Exam notes Flashcards
What percentage of patients do not receive care according to present scientific evidence?
Or care provided is not needed or potentially harmful?
- 30-40%
- 20-25%
What are the barriers to EBP
Proffessional barriers?
Social barriers
- lack of financial reimbursement for EB care
- lack of time in consultation
- fear of legal liability
Professional barriers?
- lack of skill
- doctors sense of information overload
Social barriers:
- patient expectations
- advocacy (Advocacy is a political process by an individual or group which aims to influence decisions within political, economic, and social systems and institutions)
Consumers must ask?
Consumers should be able to expect from their doctors?
- What are my options
- What are the expected outcomes
- What is the likelihood of each expected outcome
Consumer expectations?
- know his subject, know what evidence is available and draws on it
- use expertise and experience
- compassionate- every patient is different
What are the 4 challenges that face physicians?
- Reaching correct diagnosis
- selecting management that does more good than harm
- Keeping up with useful advances
What is evidenced based practice?
Extend on each
Integration of best research evidence with clinical expertise and patient values and circumstances
- Best research evidence: patient centred clinical research into accuracy and precision of diagnostic tests, power of prognostic markers, efficacy and safety of therapeutic, rehabilitative and preventative regimes
- Clinical expertise: ability to use clinical skills and past experience to rapidly identify each patient’s unique health state and diagnosis, their individual risks and benefits of potential interventions and the patients personal values and expectations, must be biologically plausible
- Patient values and circumstances: the unique preferences, concerns, expectations and circumstances each patient brings to a clinical encounter and which must be integrated into clinical decisions if they are to serve the patient
What is the P value, what does it mean?
-measure of strength against the null hypothesis
The null hypothesis (H0) is a hypothesis which the researcher tries to disprove, reject or nullify.
eg H0: Tomato plants show no difference in growth rates when planted in compost rather than soil.
-less than 0.05 means that it is clinically significant
The P value or calculated probability is the estimated probability of rejecting the null hypothesis (H0) of a study question when that hypothesis is true.
What a confidence interval?
what are the things that can affect it?
-what does the CI indicate?
So its basically how confident you are that the samples results mimic the true population. A small confidence interval is better. 2 things that effect it is variation within the population- more variation the bigger the CI.
-and the sample size- the bigger the sample the smaller the CI. The smaller the sample the less likely it is to represent the true population.
-so the CI gives a measure of precision or uncertainty of study results for making interferences about population under question.
-95% of such intervals will contain the true population value
-indicate strength of evidence about quantities of direct inter.
If the wisker thing crosses the 0 its bad -worthless- not clinically significant.
Hierarchy of Evidence types?
- Systematic reviews of randomised controlled trials
- systematic reviews use rigorous methods to identify, critically appraise and synthesis relevant studies. - Individual RCT- a randomised controlled trial.
- used in testing the efficacy of medicines - SR of cohort studies
- Individual cohort studies
- Outcomes Research
- SR of case-control studies
- Individual case control study
- case series
- Expert opinion.
EBP needs the following steps?
- Converting info needs from clinical encounters into questions with an answerable format
- Locating best available evidence in order to answer these questions
- Critically appraising the evidence (exam internal validity, assessing important or size of effect, deciding on relevance (exam internal, assessing importance or size of effect, deciding on relevance to your clinical practice
- Applying the information from critical appraisal to care of individual, requires integration of our critical assessment of article with clinical expertise and knowledge about individual patients, their values and circumstances.
What does PICO stand for?
- Population, patient or problem
- Intervention, prognostic factor or exposure
- Comparison
- Outcomes
- In patients with (patient, population, problem) does (intervention) affect (outcome) compared to (comparison)?
- Also, type of question and type of study?
what are the common types of questions related to clinical taste?
- Therapy and prevention: Evidence for question of therapy efficacy, RCT’s, SR’s
- Harm/aetiology: how to identify causes for harm or causes of disorder, cohort, case control studies
- Diagnosis: how to select and interpret diagnostic tests, ‘gold standard’ test
- Prognosis: how to estimate patients likely clinical course over time and anticipate likely complications of disorder
Secondary research?
- Systematic reviews: focus on a clinical topic and answer a specific question
- Meta-analysis: takes systematic reviews and summarises the results of several studies into a single estimate of their combined result (through statistical analysis)
- Practise guidelines: systematically developed statements to assist practitioner, review and evaluate evidence and then make explicit recommendations for practise
Data bases and resources
- Medline: medicine, nursing, dentistry, vet, health care system
- Pubmed: access to Medline, InProcess citations OldMedline and citations to out-of-scope articles, diagnosis, aetiology, therapy or prognosis, systematic reviews and meta-analysis
- Cochrane: systematic reviews
Describe natural history studies
- The course of disease from onset to resolution
Stages
1: pathological onset
2: pre-symptomatic stage-> from onset to first appearance of symptoms/signs
3: clinically manifest disease, may progress inexorably, be subject to remissions or regress spontaneously - Detection and intervention may alter natural history of disease
- Eg. Sciatica: stage 1 -> silent internal disc disruption from a degenerative process,
Stage 2-> LBP, stage 3-> fully blown leg pain which may regress spontaneously
Disease frequency studies?
- Quantify occurrence of disease
- Need numerator and denominator
- Can put this in terms of incidence and prevalence = rates
- Incidence = number of new cases per unit time
- Prevalence = number of cases present at a particular time/ in a time interval
Descriptive studies
- Describe patterns of disease occurrence in relation to variables eg. Person, place, time
1. Correlation - consider patterns of disease among populations
- look at measures that represent characteristics of populations that are used to describe disease in relation to some factor
- correlation coefficient r: quantifies extent to which there is a linear relations between exposure and disease, +1 - -1
- Limitations: limited ability to link exposure with disease, what is cause and what is effect?
Case report or case series
- describe experience of single patient/ group of patients with similar diagnosis
- may lead to formation of new hypothesis (usually unusual feature of disease or patients history has been identified)
- cannot be used to test for presence of valid statistical association or to demonstrate efficacy in therapy
- commonly used for alerting a potential adverse event or providing an unusual diagnostic presentation
- generally, limited to hypothesis generation (do not show convincing evidence in terms of preventative or therapeutic intervention)
Cross sectional surveys of individuals
- exposure and disease of interest are assessed simultaneously
- provide snapshot in time of condition
- eg. National health surveys, LBP prevalence study
- limitations: cannot determine temporal sequence between exposure and outcome
Ecological studies
- units of analysis are populations or groups
Case control studies (retrospective)
Odds ratio - what is it?
What are the limitations to a retrospective study?
- observational analytic epidemiologic investigation
- subjects are selected of basis of whether they do (cases) or do not (controls) have disease
- cases are uncommon and are selected, then matching controls are assembled for comparison
- retrospective
- statistically results are often quoted as odd ratios with confidence intervals
Odds ratio:
- ratio of odds of having the disorder in question if exposed to the factor in question divided by the odds of having the disorder if not exposed to the factor in question
Limitations:
- limitations: retrospective, recall bias, other factors may have intervened, selection bias, hospital controls are often ill in another way, relying on medical records
Cohort study
- observational analytic study
- group or group of individuals are defined on basis of presence or absence of exposure
- ‘follow up’ study -> subjects followed forward over time (prospectively)
- Subjects have been exposed to risk factor but do not have disease in question, subjects then assessed over time to see if disease manifests
- Useful for rare exposures
- Can use similar statistic to odds ratio -> relative risk = risk of getting disease if exposed vs. risk of getting disease if not exposed
Look at the table of comparison of cohort, case control, prevalence
s
Experimental Studies
- Clinical trial where individuals are randomly allocated to 2+ groups (experimental and control groups)
- Experimental group is given treatment, control group is given another treatment, sham, placebo or no treatment
1. Therapeutic: agent/ procedure given to relieve symptoms or improve survivorship of those with disease
2. Intervention: intervention before disease has developed in individuals with characteristics that increase risk of developing disease
3. Preventative: attempt made to determine efficacy of preventative agent/procedure
View table
Blinding
Single blind study
double blind
triple blind
- Single blind study: subjects not sure what group they are
- Double blind: single blinding plus observer taking data are blind
- Triple blind: double blinding plus analyser is blind
Systematic review
- Synthesis of all eligible controlled trials about a specific question
- Common method used to pool all data from a RCT-> meta-analysis
Normal, abnormality, reliability and validity.
What is normal? Whats it indicative of?
⇒ Normal
- Within the usual range of variation in a given population or population groups, or frequently occurring in a given population or groups, 95.44%, within 2 standard deviations of mean
- In good health, indicative or predictive of good health or conducive to good health (for a diagnostic test -> normal is in a range in which the probability of a specific disease is low)
- Gaussian distribution ——————————————→
- Normal limits: compare normal values obtained when measurements are made in 2 groups, one that is healthy and has been found to remain healthy, the other ill, or has subsequently found to become ill
- Result may be 2 overlapping distributions (overlap may have normal or abnormal patients)
read the reading
Normal, abnormality, reliability and validity.
Reliability?
Types of reliability?
⇒ Reliability
- Degree to which the results obtained by a measurement procedure can be replicated under identical conditions
- Lack of may arise from divergences between observers or instruments or instability of the attribute being measured
- Inter-rater reliability
- Clinicians agreeing
- By chance alone will be 50% of the time
- Examiners discipline, experience level, consensus on producer used, training before study and use of symptomatic subjects does not improve reliability - Intra-rater reliability
- Level of agreement by same observer - Kappa
- rates agreement
- from 0-1
- level of agreement beyond chance divided by the level of agreement possible beyond chance
look at Kappa value and degree of agreement.
Vailidty
What are the types of validity?
- Method is sound
- Usually tested against a gold standard
Internal validity - internal study design is such that we can have confidence that it sets out to do what it claims to do
- usually achieved by critical appraisal
External validity
- Capacity of study to be generalizable to target population outside the sample studied
- Based on sample of subjects in the study
Measurement validity
- Degree to which a measurement measures what it purports to measure
- Construct validity
- Extent to which measurement corresponds to theoretical concepts concerning phenomenon under study
- Eg. Spinal degeneration worsens with each adult decade as does hair loss and weight gain - Content validity
- Extent to which measurement incorporates domain of phenomenon under study
- Eg. Measurement of functional health status should embrace ADL’s, occupation, family and social functioning - Criterion validity
- Extent to which measurement correlates with an external criterion of phenomenon under study
- Concurrent: same point in time, ankle jerk missing and person has L5.S1 disc herniation
- Predictive: measurements validity is expressed in terms of ability to predict criterion eg. Finding exposure to a large dose of radiation and being able to predict that the person will develop cancer in the future
Face validity
- Indicates after reading proposal one believes that it seems valid
- Eg. Read about a new instrument designed to measure neck disability and after pursuing the question you decide it appears valid (on the face of it)
Evidenced based approach to diagnosis and screening test.
Diagnostic tests
What is sensitivity and specificity?
⇒ Diagnostic tests
- any type of information that could be helpful in making a diagnosis
- To identifying anatomical structure involved or process responsible, make informed decision about treatment, give patients accurate info about prognosis
- Refine probability of presence/absence of a disease or disorder (the results of a diagnostic test should change the likelihood of a particular diagnosis
- What we think before test + test information = what we think after
⇒ Sensitivity
- Proportion of truly diseased persons in screened population who are identified as diseased by diagnostic test ie. Probability that any given true case will be identified by test “true positive rate”
- if low -> proportion of patients with disease who have a positive test is low
⇒ Specificity
- Proportion of truly non-diseased persons who are so identified by screening/diagnostic test
Ie. Measure of probability of correctly identifying a non-diseased person with a screening test “true negative rate”
- If high -> proportion of patients without the disease who have a negative test is high
view tables
Whats pre-test probability?
⇒ Pre-test probability: Probability patient has disease before undergoing test
- Clinical data
- derived from clinical assessment (previous test results from patient, personal clinical experience)
- reliant on careful, unbiased estimate - published data
- giving prevalence of disease in a defined clinical setting/population - clinical prediction rules
- developed from research into factors that may predict a disorder that responds to a specific treatment
- ie. Have these symptoms -> more likely to have this disease
Post-test Probability?
⇒ Post-test probability: probability patient has disease given test results
Likelihood ratios (LR’s)
- Alternative way of describing performance of a diagnostic test
- Can be used to calculate probability of disease after a + or – test
- Likelihood that a given test result would be expected in a patient with the target disorder compared with the likelihood that the same result would be expected in a patient without the target disorder
- Defines how much a + or - test result modifies the probability of disease
-be able to calculate it -liklihood ratio
Critical Appraisal guide: Diagnosis.
What are the questions we must ask
- Is the study valid (internal validity)?
- Measurement: was there an independent blind comparison with a gold standard reference test?
- Representative: was test applied in appropriate spectrum of patients?
- Ascertainment: was reference standard applied or ascertained regardless of test result?
- Were test methods described in sufficient detail to permit replication? - Are the valid results of this diagnostic study important to me?
- What were the results?
- Are likelihood ratios provided or is data necessary for their calculation provided? - Can I apply this valid, important result to my patient (relevance)?
- Will reproducibility of test result and its interpretation be satisfactory in my setting?
- Are results applicable to my patient?
- Will results change my management?
- Will patient be better off as a result of the test?
What is the traffic light system used for?
What does each colour traffic light tell you?
Why do you examine your patient?
Traffic light system is used to examine the patient.
Red light- illogical test that hasn’t been tested
- illogical test that was tested and found not to work
- logical test that has been tested and found not to work
Yellow Light:
- logical test that hasn’t been tested
- logical or illogic test that has been tested and received different results or with moderate success
Green light:
- Logical test that has been tested and found to work
- illogical test that has been tested and found to work
- several moderately useful test combined and found to work when considered together
Why do you examine your patient?
To detect any contra-indication or non-indication to chiropractic treatment.
What are the sources of Bias in experiments?
Selection bias- allocation of subjects to groups
Performance bias- implementation of interventions e.g. real vs sham
Attrition bias- follow up of participants
Detection bias- Evaluation of outcomes
Precision and Confidence intervals
Precision: measure of likelihood of random errors, reflected in confidence intervals around estimate of effect.
CI’s can be used to examine statistical significance and provide us with more info than P values
CI’s
- exact effect size (treatment effect observed in particular study) is called point estimate
- best estimate from study of true effect size
- precision or stability of estimate may be expressed using confidence intervals
- 95% CI usually reported
- studies with larger sample sizes give more precise estimates and narrower confidence intervals
- the narrower the CI- more certain you can be about true effect
- results are statistically significant at 0.05
Type 1 Statistical error
- difference due to chance alone , represents a true difference
- FALSE POSITIVE
- statistics used to determine likelihood of type 1 error = a
- P value quantifies probability that observes difference between 2 studies by chance alone (assuming there is no difference between groups)
Whats the P-value?
P < 0.05= statistically significant
- 1/20 prob that difference is due to chance
- highly statistically significant results could be misleading if study methods were bias or had systematic error
Therapy and harm, why study results may mislead- bias and random error
- internal validity: extend to which design and conduct are likely to prevent systematic error or bias
- more methodologically rigorous studies may yield results closer to the truth i.e. better external validity –> generalisable.
Type 2 Statistical Error
CI’s also used to help interpret results of studies that appear negative
- negative result may be true negative or false positive (type 2 error)
- B
- may arise if study has insufficient statistical power to detect true difference between groups
- often occurs because of lack of subjects.
Measure of treatment effect
- results of studies with binary outcomes (yes/no) may be expressed in several ways
- relative benefit of active treatment over control is often expressed as relative risk or odds ratio.
- if applying results to clinical practice –> NNT is more meaningful
NNT- number needed to treat
- Number of patients needed to treat to provide one additional positive outcome when compared to other therapy
- In harm prevention study: number of patients needed to treat to prevent one additional bad outcome
- NNH = number of patients required to treat before seeing one case of harm
Absolute Risk reduction?
Relative risk?
Relative Risk reduction?
-difference in proportion of subjects with the outcome of interest in each group.
-probability of an event in active treatment group divided by probability of event in control group
1- relative risk, measure of absolute risk reduction, ARR divided by probability of event occurring in control group
External validity (generalisability)
- Results of RCT may not be generalizable
- RCT’s address question of whether treatment can work (efficacy) but may not tell us whether treatment may be effective (effectiveness) when offered to broad range of patients see in clinical practise
- Efficacy: treatment might work but might not be accepted/ will work outside clinical trial
- Effectiveness: commonly accepted
Inclusion/ exclusion criteria
- Used in order to limit sources of heterogeneity that may influence study results
- Can narrow focus so results may not be generalizable
Intention to treat analysis (ITT)
- Impute numbers into data to replace missing data
Evidence based guide to harm.
Whats it involve?
- Need to evaluate evidence about causation -> for validity, importance and direct relevance to patients
Guide to harm
Tests for causation (Bradford-hill rules for causation)
-assosiation doenst demonstrate causation
Testing for causation: Strength of results? Consistency of evidence? Specificity in cause? temporal relationship? Dose-response? Does association make biological sense? Coherence or consistency of evidence over time? Experimental evidence? Anaology?
- Strength of results
- Clinical and statistical strength (magnitude of effect)
- Larger the effect size, closer the confidence intervals, smaller the p value (signs results didn’t occur by chance alone)
- In case control OR must be 4 or more
- In cohort, RR must be 3 or more - Consistency of evidence
- Similar results from other studies of same problem
- If effect size is similar, evidence is stronger
- Should be similar results and evidence on varying types of study - Specificity in cause
- In ideal situation, effect has one cause
- Outcome is best predicted by one primary factor adds credibility to cause
- De-challenge re-challenge test: if adverse outcome decreases or disappears when possible causative agent is withdrawn, then re-appears when agent is re-introduced -> suggests causal agent - Temporal relationships
- If exposure precedes outcome in time, suggests possible causal relationship
- Temporal sequence is correct - Dose-response
- If likelihood of adverse outcome increases with level of exposure to factor of interest, suggests causal relationship - Does association make biological sense
- Causal relationship more likely if association between factor and adverse outcome makes biological sense - Coherence or consistency of evidence over time
- A cause and effect interpretation for an association is clearer when it does not conflict with what is known about variables under study and when there is no plausible competing theories or rival hypothesis - Experimental evidence
- Any direct research that is based on experiments will make causal inference more plausible
- Experimental tests agent to see if person gets disease - Analogy
- Weakest test
- Refers to similar results in a related test
- Eg. If lifting heavy weight causes LBP, lends weight to notion that it will cause thoracic pain
