Measurement of Neck-Shaft Angle Using CT Scout View in Healthy Jordanian Adults - A Reliability and Agreement Study

Aims:To report estimates of the reliability and agreement of a new method for measuring the femoral Neck-shaft angle in the Jordanian population. The neck-shaft angle is an important anatomical indicator in orthopedics of the hip. While there are different approaches to measuring the neck-shaft angle in the literature, there is no agreement on the best technique used for measurement. CT scout view was used in this study to provide a promising alternative. Study Design: Observational reliability and agreement study.Places and Duration of the Study:Department of physiotherapy, school of rehabilitation science, University of Jordan and University of Jordan Hospital between March 2014 and October 2015. Methodology:Two independent raters calculated the neck-shaftangle on each hip of 50 pelvic CT scout images of healthy adults to determine inter-rater reliability. One rater performed the measurement twice to determine the intra-rater reliability. Intra-class correlation coefficients were used to examine relative reliability. The standard error of measurement (SEM) and 95% minimal detectable change (MDC) were calculated to examine absolute reliability. Results:The mean value of all angle measurements was 131.3. Intra-class correlation coefficients were 0.726 and 0.63 for inter and intra-rater measurements respectively. SEM and MDC for inter-rater measurements were 2.69 and 7.46 respectively. For intra-rater measurements, they were 2.84 and 7.86 respectively. Conclusion: The new method proposed in this study for measuring the neck-shaft angle showed good reliability and small measurement error.

New insights for statistical analysis of blood pressure response to resistance training in elderly hypertensive women / Novas perpectivas para a análise estatística da resposta da pressão arterial ao treinamento resistido em mulheres idosas hipertensas

ABSTRACT The main goal was to present statistical procedures for a better data interpretation of responsiveness, explain how to deal with RTM effect, and describe how to determine clinically important changes in BP from significant real difference (SRD). Twenty-seven hypertensive elderly women were included, and RT consisted of a periodized linear model. The RT lasted 10 weeks, with two sessions performed per week. Responders were classified on the basis of SBP differences between time-points T1 (first 3 weeks) and T4 (weeks 9-10). Statistical analyses were performed using One-Way Repeated Measures ANOVA, an analysis of covariance (ANCOVA), the linear mixed model (LMM) was used in the present study, and SRD was also calculated. In conclusion, when one-way repeated measure ANOVA was conducted to determine whether there was a statistically significant difference in SBP levels over the course of 10-week RT, results showed a non-significant reduction of -2.24 mmHg, while classifying subjects by responsiveness provides a different perspective of the results. Furthermore, initial SBP was the more powerful predictor of post-exercise SBP response, as analyzed by the regression to the mean effect. Finally, the reductions of -2.24 mmHg was not statistically significant nor clinically meaningful, but fell within the measurement error of the SBP measurements.

RESUMO O objetivo principal do estudo foi apresentar procedimentos estatísticos para uma melhor interpretação dos dados sobre a responsividade, explicar como lidar com o efeito da regressão a média (RM) e descrever como determinar alterações clinicamente importantes na pressão arterial (PA) pelo cálculo da diferença clínica (DC). Vinte e sete mulheres idosas hipertensas foram incluídas e o treinamento resistido (TR) consistiu em um modelo linear periodizado. O TR durou 10 semanas, com duas sessões realizadas por semana. Os responsivos foram classificados com base nas diferenças da pressão arterial sistólica (PAS) entre os momentos T1 (primeiras 3 semanas) e T4 (semanas 9-10). As análises estatísticas no presente estudo foram realizadas utilizando a ANOVA de medidas repetidas, análise de covariância (ANCOVA) e modelo linear misto (MLM). Conclui-se que quando uma ANOVA de medidas repetidas é aplicada, os resultados mostram uma redução não significativa de -2,24 mmHg, mas a classificação dos participantes por responsividade fornece uma interpretação diferente dos resultados. Além disso, a PAS inicial foi o preditor mais potente da resposta pós-exercício da PAS, conforme analisado pela RM. Finalmente, as reduções de -2,24 mmHg não foram estatisticamente significativas e nem clinicamente importantes, mas caíram dentro do erro de medida.

Application of modified tracking components in CyberKnife treatment of thoracic and abdominal tumors / 肿瘤研究与临床

Objective@#To improve synchrony tracking components of CyberKnife (tracking vest and tracking markers) and to analyze the clinical application value of the improved tracking components in CyberKnife treatment of thoracic and abdominal tumors.@*Methods@#The tracking apron was made of knitted four-side elastic spandex cloth and suture design of Velcro, which was used to stick the tracking markers on the chest and abdomen of patients. The tracking markers added a 2 cm thick light foam block to the bottom of the original markers, and then the hook face of the Velcro was fixed to the bottom of the light foam. The improved trace component (the improved component) and the original component (the vendor component) were applied to the lung tracking treatment model, and the manufacturer components were included in the reference group. Adoption of improved components into the observation group; 20 different types of respiratory waveforms were simulated and applied to the same mold plan. After treatment, the coverage rate, mean standard deviation, maximum standard deviation and the slope of XYZ-axis vs. R correlation graph were recorded. The relevant parameters of Synchrony model and wearable time of two components were compared, and the application significances of the improved tracking component in the breathing tracking process of the CyberKnife were evaluated.@*Results@#The maximum slope [median(interquartile range)] of XYZ-axis vs. R related graph in the reference group was 0.73 (3.89), 0.27 (0.49) and 0.34 (1.02), respectively. The maximum slope of XYZ-axis vs. R related graph in the observation group was 0.70 (2.78), 0.31 (0.30) and 0.36 (0.75), respectively. There was no statistically significant difference in the slope of XYZ-axis vs. R between the reference group and the observation group (all P > 0.05). There was no significant difference in the average standard error and maximum standard error between the reference group and the observation group [(1.7±0.4) mm vs. (1.7±0.5) mm, t=-0.382, P= 0.710; (2.0±0.6) mm vs. (1.7±0.5) mm, t=-0.877, P= 0.401], and the difference of the model coverage rate between the two groups was statistically significant [(48±18)% vs. (60±22)%, t= 2.762, P= 0.042]. The setup time of tracking components in the observation group was less than that in the reference group, and the difference was statistically significant [(44±24) s vs. (81±15) s, t=-4.310, P= 0.001].@*Conclusions@#The improved tracking components are comparable to the manufacturer tracking components in the standard error of the Synchrony model. The improved components shorten the wear time and appropriately improve the coverage of the Synchrony model.

Estatística descritiva: perguntas que você sempre quis fazer, mas nunca teve coragem / Descriptive statistics: questions you have always wanted to ask, but never had the courage to

A revista do HCPA (Clinical & Biomedical Research) está reabrindo a seção de Bioestatística com o intuito de apresentar artigos explicativos, conceituais ou tutoriais, de modo a elucidar os leitores sobre os mais diversos temas estatísticos. Neste contexto, este artigo será o primeiro de uma série que tem como objetivo responder algumas das questões mais levantadas por pesquisadores da área da saúde. Começando pela Estatística Descritiva, alguns conceitos são esclarecidos e diversas referências são indicadas para o estudo do tema e para análises em SPSS ou R-project. (AU)

The HCPA journal (Clinical & Biomedical Research) is reopening its Biostatistics section with the aim of presenting readers with explanatory, conceptual or tutorial articles on a wide range of statistical topics. In this context, this is the first in a series of articles seeking to answer some of the questions raised by health researchers. Starting with descriptive statistics, some concepts are introduced and several references are indicated for those interested in studying the topic and performing analyses in SPSS or R-project. (AU)

Item Analysis, Reliability Statistics And Standard Error Of Measurement To Improve The Quality And Impact Of Multiple Choice Questions In Undergraduate Medical Education In Faculty Of Medicine At Unisza

Multiple-choice question as one best answer (OBA) is considered as a more effective tool to test higher order thinking for its reliability and validity compared to objective test (multiple true and false) items. However, to determine quality of OBA questions it needs item analysis for difficulty index (PI) and discrimination index (DI) as well as distractor efficiency (DE) with functional distractor (FD) and non-functional distractor (NFD). However, any flaw in item structuring should not be allowed to affect students’ performance due to the error of measurement. Standard error of measurement (SEM) to calculate a band of score can be utilized to reduce the impact of error in assessment. Present study evaluates the quality of 30 items OBA administered in professional II examination to apply the corrective measures and produce quality items for the question bank. The mean (SD) of 30 items OBA = 61.11 (7.495) and the reliability (internal consistency) as Cronbach’s alpha = 0.447. Out of 30 OBA items 11(36.66%) with PI = 0.31-0.60 and 12 items (40.00%) with DI = ≥0.19 were placed in category to retain item in question bank, 6 items (20.00%) in category to revise items with DI ≤0.19 and remaining 12 items (40.00%) in category to discard items for either with a poor or with negative DI. Out of a total 120 distractors, the non-functional distractors (NFD) were 63 (52.5%) and functional distracters were 57 (47.5%). 28 items (93.33%) were found to contain 1- 4 NFD and only 2 (6.66%) items were without any NFD. Distracter efficiency (DE) result of 28 items with NDF and only 2 items without NDF showed 7 items each with 1 NFD (75% DE) and 4 NFD (0% DE), 10 items with 2 NFD (50% DE) and 4 items with 3 NFD (25% DE). Standard error of measurement (SEM) calculated for OBA has been ± 5.51 and considering the borderline cut-off point set at ≥45%, a band score within 1 SD (68%) is generated for OBA. The high frequency of difficult or easy items and moderate to poor discrimination suggest the need of items corrective measure. Increased number of NFD and low DE in this study indicates difficulty of teaching faculty in developing plausible distractors for OBA question. Standard error of measurement (SEM) should be utilized to calculate a band of score to make logical decision on pass or fail of borderline students.

Standard deviation and standard error of the mean / 대한마취과학회지

In most clinical and experimental studies, the standard deviation (SD) and the estimated standard error of the mean (SEM) are used to present the characteristics of sample data and to explain statistical analysis results. However, some authors occasionally muddle the distinctive usage between the SD and SEM in medical literature. Because the process of calculating the SD and SEM includes different statistical inferences, each of them has its own meaning. SD is the dispersion of data in a normal distribution. In other words, SD indicates how accurately the mean represents sample data. However the meaning of SEM includes statistical inference based on the sampling distribution. SEM is the SD of the theoretical distribution of the sample means (the sampling distribution). While either SD or SEM can be applied to describe data and statistical results, one should be aware of reasonable methods with which to use SD and SEM. We aim to elucidate the distinctions between SD and SEM and to provide proper usage guidelines for both, which summarize data and describe statistical results.

Sample size: from formulae to concepts.

Sample size can be calculated from many online calculators or tables. But the use of these instruments is rational only when we understand our input data and the concept behind them completely. Terminologies like confidence interval, confidence limit, standard error of mean, margin of error, standard normal variate, power, significance level etc. and extent to which population size or chances of occurrence of an outcome can affect our sample size remain to be well understood before using these software solutions.

Standard Error of Empirical Bayes Estimate in NONMEM(R) VI

The pharmacokinetics/pharmacodynamics analysis software NONMEM(R) output provides model parameter estimates and associated standard errors. However, the standard error of empirical Bayes estimates of inter-subject variability is not available. A simple and direct method for estimating standard error of the empirical Bayes estimates of inter-subject variability using the NONMEM(R) VI internal matrix POSTV is developed and applied to several pharmacokinetic models using intensively or sparsely sampled data for demonstration and to evaluate performance. The computed standard error is in general similar to the results from other post-processing methods and the degree of difference, if any, depends on the employed estimation options.