The Effectiveness of Fluoride Varnish and Fissure Sealant in Elementary School Children: A Systematic Review and Meta-Analysis.

Background: Highly necessary to evaluate the effectiveness of preventive interventions to prioritize them at the community level. We aimed to systematically investigate the related studies on the effects of fluoride varnish and fissure sealant on dental caries in 6-12 children. Methods: We searched PubMed, EMBASE, Web of Science, Cochrane Library and Scopus databases using Fluoride Varnish, Fissure Sealant, Caries, and Oral Health keywords. The timeframe selected to search for articles is from 2000 to Dec 2020. CMA software: 2 (Comprehensive Meta-Analysis) was used to perform the meta-analysis. The intervention groups in this study were fluoride varnish and fissure sealants, each of them compared to the control groups. Results: We included nine studies. In the intervention group 84,380 and control group 11,254 individuals were studied. Eight of the studies were Randomized Clinical Trial (RCT) and Field RCT, and two was non-RCT. In the overall Fluoride Varnish efficacy study, 4 were fully effective, 1 was ineffective, and all 4 were completely effective for Fissure Sealant. There was a significant difference between decayed, missing, and filled permanent teeth (DMFT) and decayed, missing, and filled primary teeth (dmft) indices in both interventions and comparison groups. Moreover, the mean difference of DMFT for Fluoride Varnish and Fissure Sealant in the intervention and control groups were -0.55 and -0.29, respectively (P=0.00). Conclusion: Due to the efficacy of fissure sealant and fluoride varnish in preventing dental caries in children aged 6-12 yr, these interventions can be considered as health priorities of societies and health systems interventions in countries.

Malaria situation in a clear area of Iran: an approach for the better understanding of the health service providers' readiness and challenges for malaria elimination in clear areas.

BACKGROUND: Malaria mortality and morbidity have decreased in recent years. Malaria elimination (ME) and effective efforts to achieve ME is one of the most important priorities for health systems in countries in the elimination phase. In very low transmission areas, the ME programme is faced with serious challenges. This study aimed to assess the trend while getting a better understanding of Health Service Providers' (HSPs) readiness and challenges for ME in a clear area of Iran. METHODS: This study was performed in two phases. At first, the malaria trend in East Azerbaijan Province, was surveyed from 2001 to 2018; afterward, it was compared with the national situation for a better understanding of the second phase of the study. Data were collected from the Ministry of Health's protocol and the health centre of the province. In the second phase, malaria control programme experts, health system researchers, and health managers' opinions were collected via in-depth interviews. They were asked regarding HSPs readiness and appropriate Malaria Case Management (MCM) in a clear area and possible challenges. RESULTS: A total of 135 and 154,560 cases were reported in the last 18 years in East Azerbaijan Province and Iran, respectively. The incidence rate decreased in East Azerbaijan Province from 0.4/10,000 in 2001 to zero in 2018. Furthermore, no indigenous transmission was reported for 14 years. Also, for the first time, there was no indigenous transmission in Iran in 2018. The main elicited themes of HSPs readiness through in-depth interviews were: appropriate MCM, holistic and role-playing studies for assessment of HSPs performance, system mobilization, improving identification and diagnosis of suspected cases in the first line. Similarly, the main possible challenges were found to be decreasing health system sensitivity, malaria re-introduction, and withdrawing febrile suspected cases from the surveillance chain. CONCLUSION: Health systems in eliminating phase should be aware that the absence of malaria cases reported does not necessarily mean that malaria is eliminated; in order to obtain valid data and to determine whether it is eliminated, holistic and role-playing studies are required. Increasing system sensitivity and mobilization are deemed important to achieve ME.

Factors associated with therapeutic target achievement in the control of complications in consequence of diabetes: A hospital-based study in west of Iran.

BACKGROUND AND AIM: The goal of diabetes management is to enhance the performance of the surveillance system to perpetuate optimal blood sugar, blood pressure and cholesterol levels in the normal values. This paper aimed to identify factors associated with therapeutic target achievement in the control of complications in consequence of diabetes. METHODS: In this cross-sectional study, a secondary analysis was performed on data obtained in the surveillance center of patients referred to in Makoo city, West Azerbaijan Province. The main interested variables included Fasting Blood Sugar (FBS), HbA1c, triglycerides, cholesterol, Low Density Lipoprotein (LDL), High Density Lipoprotein (HDL) diastolic and systolic blood pressure, duration of diabetes, family history of diabetes, early and late complications of diabetes, treatment received, history of smoking. RESULTS: Average age of the patients with diabetes mellitus, insulin-dependent was 35.43 (SD = 17.25) and in patients of diabetes mellitus 53.37 (SD = 10.89), which was significantly different (p-value = 0.001). Frequency amount of fasting blood sugar in diabetes mellitus, insulin-dependent and diabetes mellitus, type II was 64.30% and 66.0%, respectively. Only 19.0% of patients with diabetes mellitus, insulin-dependent and 13.90% of diabetes mellitus, type II breached to the optimum level of blood glucose control. CONCLUSIONS: This study found that a considerable proportion of subjects with diabetes mellitus, insulin-dependent and diabetes mellitus, type II did not achieve the goals of care guidelines of Iran on secondary prevention of complications related to diabetes, especially vascular complication.

Comparative study of different wavelet-based neural network models to predict sewage sludge quantity in wastewater treatment plant.

In this study, artificial neural networks (ANNs) including feed forward back propagation neural network (FFBP-NN) and the radial basis function neural network (RBF-NN) were applied to predict daily sewage sludge quantity in wastewater treatment plant (WWTP). Daily datasets of sewage sludge have been used to develop the artificial intelligence models. Six mother wavelet (W) functions were employed as a preprocessor in order to increase accuracy level of ANNs. In this way, a 4-day lags were considered as input variables to conduct training and testing stages for the proposed W-ANNs. To compare performance of W-ANNs with traditional ANNs, coefficient of correlation (R), root mean square error (RMSE), mean absolute error (MAE), and Nash-Sutcliffe efficiency coefficient (NSE) were considered. In the case of all wavelet functions, it was found that W-FFBP-NN (R = 0.99 and MAE = 5.78) and W-RBF-NN (R = 0.99 and MAE = 6.69) models had superiority to the FFBP-NN (R = 0.9 and MAE = 21.41) and RBF-NN (R = 0.9 and MAE = 20.1) models. Furthermore, the use of DMeyer function to improve ANNs indicated that W-FFBP-NN (RMSE = 7.76 and NSE = 0.98) and W-RBF-NN (RMSE = 9.35 and NSE = 0.98) approaches stood at the highest level of precision in comparison with other mother wavelet functions used to develop the FFBP-NN and RBF-NN approaches. Overall, this study proved that application of various mother wavelet functions into architecture of ANNs led to increasing accuracy of artificial neural networks for estimation of sewage sludge volume in the WWTP.

Derivation of optimal equations for prediction of sewage sludge quantity using wavelet conjunction models: an environmental assessment.

Determining the quantity of sewage sludge is a major component of designing sludge treatment units and their handling and disposal facilities including its fluctuation over a wide range. In the present study, the capabilities of the hybrid wavelet-gene expression programming (WGEP), wavelet-model tree (WMT), and wavelet-evolutionary polynomial regression (WEPR) models have been investigated to predict the quantity of daily sewage sludge. In the first step, the single gene expression programming (GEP), model tree (MT), and evolutionary polynomial regression (EPR) models were employed to predict the amounts of sewage sludge based on the input vector content produced by the sewage sludge data series, which ranged from lagged-1 day to lagged-4 days. In this study, the WGEP, WMT, and WEPR models were obtained through the combination of two methods: discrete wavelet transforms (DWT) and simple GEP, MT, and EPR models. Incidentally, the models were implemented by transforming the input datasets using the Meyer wavelet function in order to reveal the temporal and spectral information contained within the data, and subsequently, this transformed data was used as the input vectors for the simple GEP, MT, and EPR models. In addition, the results of the wavelet conjunction model were compared with those obtained using the simple GEP, MT, and EPR models. The study indicated that the performance of the wavelet coupled-models was better than the simple models. The quantitative comparisons demonstrated that the WMT, with root mean square error (RMSE) of 8.15 and R = 0.98, performed better than the WGEP (RMSE = 15.26 and R = 0.92) and WEPR (RMSE = 18.20 and R = 0.89) models. Overall, the use of wavelet conjunction models provided an acceptable performance in order to improve precision in one of the most effective parameters involved in the design of a wastewater treatment plant (WWTP).

A Diagnostic Analysis of Erroneous Language in Iranian Medical Specialists' Research Papers.

BACKGROUND: As English has increasingly become the lingua franca in science and international journals require native-like academic writing standards from nonnative researchers, there is more pressure on nonnative scholars to write their research articles more accurately and appropriately in English. This study was conducted to determine the most-occurring language-related errors which Iranian medical authors/researchers commit while trying to have their research published in international English journals. Also, this article seeks to provide useful guidelines to reduce such linguistic mistakes. METHODS: The present study investigated the most common language-related errors in Iranian medical specialists' research articles. To this end, the first drafts of 60 published research articles in medical sciences were cross-checked against their peer-reviewed published versions in order to identify the most frequent non-target language forms which received discoursal, lexical, grammatical, and mechanical revisions by peer editors. RESULTS: The findings revealed that the editors had surprisingly dealt with discoursal errors more than any other linguistic aspects of these research articles. This was followed by lexical replacements. In third place were grammatical improvements, where erroneous structures mostly related to tenses, usage of articles and prepositions, and agreement between verbs and nouns were treated. The least common revisions were on the mechanics of academic writing, consisting of hyphenating, spelling, case lettering, spacing, and spacing with commas. CONCLUSION: Although most of the Iranian medical authors/researchers enjoyed a good level of proficiency in English, their manuscripts required discoursal, lexical, grammatical, and mechanical revisions before publication in credited international journals.