Basics of biomedical research and ethics

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Basics of biomedical research and ethics:

Basics of biomedical research and ethics Time 1:3 Eman youssif

srael’s economy has escaped relatively unscathed from the global economic recession. Gross domestic expenditure on research and development[1] (GERD) fell by just 0.4 percentage points to 4.4% of GDP between 2008 and 2010, maintaining Israel’s global lead for the level of commitment to R&D. Most exposed to the financial turbulence has been the business sector (80% of all R&D[2]), owing to its dependence on world markets for its high-tech exports and venture capital. One development that should have strong repercussions for the country’s economy is Israel’s integration into the Organisation for Economic Co-operation and Development in 2010.:

srael’s economy has escaped relatively unscathed from the global economic recession. Gross domestic expenditure on research and development[1] (GERD) fell by just 0.4 percentage points to 4.4% of GDP between 2008 and 2010, maintaining Israel’s global lead for the level of commitment to R&D. Most exposed to the financial turbulence has been the business sector (80% of all R&D[2]), owing to its dependence on world markets for its high-tech exports and venture capital. One development that should have strong repercussions for the country’s economy is Israel’s integration into the Organisation for Economic Co-operation and Development in 2010.

Case report1-:

Case report1- Successful treatment for adrenocorticotropic hormone-independent macronodular adrenal hyperplasia with laparoscopic adrenalectomy : a case series We performed successful laparoscopic adrenalectomy on four patients with adrenocorticotropic hormone-independent macronodular adrenal hyperplasia. Computed tomography scans showed bilateral adrenal enlargement in all patients. Case 1: a 56-year-old Japanese woman presented with obvious Cushing's symptoms during treatment for diabetes mellitus and hypertension. Case 2: a 37-year-old Japanese man also presented with Cushing's symptoms during treatment for diabetes mellitus and hypertension. These patients were diagnosed as Cushing's syndrome caused by adrenocorticotropic hormone-independent macronodular adrenal hyperplasia based on endocrinologic testing, and underwent bilateral laparoscopic adrenalectomy . Case 3: an 80-year-old Japanese woman was hospitalized due to unusual weight gain and heightened general fatigue, and was diagnosed as Cushing's syndrome caused by adrenocorticotropic hormone-independent macronodular adrenal hyperplasia. She underwent unilateral laparoscopic adrenalectomy due to high operative risk. Case 4: a 66-year-old Japanese man was discovered to have bilateral adrenal tumors on medical examination. He did not have Cushing's symptoms and was diagnosed as subclinical Cushing's syndrome due to suppressed adrenocorticotropic hormone serum levels and loss of cortisol circadian rhythm without abnormal levels of serum cortisol. He underwent unilateral laparoscopic adrenalectomy . During follow-up, serum cortisol levels were within the normal range in all cases, and serum adrenocorticotropic hormone levels were not suppressed. Further, cases with Cushing's syndrome experienced clinical improvemen t.

2-case series report:

2-case series report A case series (also known as a clinical series) is a medical research descriptive study that tracks patients with a known exposure given similar treatment[1] or examines their medical records for exposure and outcome. It can be retrospective or prospective and usually involves a smaller number of patients than more powerful case-control studies or randomized controlled trials. Case series may be consecutive[2] or non-consecutive,[3] depending on whether all cases presenting to the reporting authors over a period were included, or only a selection. Case series may be confounded by selection bias, which limits statements on the causality of correlations observed; for example, physicians who look at patients with a certain illness and a suspected linked exposure will have a selection bias in that they have drawn their patients from a narrow selection (namely their hospital or clinic).

Correlational study:

Correlational study In statistics, dependence refers to any statistical relationship between two random variables or two sets of data. Correlation refers to any of a broad class of statistical relationships involving dependence . Familiar examples of dependent phenomena include the correlation between the physical statures of parents and their offspring, and the correlation between the demand for a product and its price. Correlations are useful because they can indicate a predictive relationship that can be exploited in practice. For example, an electrical utility may produce less power on a mild day based on the correlation between electricity demand and weather. In this example there is a causal relationship, because extreme weather causes people to use more electricity for heating or cooling; however, statistical dependence is not sufficient to demonstrate the presence of such a causal relationship. Formally, dependence refers to any situation in which random variables do not satisfy a mathematical condition of probabilistic independence . In loose usage, correlation can refer to any departure of two or more random variables from independence, but technically it refers to any of several more specialized types of relationship between mean values. There are several correlation coefficients, often denoted ρ or r, measuring the degree of correlation. The most common of these is the Pearson correlation coefficient, which is sensitive only to a linear relationship between two variables (which may exist even if one is a nonlinear function of the other). Other correlation coefficients have been developed to be more robust than the Pearson correlation – that is, more sensitive to nonlinear relationships

An ecological study :

An ecological study is an epidemiological study in which the unit of analysis is a population rather than an individual. For instance, an ecological study may look at the association between smoking and lung cancer deaths in different countries. An ecological study is normally regarded as inferior to non-ecological designs such as cohort and case-control studies because it is susceptible to the ecological fallacy. An example of an ecological study is the analysis of the effects of disinfection byproducts on newborn babies, using 109 Massachusetts towns as units of analysis (Wright et al. 2004). (For an environmental definition of this term see Ecology.) Ecological studies can be easily confused with cohort studies, especially if different cohorts are located in different places. The difference is that in the case of ecological studies there is no information available about the individual members of the populations compared (e.g. comparing several states based on state-wide average air pollution and state-wide average prevalence of respiratory diseases); whereas in a cohort study the data pair exposure/health is known for each individual.

Quantitative data is any data that is in numerical form such as statistics, percentages, etc.[1] In layman's terms, this means that the quantitative researcher asks a specific, narrow question and collects numerical data from participants to answer the question. The researcher analyzes the data with the help of statistics.:

Quantitative data is any data that is in numerical form such as statistics, percentages, etc.[1] In layman's terms, this means that the quantitative researcher asks a specific, narrow question and collects numerical data from participants to answer the question. The researcher analyzes the data with the help of statistics.

Analytical chemistry is the study of the separation, identification, and quantification of the chemical components of natural and artificial materials.[1] Qualitative analysis gives an indication of the identity of the chemical species in the sample:

Analytical chemistry is the study of the separation, identification, and quantification of the chemical components of natural and artificial materials.[1] Qualitative analysis gives an indication of the identity of the chemical species in the sample

Statistics is the study of the collection, organization, analysis, interpretation, and presentation of data.[1][2] It deals with all aspects of this, including the planning of data collection in terms of the design of surveys and experiments.[1] A statistician is someone who is particularly well versed in the ways of thinking necessary for the successful application of statistical analysis. Such people have often gained this experience through working in any of a wide number of fields. There is also a discipline called mathematical statistics that studies statistics mathematically. The word statistics, when referring to the scientific discipline, is singular, as in "Statistics is an art."[3] This should not be confused with the word statistic, referring to a quantity:

Statistics is the study of the collection, organization, analysis, interpretation, and presentation of data.[1][2] It deals with all aspects of this, including the planning of data collection in terms of the design of surveys and experiments.[1] A statistician is someone who is particularly well versed in the ways of thinking necessary for the successful application of statistical analysis. Such people have often gained this experience through working in any of a wide number of fields. There is also a discipline called mathematical statistics that studies statistics mathematically. The word statistics, when referring to the scientific discipline, is singular, as in "Statistics is an art."[3] This should not be confused with the word statistic, referring to a quantity

Correlation and linearity:

Correlation and linearity

Statistical methods:

Statistical methods

Experiments The basic steps of a statistical experiment are: Planning the research, including finding the number of replicates of the study, using the following information: preliminary estimates regarding the size of treatment effects, alternative hypotheses, and the estimated experimental variability. Consideration of the selection of experimental subjects and the ethics of research is necessary. Statisticians recommend that experiments compare (at least) one new treatment with a standard treatment or control, to allow an unbiased estimate of the difference in treatment effects. Design of experiments, using blocking to reduce the influence of confounding variables, and randomized assignment of treatments to subjects to allow unbiased estimates of treatment effects and experimental error. At this stage, the experimenters and statisticians write the experimental protocol that shall guide the performance of the experiment and that specifies the primary analysis of the experimental data. Performing the experiment following the experimental protocol and analyzing the data following the experimental protocol. Further examining the data set in secondary analyses, to suggest new hypotheses for future study. Documenting and presenting the results of the study. Experiments on human behavior have special concerns. The famous Hawthorne study examined changes to the working environment at the Hawthorne plant of the Western Electric Company:

Experiments The basic steps of a statistical experiment are: Planning the research, including finding the number of replicates of the study, using the following information: preliminary estimates regarding the size of treatment effects, alternative hypotheses, and the estimated experimental variability. Consideration of the selection of experimental subjects and the ethics of research is necessary. Statisticians recommend that experiments compare (at least) one new treatment with a standard treatment or control, to allow an unbiased estimate of the difference in treatment effects . Design of experiments, using blocking to reduce the influence of confounding variables, and randomized assignment of treatments to subjects to allow unbiased estimates of treatment effects and experimental error. At this stage, the experimenters and statisticians write the experimental protocol that shall guide the performance of the experiment and that specifies the primary analysis of the experimental data. Performing the experiment following the experimental protocol and analyzing the data following the experimental protocol. Further examining the data set in secondary analyses, to suggest new hypotheses for future study. Documenting and presenting the results of the study. Experiments on human behavior have special concerns. The famous Hawthorne study examined changes to the working environment at the Hawthorne plant of the Western Electric Company

Thanks eman copied:

Thanks eman copied

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