Background: Preeclampsia (PE) is a serious complication of pregnancy and one of the main causes of maternal and neonatal mortality and morbidity in the world. Finding a biomarker with high sensitivity and specificity could lead to prediction and early diagnosis of the disease and reduces its complications. In this study, we evaluated diagnostic accuracy of Soluble fms-like tyrosine kinase-1 (sFlt-1) to Placental growth factor (PlGF) ratio for diagnosis of PE. Methods: The cases included 23 mild, 15 severe preeclamptic patients, and 20 normal term pregnant women as control referred to GYN ward of the Persian Gulf Hospital in Bandar Abbas from 2014 to 2016. Levels of sFlt-1 and PlGF were measured. Receiver Operating Characteristic (ROC) curve analysis was applied to calculate diagnostic accuracy of sFlt-1/PlGF ratio. Results: The mean Level of sFlt-1/PlGF in PE patients (91.33 ng/ml) was significantly higher than control women (17.62) (P<0.001). ROC curve analysis showed sFlt-1/PlGF ratio diagnostic accuracy in preeclamptic patients with Area Under Curve (AUC) of 0.90, the best cutoff value of 24.96, sensitivity and specificity of 84.2 and 85.0%, respectively. Conclusions: Our data showed sFlt-1/PlGF ratio has higher accuracy for differentiating PE patients from non-PEs in comparison with its power for differentiating severe or early onset forms of the disease.

Our results indicate that NDM-1-producing K. pneumoniae ST 13 and ST 392 are disseminated in our region. Moreover, one of our major concerns is that these isolates may be more prevalent in the near future. Tracking and urgent intervention is necessary for control and prevention of these resistant isolates.

To diagnose the malignancy in thyroid tumor, neural network approach is applied and the performances of thirteen batch learning algorithms are investigated on accuracy of the prediction. Therefore, a back propagation feed forward neural networks (BP FNNs) is designed and three different numbers of neuron in hidden layer are compared (5, 10 and 20 neurons). The pathology result after the surgery and clinical findings before surgery of the patients are used as the target outputs and the inputs, respectively. The best algorithm(s) is/are chosen based on mean or maximum accuracy values in the prediction and also area under Receiver Operating Characteristic Curve (ROC curve). The results show superiority of the network with 5 neurons in the hidden layer. In addition, the better performances are occurred for Polak-Ribiere conjugate gradient, BFGS quasi-newton and one step secant algorithms according to their accuracy percentage in prediction (83%) and for Scaled Conjugate Gradient and BFGS quasi-Newton based on their area under the ROC curve (0.905).

Objectives: This study aimed to acquire knowledge about the factors affecting smartphone adoption for accessing information in medical settings in Iranian Hospitals. Methods: A qualitative and quantitative approach was used to conduct this study. Semi-structured interviews were conducted with 21 medical residents and interns in 2013 to identify determinant factors for smartphone adoption. Afterwards, nine relationships were hypothesised. We developed a questionnaire to test these hypotheses and to evaluate the importance of each factor. Structural equation modelling was used to analyse the causal relations between model parameters and to accurately identify determinant factors. Results: Eight factors were identified in the qualitative phase of the study, including perceived usefulness, perceived ease of use, training, internal environment, personal experience, social impacts, observability and job related characteristics. Among the studied factors, perceived usefulness, personal experience and job related characteristics were significantly associated with attitude to use a smartphone which accounted for 64% of the variance in attitude. Perceived usefulness had the strongest impact on attitude to use a smartphone. Conclusion: The factors that emerged from interviews were consistent with the Technology Acceptance Model (TAM) and some previous studies. TAM is a reliable model for understanding the factors of smartphone acceptance in medical settings.Keywords: consumer health information; information management; information seeking behaviour; social media Key messages• Perceived usefulness, personal experience and job related characteristics were the main factors predicting attitude to use a smartphone for accessing information in medical settings.• The Technology Acceptance Model (TAM) provides a good framework for understanding the factors behind the adoption of smartphones for accessing information in medical settings.• Librarians in medical settings and hospitals should provide health care professionals with highly used and licensed mobile medical resources.

Introduction:Pregnancy and childbirth are important periods of women’s life that cause hormonal and bodily changes, and these changes could have significant effects on sexual function.Aim:The aim of this study was to assess the effectiveness of PLISSIT-based counselling model on the sexual function of women during the first six months after childbirth.Material and Methods:This was a randomized controlled clinical trial study from June to November, 2015. Ninety lactating women,with at least one sexual problem, were included in this study. Samples were recruited and randomized into two groups (intervention group and control group). Demographic and obstetric information, Edinberg postpartum depression, Larson’s sexual satisfaction and female sexual function index questionnaire were used. Data were collected from participants at two points: before consultation and 4weeks after consultation. The statistical analyses were performed using SPSS software and Data were analyzed using the Paired t-test,dependent t-test with parametric data and Chi-square tests.Results:Ninety women who were the nulliparous and lactating criteria subjects were randomly divided into two groups and all recruited women completed the questionnaires. Mean score of sexual function was 19.35 before consultation and 27.90 after consultation in experimental group. In the control group, mean score of sexual function was 20.55 before consultation and 22.41 after consultation. These differences were statistically significant in pre-counseling stage and 4 weeks after counseling in the two groups (P<0.001 and P=0.002). Four weeks after consultation, there was significant difference in the mean score of sexual function between the control and experimental groups (P<0.001).Conclusion:Based on the result of this study, sexual problems in lactating women decreased by using the PLISSIT model. The use of the PLISSIT model is recommended in health care setting.