Pitfalls in clinical research EFNS teaching course

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Pitfalls in clinical research EFNS teaching course by Mind Map: Pitfalls in clinical research EFNS teaching course

1. RCT presentation 1

1.1. Validity

1.1.1. external effects

1.1.2. Components observed effect

1.1.3. Learning from single observations or on basis of experience

1.1.4. regressionto the mean

1.1.5. Treatment effect

1.2. Miscellaneous

1.2.1. Phases of clinical trials picture

1.2.2. Subgroup analysis picture be careful usually too little patients to do subgroups

1.2.3. Factorial design picture reference dennis black

1.2.4. Cross over designs picture picture

1.2.5. Stopping rules picture

1.2.6. Primary outcome measures picture

1.2.7. Secondary outcome measures picture

1.2.8. Clinical trial paradigm for etiologic research you need

1.3. Study size

1.3.1. picture

1.4. Aim of intervention

1.4.1. Explanatory study

1.4.2. Pragmatic study

1.4.3. example picture

1.5. Selection

1.5.1. Comparability of natural history NHi = NHr

1.6. Comparability of extraneous effects (EFi = EFr)

1.6.1. placebo or fake treatment iin the reference group

1.6.2. picture

1.7. "Intention to treat" analysis

1.7.1. picture

1.8. Comparability of information

1.8.1. IBi = IBr

1.8.2. Doctors

1.8.3. Patients

1.8.4. picture picture

1.8.5. Randomisation is not always needed very soft very hard outcomes everything in middle YES

1.9. Basic data analysis

1.9.1. picture - data analysis 1

1.9.2. picture - data analysis 2

1.9.3. picture - data analysis 3

1.10. CONSORT 2010 checklist of information to include when reporting a randomised trial

1.10.1. important to look at

1.10.2. example ICSS trial International Carotid Stent Trial Elegibility interventions randomisation outcome measures picture Outcome assessment blinded Sample Size picture New node

1.11. Validity and generalisability

1.11.1. picture

2. presentation 2

2.1. picture

2.2. Cohort study

2.2.1. Example Basal artery thrombosis picture aim BASICS study Determinants primary outcome picture Baseline variables picture results picture Risk rations Reflections picture 1 picture 2

2.3. Case control study

2.3.1. Example picture Lay out data case-control study picture Advantages case-control study picture Design options in case-control studies picture picture Selection of controls picture picture RATIO study - 1 Ratio study - 2 no pic Biases picture solutions Data RATIO study - 3 picture Data RATIO - 4 picture

3. Presentation 3

3.1. Common errors in research

3.2. prognosis

3.2.1. pitfalls in studies of prognosis selection by indication inappropriate measures known risk factors shall always be included in equations Chance findings always happen

3.3. statistics

3.3.1. interval scale vs ordinal scale

3.3.2. Is your data normal divided? check the shape of your data

3.4. diagnosis

3.4.1. Take a structure approach to diagnosis don't rely on chance Tests have false positive / negative results eg chance to have MS eg chance to have white spots on brain in MRI picture study Sensitivity / specificity A single measure of test properties can be combined with a priori odds