسی قرار گرفتند. نتایج نشان داد جنسیت، استعمال دخانیات، بیماری عروق کرونر، فشارخون بالا، بی تحرکی، پیشگیری از بارداری به وسیله دارو، اورمی (مقادیر بیش از حد اوره و سایر ترکیبات نیتروژنی در خون) و میزان نبض محیطی عوامل خطر معنی داری برای شریان کاروتید بدون علامت هستند. علاوه بر این الگوریتم ژنتیک در مقایسه با رگرسیون لجستیک یک روش بهتری برای این رویکرد بود.
    نتیجه گیری
    مطالعه ما نشان داد که بیماری عروق کرونر و فشار خون بالا عوامل مهمی در پیش بینی و پیش آگهی تنگی شریان کاروتید بدون علامت هستند.
    کلید واژگان: داده کاوی, شریان های کاروتید, توزیع مربع کای
    Farzad Firouzi Jahantigh*, Razieh Alizadeh
    Introduction
    Asymptomatic carotid artery stenosis is one of the factors that causes stroke. Other factors such as high blood pressure, cardiac diseases, smoking, diabetes, and physical inactivity may also cause the disease. Understanding and identifying the factors that cause carotid artery stenosis will help in prevention of acute stroke. Using data mining techniques, this study was aimed to discover the rules and relations that are effective in identifying asymptomatic carotid artery stenosis.
    Materials And Methods
    To find the best approach, logistic regression (LR), genetic algorithm (GA), and chi-square test were used to predict carotid artery stenosis in patients.
    Results
    372 participants, 173 women (% 46.5) and 199 men (% 53.5), with an average age of 70.74± 5.29 were investigated. The results showed gender, smoking, coronary artery disease, high blood pressure, inactivity, prevention of pregnancy by medication, uremia (excessive amounts of urea and other nitrogenous compounds in the blood), and pulse rate environment are the significant risk factors for asymptomatic carotid artery. In addition, GA was a better method for this approach compared to LR.
    Conclusion
    Our study revealed that coronary artery disease and hypertension are important factors in predicting and prognosis of asymptomatic carotid artery stenosis.
    Keywords: Data Mining, Carotid Arteries, Chi-Square Distribution
نکته
  • نتایج بر اساس تاریخ انتشار مرتب شده‌اند.
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