Background: The study was aimed to evaluate the safety and efficacy of fentanyl and pethidine on the sedative quality of patients who underwent phacoemulsification cataract surgery with Propofol. Materials and Methods: In this double-blind randomized controlled clinical trial, patients who were candidates for elective phacoemulsification surgery with topical anesthesia were enrolled. The selected patients were randomly allocated into the two groups for receiving sedation with Propofol-Pethidine (PP) or propofol-fentanyl (PF) combinations. Demographic characteristics, hemodynamic parameters before, during, and after the operation, sedation and pain scores, and patients' and surgeons' satisfaction scores were compared in the two studied groups. Results: In this trial, 70 patients (35 patients in each group) have completed the study. Mean (standard deviation) operation time was 22.9 (6.8) and 25.46 (7.7) minutes in PF and PP groups (P = 0.118).Mean pain score in PF 0.46 (0.14) was significantly higher than PP groups 0.236 (0.06) (P = 0.011). The mean value of diastolic and systolic blood pressures, pulse rate, and mean arterial pressure dioxide were significantly decreased in both PF and PP groups (P_Time< 0.001), although there was no significant difference between groups. Conclusion: Our findings indicated the equivalence effects on hemodynamic parameters for both pethidine and fentanyl in combination with propofol in which they could provide appropriate sedation and safe anesthesia with lower complications and acceptable patients' and surgeons' satisfaction.

Background: The etiology of nausea and vomiting during pregnancy (NVP) is unclear and appears multifactorial. It has been shown that the physiological changes associated with NVP include changes in the levels of adipocytokines. Therefore, we investigated the association of nausea and vomiting during pregnancy with visfatin, β-human chorionic gonadotropin (βHCG), and perceived stress. Materials and Methods: In this cross-sectional study, 100 nulliparous pregnant women aged 18–45 years were evaluated. Participants completed two questionnaires including the Index of Nausea, Vomiting, and Retching (INVR) and Perceived Stress Scale (PSS) in the three trimesters of pregnancy. They also referred to the laboratory to conduct the biochemical examinations including serum visfatin and βHCG levels in three trimesters. The obtained data were analyzed by SPSS 16 using statistical repeated-measures analysis of variance, Friedman, Bonferroni, and Wilcoxon post hoc tests. Marginal model (method generalized estimating equation [GEE]) was performed to assess the predictors of the INVR in the participants. Results: INVR, PSS, visfatin, and βHCG levels significantly decreased from the first trimester to the third trimester of pregnancy (P ≤ 0.001). As a result of simple marginal model (GEE method), visfatin was predicted log βHCG (P = 0.035). Furthermore, the multiple marginal model revealed that the two predictors of βHCG (P = 0.01) and PSS (P ≤ 0.001) were positively correlated with the INVR. Furthermore, visfatin had an indirect positive effect on INVR. Conclusion: The present study showed that visfatin can be indirectly related with nausea and vomiting throughout pregnancy. Furthermore, it seems that fluctuations in visfatin levels are independent of weight gain during pregnancy.

Background: The artificial intelligence field is obtaining ever-increasing interests for enhancing the accuracy of diagnosis and the quality of patient care. Deep learning neural network (DLNN) approach was considered in patients with brain stroke (BS) to predict and classify the outcome by the risk factors. Materials and Methods: A total of 332 patients with BS (mean age: 77.4 [standard deviation: 10.4] years, 50.6% – male) from Imam Khomeini Hospital, Ardabil, Iran, during 2008–2018 participated in this prospective study. Data were gathered from the available documents of the BS registry. Furthermore, the diagnosis of BS was considered based on computerized tomography scans and magnetic resonance imaging. The DLNN strategy was applied to predict the effects of the main risk factors on mortality. The quality of the model was measured by diagnostic indices. Results: The finding of this study for 81 selected models demonstrated that ranges of accuracy, sensitivity, and specificity are 90.5%–99.7%, 83.8%–100%, and 89.8%–99.5%, respectively. Based on the optimal model (tangent hyperbolic activation function with the minimum–maximum hidden units of 10–20, max epochs of 400, momentum of 0.5, and learning rate of 0.1), the most important predictors for BS mortality were time interval after 10 years (accuracy = 92.2%), age category (75.6%), the history of hyperlipoproteinemia (66.9%), and education level (66.9%). The other independent variables are at moderate importance (66.6%) which include sex, employment status, residential place, smoking habits, history of heart disease, cerebrovascular accident type, blood pressure, diabetes, oral contraceptive pill use, and physical activity. Conclusion: The best means for dropping the BS load is effective BS prevention. DLNN strategy showed a surprising presentation in the prediction of BS mortality based on the main risk factors with an excellent diagnostic accuracy. Moreover, the time interval after 10 years, age, the history of hyperlipoproteinemia, and education level are the most important predictors for BS.

Background: Whether early lumbar puncture (LP) and blood indicators are suitable as diagnostic criteria and helpful to treatment strategies for newborns remains to be solved. The study was to evaluate the value of cerebrospinal fluid (CSF) at the first LP and blood indicators at the similar time in the early diagnosis and the drug therapy of neonatal bacterial meningitis. Materials and Methods: We conducted a retrospective observational study of 997 infants with suspected bacterial meningitis between June 2012 and June 2018. CSF and blood parameters were evaluated by three stepwise logistic models to assess their ability: to distinguish bacterial meningitis from nonbacterial meningitis, to distinguish positive CSF culture from negative, and to distinguish Gram-positive bacteria from negative. Results: Of the 997 neonates, 236 (23.67%) were later diagnosed as bacterial meningitis. Of the neonates with meningitis, 54 (22.88%) had positive CSF culture results. And of neonates with positive CSF culture, 27 (50%) had Gram-positive results. One or more CSF indicators were added to the three models. Only blood hypersensitive C-reactive protein and blood lactate dehydrogenase were added to the first model, while no blood parameters was added to the other two models. The areas under the effect-time curves of the three models were 0.91 (95% confidence interval [CI]: 0.89–0.92, P < 0.001), 0.69 (95% CI: 0.63–0.75, P < 0.001), and 0.86 (95% CI: 0.74–0.94, P < 0.001), respectively. Conclusion: LP was irreplaceable predictor of bacterial meningitis, and comprehensive analysis of CSF indicators can predict the offending organism, which enables refinement of therapy.

Background: The present study aimed to provide a field-tested model of constituting factors affecting mental health in young Iranian adolescents. Materials and Methods: In this cross-sectional study, a conceptual model was proposed based on an extensive literature review. A total of 254 young adolescents aged 11–14 years were recruited from north, south, east, and west regions of Tehran megacity by a random cluster sampling procedure, of whom 244 adolescents participated. The adolescents and their mothers altogether completed eight questionnaires pertaining to the proposed conceptual model: (1) Strengths and Difficulties Questionnaire (SDQ), (2) Childhood Experience of Care and Abuse Questionnaire, (3) Child Exposure to Domestic Violence Scale, (4) Drug Abuse Screening Test-10, (5) Baumrind Parenting Style Questionnaire, (6) Conflict Behavior Questionnaire, (7) General Health Questionnaire-28, and (8) Garmaroodi Socioeconomic Status Questionnaire. The statistical analysis was performed using structural equation modeling. Results: This study demonstrated that parent mental health (b = −0.111), experience of father's care (b = −1.112), conflict with mother (b = 0.309), conflict with father (b = 0.135), and exposure to domestic violence (b = 0.217), as well as age (b = 0.93) and gender (b = 0.139), had direct effect on adolescent mental health (all P < 0.05). Further, the results showed that exposure to domestic violence and conflict with mother had the greatest direct impact on adolescent mental health among all other family-related factors, followed by conflict with father and parent mental health. Conflict with mother and conflict with father also affected adolescent mental health indirectly through experience of domestic violence and had a mediating effect for the influence of several other factors on adolescent mental health, thus playing an important role in the pathway leading to young adolescent mental health status in the Iranian population. Conclusion: Overall, the final model proved to be fit and the factors constituting the final model were able to predict 88% of the variations in the mental health of Iranian adolescents. This model can guide clinical psychologists, psychiatrists, and other mental health workers in a more realistic and effective prevention or treatment planning for their young clients. Moreover, it may help in arriving at a comprehensive preventive policymaking for mental health policymakers.