Management of Baseline Measurements in Statistical Analysis of 2×2 Crossover Trials

 Introduction: Crossover designs have applications in a wide range of sciences. The simplest and most common of such designs are the two-period, two-treatment (2×2) crossover. As a consequence, each subject provides a 4×1 vector of responses for data analysis in the following chronological order: baseline (period 1), post-baseline (period 1), baseline (period 2), and post-baseline (period 2).Methods: We considered three types of analytic approaches for handling the baselines:1) analysis of variance (ANOVA) method which ignores the first or both period baselines or use a change from baseline analysis 2) analysis of covariance (ANCOVA) method which uses an analysis of covariance where linear functions of one or both baselines are employed as either period-specific or period-invariant covariates 3) Joint modeling method that conducts joint modeling of a linear function of the baseline and post-baseline responses with certain mean constraints for the baseline responses. The crossover clinical trial data was analyzed, using the proposed models.          Results: Based on the results on real data among all mentioned models, the first model (direct comparison of post-treatment values) and the second model (post-treatment measurement subtracts corresponding baseline) had the lowest and the highest standard errors, respectively. With respect to Akaike Information Criterion (AIC), the fifth model (comparison of post-treatment values adjusted by all available baseline data) and the eighth model (comparison of post-treatment values adjusted by difference and sum of all available baseline data) had the lowest magnitude, and the ninth model (modeling period baseline jointly with post-treatment values) had the highest AIC for both variables which the values of AIC were 518.1, 520.9 and 1137.8, respectively.Conclusion: To sum up, it is found that baseline data of crossover trial may be used to improve the efficiency of treatment effect estimation when applied appropriately.

Comparison of generalized estimating equations (GEE), mixed effects models (MEM) and repeated measures ANOVA in analysis of menorrhagia data

     Menorrhagia is one of the most common gynecological problem and leading causes of poor quality of life and iron deficiency anemia in women of reproductive age. Research in gynecological field relies heavily on repeated measure designs. Repeated measure studies are helpful in understanding how factors of interest change over time. Our goal is to apply statistical methods which are appropriate for analyzing repeated measure data such as gynecological data. Three statistical methods were performed by data collection from 100 patients with menorrhagia. One-hundred patients were randomly assigned to two groups, i.e. intervention group (Urtica Dioica and mefenamic acid) and control group (placebo and mefenamic acid) with an equal size of 50. In this study, generalized estimating equations (GEE) and mixed effects models (MEM) were used for analyzing menorrhagia data to determine the effect of hydroalcoholic extract of Urtica Dioica on Menorrhagia. Finally, these methods are compared to the conventional repeated measures ANOVA (RM-ANOVA).Based on the results, the three methods are found to be similar in terms of statistical estimation, the amount of bleeding before and after treatment between and within groups was compared. Results showed the average amount of bleeding was reduced significantly (P˂0/001). The average menorrhagia score in the third month (second cycles after intervention) were 91.38(71.432) and 149.40(127.823) in Urtica Dioica and control groups, respectively. The difference between the two groups was statistically significant (p =0.036). Because their advantages, GEE and MEM should be strongly considered for the analysis of repeated measure data. In particular, GEE should be utilized to explore overall average effects. When in addition to overall average effects, subject-specific effects are of primary interest, MEM should be utilized. With respect to these methods, it seems the extract of Urtica Dioica can be effective in reducing the amount of menstrual bleeding in women of reproductive age with Menorrhagia.

Professional socialization in clinical nurses- A phenomenological study

زمینه و هدف: اجتماعی شدن، فرآیند پذیرش نقش های حرفه ای و یک راه واقعی برای توسعه هویت حرفه ای به شمار می رود؛ لذا این مطالعه با هدف تبیین این مفهوم در پرستاران در بالین صورت گرفته است. روش بررسی: در این مطالعه توصیفی از نوع کیفی و با رویکرد پدیدارشناسی انجام شده است. 10 نفر پرستار بالینی از بیمارستان های آموزشی در شهرهای شهرکرد و تهران در مطالعه مشارکت داشتند. داده ها از مصاحبه های نیمه ساختار یافته و با تحلیل به کمک روشVan Manen استخراج گردید. یافته ها: شش درون مایه از تحلیل مصاحبه های پرستاران بالینی استخراج گردیدکه با کمک آن ها مفهوم اجتماعی شدن حرفه ای با درون مایه های شناوری شایستگی، استقلال عملی، پویایی بالینی، موردحمایت جامعه قرار گرفتن، دلبستگی حرفه ای و مشارکت منفعل گروهی تبیین گردید. نتیجه گیری: نتایج این مطالعه نشان داد که توصیف های تجارب پرستاران، راهنمای عملی برای مدیران آموزشی جهت بازبینی برنامه های درسی پرستاری وهمچنین مدیران پرستاری در برنامه های اجتماعی شدن مجدد بعد از انتقال نقش را فراهم نماید. این مطالعه، ضمن تبیین تجارب در خصوص مفهوم اجتماعی شدن در حرفه پرستاری، نقطه آغازی برای پژوهش بیشتر مفهوم و گسترش بدنه دانش حرفه ای پرستاری خواهد بود

Comparison of the Precision of Measurements in Three Types of Micropipettes according to NCCLS EP5-A2 and ISO 8655-6

Micropipettes or piston pipettes are used to make most volume measurements in fields such as health, chemistry, biology, pharmacy and genetics. Laboratories must ensure that results obtained using these instruments are reliable; therefore, it is necessary to calibrate micropipettes. Before the start of the calibration process, we must check the precision of measurements. The objective of this work is to compare several methods for calculating the precision of three kinds of micropipettes according to the reference value in ISO 8655-6. The medical tests will not have accurate results, if the volume of the liquid doesn’t transfer precisely by micropipettes. Thus, the physician might potentially face problems in the disease diagnosis and its control. In the NCCLS EP5-A2, there is a method to specify and assess the precision of micropipettes by using CV (Coefficient of Variation). Also there are other methods to estimate and test the CV theory, in the formal statistics texts which could be applied to assess the micropipettes precision. In this research we evaluate the precision of lab micropipettes. Three brands of micropipettes, A, B and C are assigned to measure the distilled water mass by using accurate scale which is accurate up to 10-6 to measure 50-gram weights. The experimental environment is a metrology lab which is approved by Iran Standard and Industrial Researches Organization. A technician sampled at the beginning of the experiment and then after 2 hours, the same technician repeated the sampling. Overall, each micropipette is used to measure 40 times with 10-repeat times for single measurement in 28 work days. Common statistical methods are used to estimate and test the CV. Point estimation of CV for micropipettes A, B and C were 0.50%, 0.64% and 1.56%, respectively. Furthermore, the upper limit of 95% confidence bounds for these three micropipettes using the exact method were 0.53%, 0.69% and 1.65%, respectively. Micropipette A met the ISO 8655-6 standard level, but micropipettes B and C did not. On average, measurement errors in micropipettes B and C were respectively 30% and 3.11 times more than micropipette A. By using the approach of CLS EP5-A2 and confidence interval for CV, precision of the three micropipettes were compared. Only one of them met the ISO 8655-6 standard level, but the others failed

Using partitioning and non-partitioning clustering algorithms for included proteins sequences in esophagus, stomach and colon cancer

A thorough recognition of the nature and duties of the genes is based upon having adequate information about the proteins. However, the proteomic projects follow a slow trend; therefore, solving the protein-related problems has become as one of the most important challenges in bio-informatics. Consequently, the presence of tools which can enhance the structural recognition, classification, and interpretation of proteins will be advantageous. Statistical methods are among the tools to help solve bio-informatics problems. These methods may be used to help predict the third structures of proteins, study proteins collectively, as well as extract new interactions among the protein collections. One of the very efficient and useful methods in the collective study of protein subsets is the cluster analysis. In the present study, the recognized protein sequences related to esophagus, stomach, and colon cancers are analyzed through partitioning, non-partitioning, and fuzzy clustering methods. Needleman-Wunsch global alignment algorithm was used to determine pair-wise similarities. The evaluations have shown that the clusters obtained through using the AGNES method have produced more powerful structures; yet, it can be said that the PAM clustering method, compared to other ones, has produced the best results in predicting ability of the 3D structure of the unknown protein sequences

Prediction of the Thromboembolic Syndrome: an Application of Artificial Neural Networks in Gene Expression Data Analysis

The aim of this study was to propose a method for improving the power of recognition and classification of thromboembolic syndrome based on the analysis of ‎ gene expression data using artificial neural networks. The studied method was performed on a dataset which contained data about 117 patients admitted to a hospital in Durham in 2009. Of all the studied patients, 66 patients were suffering from thromboembolic syndrome and 51 people were enrolled in the study as the control group. The gene expression level of 22277 was measured for all the samples and was entered into the model as the main variable. Due to the high number of variables, principal components analysis and auto-encoder neural network methods were used in order to reduce the dimension of data. The results showed that when using auto-encoder networks, the classification accuracy was 93.12. When using the PCA method to reduce the size of the data, the obtained accuracy was 78.26, and hence a significant difference in the accuracy of classification was observed. If auto-encoder network method is used, the sensitivity and specificity will be 92.58 and 93.68 and when PCA method is used, they will be 0.77 and 0.78 respectively. The results suggested that auto-encoder networks, compared with the PCA method, had a higher level of accuracy for the classification of thromboembolic syndrome status

Poziom hemoglobiny w pierwszym trymestrze u ciężarnej z cukrzycą ciążową

Objective: The objective of this study was to determine the relationship between the hemoglobin levels during the first trimester of pregnancy with gestational diabetes incidence in pregnant women. Materials and methods: This is a prospective cohort study on 700 pregnant women with gestational ages of 1-13 weeks. Sampling was performed using the convenience method. For each pregnant woman, the hemoglobin level of the first trimester of pregnancy was measured. All the cases were followed up to delivery due to gestational diabetes. Results: Hemoglobin levels were categorized into three groups (Cel pracy: Celem pracy była ocena związku pomiędzy poziomem hemoglobiny w pierwszym trymestrze u ciężarnej z cukrzycą ciążową. Materiał i metoda: Prospektywne kohortowe badanie przeprowadzono na 700 kobietach w 1-13 tygodniu ciąży. U każdej kobiety badano poziom hemoglobiny w pierwszym trymestrze ciąży. Wszystkie przypadki kontrolowano aż do porodu ze względu na cukrzycę. Wyniki: Wyznaczono trzy grupy w zależności od poziomu hemoglobiny

The effect of illness perception on physical health-related quality of life promotion in multiple sclerosis (MS) patients attending peer support groups

Illness perception influences patients’ decision to adopt effective behavior and achieve positive results such as adapting with the disease and improving functionality, and the interventions that increase illness perception can promote health. This study aimed to investigate the effect of illness perception on the physical health-related quality of life of MS patients attending peer support groups. This study with a quasi-experimental before-and-after design included 33 MS patients in three groups: male-only(n=10), female-only(n=11) and one with both males and females (mixed, n=12) that selected by convenience sampling Participants were required to attend 8 weekly sessions comprising 2 hours each. Instruments used to assess physical health related quality of life and illness perception were the physical health section of "Multiple Sclerosis Quality of Life Inventory (MSQLI)" and "Revised Illness Perception Questionnaire(IPQ-R)" respectively, which were completed by participants before and after attending the group sessions. The results showed that although illness perception of MS patients attending peer support groups did not show a significant increase, physical health significantly improved(p=0.001). Attending peer support group increased illness perception in the mixed group(p=0.01) and elevated physical health in men only and mixed group (p=0.03 for the mixed group and p=0.04 for men only group). Regression analysis showed a significant relationship between MS and physical health with efficacy of 0.54(p<0.001). The results showed that increased illness perception in MS patients improves their physical health. Therefore, we can improve MS patients’ physical health-related quality of life through peer support groups and hence promote patients’ quality of life.

Structure of Resilience in Older Adults with Chronic Conditions

Introduction: Promoting resilience in older adults with chronic conditions is one of the goals of professional nursing. However, few studies have been conducted in world on this issue. In our country, Iran, no study, either qualitative or quantitative, has been done in this area .The aim of this study was to explore the structure of resilience in older adults with chronic conditions. Method: In this study with descriptive phenomenological approach, participants were selected using purposive sampling method. Overall, 24 interview sessions were held with 22 participants. The minimum duration of an interview was 25 and the maximum was 75 minutes. The data were collected through semi-structured interviews and analyzed using the Colaizzi`s proposed stages. Results: Four themes were emerged that could illustrate the perspective of older adults with chronic conditions from the external structure of resilience in particular socio-cultural context of Iranian society. The themes were supportive resources, welfare status, cut-of benefit, and attitude to the elderly patient. Conclusion: Results of this study revealed important concepts in the structure of resilience in older adult patients with chronic diseases. Our fidings can help health care providers to understand the effective resources on the resilience and comprehensive care planning to grow and increase the resilience among older adults. Keywords: Resilience, Older adults, Phenomenolog