Calculation of sample size when planning a clinical study of the Bovhyaluronidaze azoximer preparation in companion animals urological practice

2020 ◽  
Vol 1 ◽  
pp. 140-144
Author(s):  
A.V. Nazarova ◽  
Keyword(s):  
Veterinary Medicine ◽  
Clinical Study ◽  
Sample Size ◽  
Evidence Based Medicine ◽  
Statistical Significance ◽  
Companion Animals ◽  
Control Group ◽  
Evidence Based ◽  
Level Of Evidence ◽  
Based Medicine

Nowadays both international and Russian medical sciences are actively working to improve the methods of evidence and the formation of standards of research and treat-ment. The necessity to develop common criteria for evaluating the effectiveness of methods of diagnosis, treatment and prevention of diseases exists in veterinary medicine. To achieve this goal, both general veterinary medicine and scientific research in the field of veterinary medicine, must reach the level of evidence that answers the requirements of Evidence Based Medicine. In accordance with the current require-ments of Evidence Based Medicine and Good Clinical Practice, at the stage of plan-ning a clinical study of the use of Bovhyalu-ronidaze azoximer preparations in the com-panion animals urological treatment, we have calculated the required sample size. In the calculation, we used the results of a pilot study, in which the incidence of post-operative complications in the experimental group was 0.10, in the control group — 0.55. We calculated that for statistical significance testing with significance level α = 0.05 and power β = 0.80 in a clinical trial of the use of bovhyaluronidaze azoximer prepara-tion in the urological practice of companion animals, the sample size should be at least 22 animals in each group (taking into ac-count the possible retirement of patients from the clinical study). And the groups must be equal in volume to achieve the max-imum test power.

Evidence-based medicine in otolaryngology journals

2002 ◽  
Vol 126 (4) ◽  
pp. 371-376 ◽  
Author(s):  
Boris L. Bentsianov ◽  
Marina Boruk ◽  
Richard M. Rosenfeld
Keyword(s):  
Clinical Research ◽  
Internal Control ◽  
Evidence Based Medicine ◽  
Research Articles ◽  
Control Group ◽  
Evidence Based ◽  
Supporting Evidence ◽  
Level Of Evidence ◽  
Therapeutic Recommendations ◽  
Based Medicine

OBJECTIVE: We set out to assess, within the context of evidence-based medicine, the levels of supporting evidence for therapeutic recommendations made in leading otolaryngology journals. DESIGN: We used a cross-sectional survey of clinical research articles published in 1999 in 4 high-circulation otolaryngology journals. OUTCOME MEASURES: We used study design methodology and level of evidence for clinical research articles with therapeutic recommendations. Outcomes were stratified by type of recommendation (positive vs negative) and by study focus (medical vs surgical therapy). RESULTS: Of the 1019 articles identified, 737 (72%) were clinical research and 268 (36%) made therapeutic recommendations. Median sample size was modest (27 subjects), with only 38% of studies reflecting planned research and 22% including an internal control or comparison group. positive studies were 20 times more prevalent than negative ones, but were 69% less likely to have an internal control group ( P = .042) and 93% less likely to include confidence intervals ( P = .020). Moreover, the level of evidence for positive studies was lower than for negative studies ( P = .037), with twice as many negative recommendations supported by analytic research. Similarly, the level of evidence for operation was lower than for medical therapy ( P < .001), with 3 times as many medical recommendations supported by analytic research. CONCLUSIONS: Most therapeutic recommendations in otolaryngology journals are on the basis of descriptive case series (80%) and least often on randomized controlled trials (7%). A dual standard appears to exist for negative versus positive studies and for medical versus surgical recommendations. Greater scrutiny of the breadth and quality of evidence levels supporting therapeutic recommendations is likely to occur as the popularity of—and demand for—evidence-based medicine increases. SIGNIFICANCE: Evaluation of levels of evidence in otolaryngology decision making.

scholarly journals Guiding Nipple-Areola Complex Reconstruction: Literature Review and Proposal of a New Decision-Making Algorithm

2020 ◽  
Author(s):  
Guido Paolini ◽  
Guido Firmani ◽  
Francesca Briganti ◽  
Michail Sorotos ◽  
Fabio Santanelli di Pompeo
Keyword(s):  
Decision Making ◽  
Patient Satisfaction ◽  
Patient Selection ◽  
Evidence Based Medicine ◽  
Evidence Based ◽  
Patient Factors ◽  
Level Of Evidence ◽  
Areola Complex ◽  
Complex Reconstruction ◽  
Based Medicine

Abstract Background Nipple-areola complex reconstruction (NAR) most commonly represents the finishing touch to breast reconstruction (BR). Nipple presence is particularly relevant to the patient’s psyche, beyond any shadow of doubt. Many reconstructive options have been described in time. Surgery is easy, but final result is often disappointing on the long run. Methods The goal of this manuscript is to analyze and classify knowledge concerning NAR techniques and the factors that influence success, and then to elaborate a practical evidence-based algorithm. Out of the 3136 available articles as of August 8th, 2020, we selected 172 manuscripts that met inclusion criteria, which we subdivided into 5 main topics of discussion, being the various NAR techniques; patient factors (including patient selection, timing and ideal position); dressings; potential complications and finally, outcomes/patient satisfaction. Results We found 92 articles describing NAR techniques, 41 addressing patient factors (out of which 17 discussed patient selection, 14 described ideal NAC location, 10 described appropriate timing), 10 comparing dressings, 7 studying NAR complications, and 22 addressing outcomes and patient satisfaction. We elaborated a comprehensive decision-making algorithm to help narrow down the choice among NAR techniques, and choose the correct strategy according to the various scenarios, and particularly the BR technique and skin envelope. Conclusions No single NAR technique provides definitive results, which is why we believe there is no “end-all be-all solution”. NAR must be approached as a case-by-case situation. Furthermore, despite NAR being such a widely discussed topic in scientific literature, we still found a lack of clinical trials to allow for more thorough recommendations to be elaborated. Level of Evidence III This journal requires that authors assign a level of evidence to each submission to which Evidence-Based Medicine rankings are applicable. This excludes Review Articles, Book Reviews, and manuscripts that concern Basic Science, Animal Studies, Cadaver Studies, and Experimental Studies. For a full description of these Evidence-Based Medicine ratings, please refer to the Table of Contents or the online Instructions to Authors www.springer.com/00266

scholarly journals Efficacy of a complex intervention comprising the guideline evidence-based health information and a training programme on the quality of health information: study protocol of a randomised controlled trial

2020 ◽  
Author(s):  
Julia Lühnen ◽  
Birte Berger-Höger ◽  
Burkhard Haastert ◽  
Jana Hinneburg ◽  
Jürgen Kasper ◽  
...  
Keyword(s):  
Health Information ◽  
Evidence Based Medicine ◽  
Information Quality ◽  
Controlled Trial ◽  
Training Programme ◽  
Control Group ◽  
Evidence Based ◽  
Study Results ◽  
Based Medicine

Abstract Background Evidence-based health information (EBHI) is a prerequisite for informed and shared decision-making. The criteria for EBHI have been described comprehensively but the implementation in practice is still insufficient. The guideline evidence-based health information addresses providers of health information. Its goal is to improve the quality of health information. The evidence-based guideline emerged from the German Network for Evidence-based Medicine (DNEbM) and was published in February 2017. In addition, the competences of providers of health information were explored and a training programme was developed. Aim of this study is to evaluate the efficacy of a training programme addressing providers of health information to support the application of the guideline evidence-based health information. We expect the intervention to improve the quality of health information in comparison to provision of the guideline only. Methods The trial uses a superiority randomised control group design with ten months follow-up. 26 providers of health information (groups with up to ten members) will be enrolled to compare the intervention (guideline & training programme) with usual care (guideline publicly available). The 5-day training programme comprises an evidence-based medicine training module and a module to prepare the application of the guideline. The primary outcome parameter is the quality of the health information. Quality is operationalised as the extent of adherence to the guideline’s recommendations. Each provider will prepare a single health information informing a health-related decision on a freely chosen topic. The quality of this information will be rated using the Mapping Health Information Quality (MAPPinfo) checklist. An accompanying process evaluation will then be conducted. Discussion The study results will show whether the efficacy of the intervention justifies implementation of the training programme to enhance health information developers’ competences in evidence-based medicine and to ensure high quality EBHI in the long-term. Trial registration ISRCTN registry, registration number: ISRCTN96941060, Date: 7 March 2019, URL: http://www.isrctn.com/ISRCTN96941060

scholarly journals A Study on How Using an Interactive Multimedia E-Book Improves Teachers’ Ability to Teach Evidence-Based Medicine, Depending on Their Seniority

2021 ◽  
Author(s):  
Yu-Hsuan Liao ◽  
Kuo-Shu Tang ◽  
Chih-Jen Chen ◽  
Ying-Hsien Huang ◽  
Mao-Meng Tiao
Keyword(s):  
Evidence Based Medicine ◽  
Clinical Teaching ◽  
Teaching Method ◽  
Control Group ◽  
Study Group ◽  
Evidence Based ◽  
Fresno Test ◽  
Before And After ◽  
Study Type ◽  
Based Medicine

Abstract Background Teaching evidence-based medicine (EBM) is not an easy task. The role of the electronic book (e-book) is a useful supplement to traditional methods for improving skills. Our aim is to use an e-book or PowerPoint to evaluate instructors’ teaching effects. Methods Our study group was introduced to learning evidence-based medicine (EBM) using an interactive e-book available on the Internet, while the control group used a PowerPoint presentation. We adopted the Modified Fresno test to assess EBM skills before and after their learning. EBM teaching sessions via e-book or PowerPoint were 20–30 minutes long, followed by students’ feedback. We adopted the Mann-Whitney U tests to compare teachers’ evaluation of their EBM skills and the students’ assessment of the teachers’ instruction. Results We found no difference of EBM skills between the two groups prior to their experimental learning. Physicians in the study group ranked higher in “Choose a case to explain which kind of research design is used for the study type of the question and explain your choice” (P = 0.011) and “How are the important results expressed in the articles found” (P = 0.023), which was assessed by the Modified Fresno test. Teaching effect was better in the e-book group than in the control group for the items, “I am satisfied with this lesson,” “The teaching was of high quality,” “This was a good teaching method,” and “It aroused my interest in EBM.” No difference was observed between the two groups in the physicians with more than 10 years’ experience. Conclusions The use of interactive e-books in clinical teaching can enhance teachers’ EBM skills and teaching and is thus clinically useful.

Evidence-based medicine

2017 ◽  
Author(s):  
Philip Wiffen ◽  
Marc Mitchell ◽  
Melanie Snelling ◽  
Nicola Stoner
Keyword(s):  
Evidence Based Medicine ◽  
Binary Data ◽  
Statistical Significance ◽  
Number Needed To Treat ◽  
Evidence Based ◽  
High Quality ◽  
Relative Risks ◽  
High Quality Evidence ◽  
Based Medicine ◽  
Quality Evidence

This chapter provides a brief overview to the concept of evidence-based medicine (EBM) starting with a well-accepted definition. The importance of clinical significance over statistical significance is discussed. A number of useful tools are presented and described to enable the practitioner to become competent in recognizing high-quality evidence and to have the skills to critically appraise evidence that is potentially important to their practice. There is a brief description of some of the statistical tools commonly used in EBM including binary data tools such as odds ratios, number needed to treat, and relative risks.

Epidemiology and evidence-based medicine

2016 ◽  
Keyword(s):  
Survival Analysis ◽  
Relative Risk ◽  
Sample Size ◽  
Evidence Based Medicine ◽  
Diagnostic Tests ◽  
Meta Analysis ◽  
Descriptive Statistics ◽  
Number Needed To Treat ◽  
Evidence Based ◽  
Based Medicine

Chapter 20 focuses on epidemiology and evidence-based medicine. It covers study design, types of data and descriptive statistics, from samples to populations, relationships, relative risk, odds ratios, and 'number needed to treat', survival analysis, sample size, diagnostic tests, meta-analysis, before concluding with advice on how to read a paper.

scholarly journals Relationship between Journal Impact Factor and Levels of Evidence in Anaesthesia

2005 ◽  
Vol 33 (5) ◽  
pp. 567-570 ◽  
Author(s):  
C. R. Bain ◽  
P. S. Myles
Keyword(s):  
Impact Factor ◽  
Evidence Based Medicine ◽  
Citation Rate ◽  
Journal Ranking ◽  
Evidence Based ◽  
Publication Type ◽  
Level Of Evidence ◽  
Level 1 ◽  
Number Of Publications ◽  
Based Medicine

Evidence-based medicine uses a hierarchy of publication types according to their vulnerability to bias. A widely used measure of journal “quality” is its impact factor, which describes the citation rate of its publications. We investigated the relationship between impact factor for eight anaesthesia journals and publication type with respect to their level of evidence 1-4 using Spearman rank correlation (rho). There were 1418 original publications during 2001 included in the analysis. The number (%) of publication types according to evidence-based medicine level were: level 1: 6 (0.4%), level 2: 533 (38%) level 3: 329 (23%), level 4: 550 (39%). There was no correlation between journal ranking according to impact factor and publication type (rho=–0.03, P=0.25). The correlation between journal rank and the proportion of publications that were randomized trials was –0.35 (P<0.001). The correlation between journal rank and number of publications was 0.65 (P<0.001). The correlation between journal rank and number of level 1 or 2 studies was 0.58 (P<0.001). The overall level of evidence published in anaesthesia journals was high. Journal rank according to impact factor is related to the number of publications, but not the proportion of publications that are evidence-based medicine level 1 or 2.

Practicing Evidence-Based Medicine

2015 ◽  
Author(s):  
Michael Barnett ◽  
Niteesh Choudhry
Keyword(s):  
Evidence Based Medicine ◽  
Test Performance ◽  
Statistical Significance ◽  
Clinical Decision ◽  
Medical Decision ◽  
Number Needed To Treat ◽  
Evidence Based ◽  
Symptomatic Carotid ◽  
The North ◽  
Based Medicine

Today, a plethora of resources for evidence-based medicine (EBM) are available via alert services, compendia, and more. In theory, a clinician researching a topic or looking for information regarding a clinical decision should easily find the literature or synopses needed. However, the real challenge lies in recognizing which resources (out of hundreds or possibly thousands) present the best and most reliable evidence. As well, evidence from research is only part of the decision calculus, and the clinician, not the evidence, makes the final decisions. Medical decision analysis attempts to formalize the process and reduce it to algebra, but it is difficult or impossible to represent all the components of a decision mathematically and validly let alone do so in “real time” for individual patients. This review discusses these challenges and more, including how to ask answerable questions, understand the hierarchy for evidence-based information resources, critically appraise evidence, and apply research results to patient care. Figures show the total number of new articles in Medline from 1965 to 2012, a “4S” hierarchy of preappraised medicine, percentage of physician and medical student respondents with a correct or incorrect answer to a question about calculating the positive predictive value of a hypothetical screening test, a nomogram for Bayes’s rule, an example of nomogram use for pulmonary embolism, and a model for evidence-informed clinical decisions. Tables list selected barriers to the implementation of EBM; Patient, Intervention, Comparison, and Outcome (PICO) framework for formulating clinical questions; guides for assessing medical texts for evidence-based features; clinically useful measures of disease frequency and statistical significance and precision; definitions of clinically useful measures of diagnostic test performance and interpretation; definitions of clinically useful measures of treatment effects from clinical trials; summary of results and derived calculations from the North American Symptomatic Carotid Endarterectomy Trial (NASCET); and selected number needed to treat values for common therapies. This review contains 6 highly rendered figures, 9 tables, and 28 references.

Practicing Evidence-Based Medicine (SAGHE)

2015 ◽  
Author(s):  
Michael Barnett ◽  
Niteesh Choudhry
Keyword(s):  
Evidence Based Medicine ◽  
Test Performance ◽  
Statistical Significance ◽  
Clinical Decision ◽  
Medical Decision ◽  
Number Needed To Treat ◽  
Evidence Based ◽  
Symptomatic Carotid ◽  
The North ◽  
Based Medicine

Today, a plethora of resources for evidence-based medicine (EBM) are available via alert services, compendia, and more. In theory, a clinician researching a topic or looking for information regarding a clinical decision should easily find the literature or synopses needed. However, the real challenge lies in recognizing which resources (out of hundreds or possibly thousands) present the best and most reliable evidence. As well, evidence from research is only part of the decision calculus, and the clinician, not the evidence, makes the final decisions. Medical decision analysis attempts to formalize the process and reduce it to algebra, but it is difficult or impossible to represent all the components of a decision mathematically and validly let alone do so in “real time” for individual patients. This review discusses these challenges and more, including how to ask answerable questions, understand the hierarchy for evidence-based information resources, critically appraise evidence, and apply research results to patient care. Figures show the total number of new articles in Medline from 1965 to 2012, a “4S” hierarchy of preappraised medicine, percentage of physician and medical student respondents with a correct or incorrect answer to a question about calculating the positive predictive value of a hypothetical screening test, a nomogram for Bayes’s rule, an example of nomogram use for pulmonary embolism, and a model for evidence-informed clinical decisions. Tables list selected barriers to the implementation of EBM; Patient, Intervention, Comparison, and Outcome (PICO) framework for formulating clinical questions; guides for assessing medical texts for evidence-based features; clinically useful measures of disease frequency and statistical significance and precision; definitions of clinically useful measures of diagnostic test performance and interpretation; definitions of clinically useful measures of treatment effects from clinical trials; summary of results and derived calculations from the North American Symptomatic Carotid Endarterectomy Trial (NASCET); and selected number needed to treat values for common therapies. This review contains 6 highly rendered figures, 9 tables, and 28 references.

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