An Introduction to Critical Appraisal Dr Ghamdi.pdf

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An Introduction to Critical Appraisal

Kholoud S. Al Ghamdi (MD, PhD)

November 27, 2014



اشراحرإن

بإاقذك

عروبقيقإواسثء

به

بجداقأداإذا

.اقد

د

.سدعا

Criticism is important in the

continuation of the humans’ life

cycle, since every human, without

exception, has his/her own

shortage in one or more aspects of

life and every person admits this. So

as long as shortage exists, there isalways place for criticism.

Dr. Salman Alowdah



“It is astonishing with how little reading a doctor can practice

medicine, but it is not astonishing how badly he may do it”



What is evidence based practice?

Evidence-based practice is the integration of

• individual clinical expertise

with the

• best available external clinical evidence from systematicresearch

and

• patient’s values and expectations



What is the Relation Between…

AND

?



The evidence-based practice (EBP) process includes:

• Decision or question arising from a patient’s care.

• Formulate a focused question.

• Search for the best evidence.

• Appraise the evidence.

• Apply the evidence.



Do NOT believe anything people write until

you’ve convinced yourself it was a well donestudy with valid conclusions.



What is critical appraisal?

It is the process of systematically examining research evidence to assess itsvalidity, results, and relevance before using it to inform a decision”

(Hill and Spittlehouse, 2001)

A critical review must identify the strengths and weaknesses in a piece of researchand this should be carried out in a systematic manner

(Eachus, 2003)

It is a skill that needs to be practiced by all health professionals as part

of their work.



Why do we need to critically appraise?

studies which don't report their methods fully overstate the benefits oftreatments by around 25%

Khan et al. Arch Intern med, 1996; Maher et al, Lancet 1998.

studies funded by a pharmaceutical company were found to be 4 timesas likely to give results that were favourable to the company than

independent studiesLexchin et al, BMJ, 2003



How do I appraise?

You need to know if this research is:

Valid & Relevant

• Mostly common sense.

• You don’t have to be a statistical expert!

• Checklists help you focus on the most important aspects ofthe article.

• Different checklists for different types of research.



• What is the objective/hypothesis of this manuscript?

•What outcomes are being measured?What is the data type gathered?

• Is the study biased, is there confounding, can the results be explained by chance?

Subject selection, data collection proper?

•Are the conclusions supported by the study data?

Appropriate statistics, adequate power?

• Was the study ethical and without conflict of interest?

General Questions to Ask



Research methods

Quantitative

• Uses numbers to describe and analyse

• Useful for finding precise answers to defined questions

Qualitative

• Uses words to describe and analyse

• Useful for finding detailed information about people’s perceptions and attitudes



What type of study is it?

• Descriptive studies – Data used for descriptive purposes and not used to make predictions

– Correlational studies, case reports or series, cross sectional surveys

– Measures of central tendency (mean, median, mode)

• Inferential studies – Use data from study sample to derive conclusions and/or make

predictions about the population

– Statistics used to prove or reject hypothesis



What type of study is it?

• Systematic reviews

• Randomized controlled trials

• Prospective studies (cohort studies)

• Retrospective studies (case control)

• Case series and reports



What is the intervention?

What are the:

Dependent

Independent

Confounding

variables of the study?



Who are the subjects?

The ideal patients to study is from a random sample

most studies do not use a totally random sample

selection bias!

Subject inclusion/exclusion criteria?



Is the study internally valid?Do I believe it?

Assess hypothesis/objective of the study

Research hypothesis what the researcher predicts

Null hypothesis (Ho) there is no difference in outcome between the two

groups; in general expect the null hypothesis to be rejected because researcher

usually predicts a difference between groups

Alternate hypothesis (H1) there is a difference between the groups; typically,researcher expects this to be supported so this is the research hypothesis



Systematic reviews

• Thorough search of literature

•All RCTs (or other studies) on a similar subject synthesised and summarised.

• Meta-analysis to combine statistical findings of similar studies.



Appraising systematic reviews

• Was a thorough literature search carried out ?

•How was the quality of the studies assessed?

• If results were combined, was this appropriate?



Randomised controlled trials (RCTs)

• Normal treatment/placebo versus new treatment.

•Participants are randomised.

• If possible should be blinded:

• Best design is when neither the investigator nor the subject know whichgroup they are in (double blinding)

• Intention to treat analysis



Appraising RCTs• Recruitment and sample size

• Randomisation method and controls

• Confounding factors: factors that 'get in the way‘

• Blinding

• Follow-up (flow diagram)

• Intention to treat analysis

• Adjusting for multiple analyses



“As a non-statistician I tend only to look for 3 numbers

in the methods :

• Size of sample

• Duration of follow-up

• Completeness of follow-up”

Greenhalgh, 2010



Assess adequate sample size

• Especially important for descriptive statistics

– 83% success rate in 6 patients is different from same success rate in 600 patients

• In general, inferential statistics take sample size into consideration

– Results may trend towards significance (p = 0.05) with low sample size but becomesignificant if more subjects were enrolled

• In research design, however, power calculations should be done to assess adequatesample size



Cohort studies• Prospective

• groups (cohorts)

• exposure to a risk factor

• followed over a period of time

• compare rates of development of an outcome of interest

• Confounding factors and bias



Case-control studies• Retrospective

• Subjects confirmed with a disease (cases) are compared with non-diseased

subjects (controls) in relation to possible past exposure to a risk factor.

• Confounding factors and bias



Appraising cohort/case control studies

• Recruitment – selection bias

•Exposure - measurement, recall or classification bias

• Confounding factors & adjustment

• Time-frames

• Plausibility: a relationship between a putative cause and an outcome



Publication bias/ Results

papers with more ‘interesting’ results are more likely to be:

– Submitted for publication

– Accepted for publication

– Published in a major journal

– Published in the English language



Results• How was data collected?

• Which statistical analyses were used?

• How precise are the results?

• How are the results presented?



Statistical testsType of test used depends upon:

• Type of data – categorical, continuous etc

• One- or two-tailed (or sided) significance

• Independence and number of samples

• Number of observations and variables

• Distribution of data, e.g. normal



P values

• P stands for probability - how likely is the result to have occurred by chance?

• P value of less than 0.05 means likelihood of results being due to chance is lessthan 1 in 20 = “statistically significant”.



• When a difference is shown, it could be due to

(1) chance or

(2) a true finding

– Chance (Type I error), False positive

– Generally we accept less than 5% chance of type I error; so check that alpha

level (P value) is set at ≤0.05 for level of significance.

P values



• When no difference is found (accept null hypothesis), it could be:

(1) The truth

(2) False negative (Type II error, beta)

– Beta is typically set at 20%

– Power of the study is defined as the probability of true positive (accept

alternate hypothesis), typically 0.80 (i.e. there is an 80% chance of detectingthe difference if one truly exists)

P values



Statistical significance

• statistical significance does not necessarily equal clinical significance

• statistical non-significance may be due to small sample size

• A bigger sample may result in a statistically significant difference



You also will need to look for the following:



Look for Sources of Bias in the Study

• Bias

– Things that may influence the research and lead to a systematicdeviation from the truth

– May occur in each stage of data manipulation:

• Collection

• Analysis

• Interpretation

• Publication

• Review



• Design bias

• Sampling bias• Observer bias

• Reviewer bias

Examples of Bias in a Study



Sampling bias is introduced when the sample used is not representative of the

population or inappropriate for the question asked.



Look for Confounding Variables

• A confounding variable is one that is associated with the predictor variableand is a cause of the outcome variable

– Example: An association was seen in a study between coffee drinking and MI.

However, if more coffee drinkers were also smokers then smoking is theconfounding variable

- So need to know other risk factors for disease

- Randomization reduces confounding but this research design is not alwayspossible



Look for adequate follow-up

• In general the follow-up should be at least 80%.

• Inadequate follow-up or too many loss to follow-up is a serious flaw in

research;

– What if only the happy patients followed up with the study?

• The authors should account for all patients lost to follow-up, and at least

discuss the potential bias and data scenarios



Look for statistical measures used and findings

• What is the data type measured for outcomes? – Nominal (categorical)

– Ordinal (rank order)

– Continuous

– Ratio



• Check that proper statistical analysis was performed; example,

– Categorical data chi square

– Ordinal dataMann - Whitney U Test, spearman’s rho, weighted kappa

– Continuous data t-test, Z-test

• Keep a statistical reference book handy to review new statistical terms whilereading journal articles until familiar with it

Look for statistical measures used and findings



Look for Disclosure?

• Disclosure

– “the act of revealing something”

• Medical Disclosure

– Author, editor, and reviewer must disclose any financial or personal

relationships that inappropriately influence (bias) his or her actions



"Moderation of Critical Appraisal session/ Journal club

The role of a moderator of a session:

1: Identifying or help in selection of paper. The paper must not be a 'perfect'

paper published in 'Nature' or 'Lancet', It must have some deficiencies to

generate critical appraisal/discussion

2: Following the critical appraisal checklists as regards critique of different

items: critique of title, abstract, introduction, methods, results, discussion,

conclusions, references.

3: Minimal interference. Listening and interfering only when the presentingstudent or attending students make a blunder or attending faculty do not

contribute in a matter of difference of opinion. Let the presenting student

'present' and attending students discuss



"Moderation of Critical Appraisal session/ Journal club

The role of a moderator of a session:

4: Preparation: so that moderator is capable of supporting or negating some

views if the need is there.

5: Awareness of the methods and particularly statistics used in the paper.

6: Evaluation of presenting and attending students.

7: Advertising: Ensuring that the student sends information/invitation andreminder to all students and faculty. Encourage faculty to attend, add

'attractants' like prizes or refreshments!



http://www.sign.ac.uk/methodology/checklists.html

Critical Appraisal: Online Notes and Checklists





Dr. Sarah [email protected]

Dr. Samira [email protected]

Dr. I. [email protected]

mailto:[email protected]






Thank you.

An Introduction to Critical Appraisal Dr Ghamdi.pdf

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