Tehran University Medical Journal

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Background: The most frequently used test for evaluation of fetal health is the Non Stress Test (NST). Unfortunately it has a high incidence of false positive results. The combination of vibroacoustic stimulation with the NTS has been shown to reduce non reactive results.
Methods: A tests assessment method was chosen with a simple randomized sampling. 40 pregnant women with non reactive NST in the first 20 minutes who received VAS in one of Tehran University's Hospitals were compared with BPP scores. A vibroacoustic stimulation was applied for a 3 seconds on the maternal abdomen and fallowed within 10 minutes.Data collection tools were NST, sonography instruments ,NST result paper, tooth brusher, watch, demographic questioner and check list. Data analysis was made by descriptive static and by using the Fisher's Exact Test (with level of significant at p<0/05). All statistical analysis were performed using an spss/win.
Results: After VAS, 70% of non reactive tracing became reactive. All cases with fetal reactivity response after a VAS had a subsequent BPP score of 8 (negative predictive value of 100%). False positivity of VAS was lower than NST.
Conclusion: VAS offers benefits, by decreasing the incidence of non reactive test and reducing test time. VAS lowers the rate of false positive NST. VAS is safe and allows more efficient of prenatal services. This test could be used as a rapid antepartum test to predict fetal well-being.

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Background: Patch forms of glyceryl trinitrate (GTN), also known as nitroglyceril, have proved useful in the management of dysmenorrhea. Increased intrauterine pressure due to exaggerated myometrial contractions is an important factor in the pathogenesis of dysmenorrhea. In a recent study, it was found that GTN caused a significant reduction in the contraction frequency of human myometrial strips. The object of this study is to evaluate the efficacy of GTN ointment in treating primary dysmenorrhea.

Methods: In this double-blind randomized placebo-controlled study, we enrolled 112 unmarried subjects with the complaint of moderate to severe primary dysmenorrhea. They were between 18-30 years of age with normal BMI (19-27) and all had normal results upon examination by pelvic ultrasound. None of these patients had a history anemia, previous pelvic surgery or cardiovascular diseases. Randomly divided in two groups using odd and even numbers, 56 of the subjects received 5 mg 1% GTN ointment and another 56 received a placebo. Before starting the treatment, severity of pain was recorded using a visual scale method. Ointment A (GTN 1%) or ointment B (placebo) was applied to special papers which were in turn applied to the skin of the abdomen below the umbilicus, and left there for the entire treatment period of four hours. The severity of pain and side effects of the treatment were recorded at intervals of 15 min, 30 min, 1 h, 2 h and 4 h after application the treatment. After four hours, the treatment was removed and the skin checked for erythema.

Results: There was no difference in severity of pain 15 min after treatment, but pain was less severe in the GTN group from the 30-min interval through the 4-h interval, with the least pain felt at the 2-h interval. This decrease in pain lasted through the 4-h interval. Side effects, which were more common in the GTN group than the placebo group (P<0.05), included headache (48.3% vs. 19.5%, respectively), dizziness and flushing.

Conclusions: GTN performed well in relieving primary dysmenorrheal discomfort however, the side effect of headache reduced its efficacy and tolerability.

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Background: Data mining as a multidisciplinary field is rooted in the fields such as statistics, mathematics, computer science and artificial intelligence and has been gaining momentum in scientific, managerial, and executive applications in health care. Data mining can be defined as the automated extraction of valuable, practical and hidden knowledge and information from large data. Applying data mining in medical records and data is of utmost importance for health care givers and providers and brings vital and valuable outcomes. Data mining can help doctors come up with better recommendations and plans for treatment which actually in many respects have significant impact on patients’ life and satisfaction In this paper we have proposed and utilized data mining methods to extract hidden information in medical records of pelvis stone patients with ureteral stone. We have tried to design a decision support system model to be applicable for selecting type of treatment for these groups of patients.
Methods: We gathered needed information from Shahid Hashemi Nejad hospital. In this research we have used decision tree as a data mining tool, for selecting suitable treatment for patients with ureteral stone. This model can predict probability of success of each treatment. 
Results: In this research we extracted effective attributes in selecting type of treatment for patients with ureteral stone.
Conclusions: By using this model we can have eight percent improvement in number of patients who have stone free output after treating. In fact, this model has a better functionality than expert system of hospitals.