Sam G Campbell
MB BCh, FCFP(EM), Dip PEC(SA), FCCHL.
Chief, Department of Emergency Medicine
Charles V Keating Emergency and Trauma Centre
Professor of Emergency Medicine
Dalhousie University, Halifax, Nova Scotia.
CFPC CoI Templates: Slide 1
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Faculty: Sam Campbell
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Relationships with commercial interests:
◦ Grants/Research Support: Shire, NSHA, BoehringerIngelheim.
◦ Speakers Bureau/Honoraria: Boehringer-Ingelheim,
◦ Other: Employee PraxES Medical Group
CFPC CoI Templates: Slide 2
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This program has received no financial nor in
kind support from anyone
Potential for conflict(s) of interest:
◦ Sam Campbell has received no payment/funding,
from any organization whose product(s) are being
discussed in this program.
CFPC CoI Templates: Slide 3
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Active involvement in Choosing Wisely
Canada
Dal Critical thinking group
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Remind people about Choosing wisely
Basic concept of testing
◦ Why/How tests lie
◦ How should we use them?
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Clinical Context/Bayesian approach
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P.H, 54 yr old 
‘Check up’
CBC, ‘lytes, BUN/Creat, LFTs, Lipids, TSH, Fe,
PSA, Vit B12, folate, Vit D.
Transaminases mildly elevated
Repeat in a month (still up)
Heaptitis serology, ANA, Abd US.
3.5 cm lesion in rt kidney (?angiomyolipoma)
CT – confirms AML
Can Fam Phys 2015;61:535-7.
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Lab:
US and CT:
Missed work
Anxiety ++
Reassurance???
Can Fam Phys 2015;61:535-7.
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L.A.W.
Canadian Journal of Diagnosis (in press)
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What we do is not
benign …
What we ask may not
be either…….
- campaign to help physicians and patients
engage in conversations about unnecessary
tests, treatments and procedures, and to help
physicians and patients make smart and
effective choices to ensure high-quality care.
Lists of interventions of questionable value
from different specialist organizations.
Germany
U.K.
Canada
Japan
U.S.
1970
1980
1990
2000
2008
2011
OECD,
2013
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IOM - 30% of health care spending wasteful,
no added value to patient care
Inappropriate testing
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> 50% of prescriptions for respiratory infections
28 - 65% of lumbar spine MRIs inappropriate
9 - 16% of head scans for headache
Bone density scans, Vit D levels, pre-operative
tests………..
Hunters vs. Fishermen:
This is a simplistic preliminary
discussion of a complicated
issue
Doctors,
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They are just tools, each designed for a
purpose
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Test variability may be related to:
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the test
the interpreter
duration of symptoms/stage of the illness
lab equipment, reagents, procedure, or even lab
error.
Test results should never be
◦ accepted at face value
◦ interpreted without considering pre-test (clinical)
probability of disease.
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Diagnostic tests are used to:
◦ to help establish diagnoses.
◦ Culture ‘more is better’
◦ Relieve pressure from patients/family (Cyberchondria)
◦ To delay making a decision (Entertain the patient while
we wait for something to declare itself)
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Consultant expectations
Save time explaining/examining
Perpetuate the myth of medical clarity
“Routine”
 Screening
 just because it is what we do!
I’m going order this test
because I don’t have time
to tell you why you don’t
need it…
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Diagnosis
◦ Rule In vs. Rule Out
◦ Treatment Threshold
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Out of sight – ethereal/magical
Measured once and rarely challenged
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Presumption that the result will help your
patient
Presumption of benefit exceeding risk
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Phlebotomy risks
Risk of false results
Waste of time/money
Misinformation/misinterpretation
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Don't "make" diagnoses; they supplement
clinical judgement and reduce the level of
diagnostic uncertainty.
Unless applied and interpreted carefully, tests
can be misleading.
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The premise of diagnostic testing is that
there are 2 populations of people
◦ those with the disease
◦ those without .....
who differ on at least one testable parameter.
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Almost all tests lie!
Most tests can be ‘positive’ for several reasons
Not everyone with (for example) pneumonia has
an infiltrate on x-ray and not everyone with an
infiltrate has pneumonia.
Patient variability and test variability result in an
overlap between the results for diseased and
normal populations for virtually all tests
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Most objective tests assess a measurable
parameter and classify the patient as "normal"
or "abnormal."
"Normal" is typically established by
determining test values in disease-free
people and identifying the range in which
95% of this population lies.
There is variability in the normal and in the diseased
population, and overlap between the two groups.
Some levels are therefore compatible with health or disease.
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Imagine a test that screens people for a
disease.
◦ Each person taking the test either has or does not
have the disease.
◦ The test outcome can be positive (predicting that
the person has the disease) or negative (predicting
that the person does not have the disease).
◦ The test results for each subject may or may not
match the subject's actual status – i.e. The test may
lie
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True positive: Sick people correctly diagnosed
as sick
False positive: Healthy people incorrectly
identified as sick
True negative: Healthy people correctly
identified as healthy
False negative: Sick people incorrectly
identified as healthy
Each test will have it’s own strengths
and weaknesses, and we can
describe these.
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Sensitivity: the ability to recognize (rule in)
the thing being tested for
Specificity: Precise – if it says the quality is
present, then it is- able to rule out the thing
being tested for
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A perfect test would be described as 100% sensitive (i.e.
predicting all people from the sick group as sick)
and
100% specific (i.e. not predicting anyone from the healthy
group as sick)
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Highly sensitive tests don’t miss those who
have a disease. The trade off is they will be
positive in people who don’t. These are false
positive results
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Highly specific tests won’t be positive in the
absence of disease. The price? Some who
have it will escape detection. These are
false negatives
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Sensitivity and Specificity are not
independent. When you increase one, you
often decrease the other.
False negatives delay diagnoses. False
positives create them.
All testing is susceptible to both
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Test results are categorized as:
◦ True or false positive, or true or false negative
all relative to a ‘gold standard’ (which may also be
imperfect..)
Gold standard is more accurate, but too slow, expensive or invasive to do as a first line test.
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The false positive rate is not just a function of
sensitivity and specificity.
It is dependent on the actual risks an
individual has of having the disease and how
common the disease itself is.
Thomas Bayes (1701 –1761)
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10% of patients with acute MI fail to develop
ST segment changes.
20-30% of ST↑ have no MI
N Engl J Med 2003;349:2128-35
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‘Screening’ ECG
He has ST elevation
Should we send him to hospital at once?
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‘Monitoring’ ECG completely normal
Cancel the cath?
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~80% of cases will have a high WBC
WBC is ↑ in up to 70 % of patients with other
causes of right lower quadrant pain
Only including ‘grey zone’ cases, it may
perform less well than clinical judgement!
Fig. 1: Hypothetical probability density distributions of measured plasma brain natriuretic
peptide (BNP) levels in 2 subgroups of a study population.
Victor M. Montori et al. CMAJ 2005;173:385-390
©2005 by Canadian Medical Association
Fig. 2: These hypothetical probability density distributions reflect a study population of
middle-aged patients who all have recurrent asthma and chronic CHF. The patients whose
dyspnea is caused by asthma exacerbations look clinically similar to those whos...
Victor M. Montori et al. CMAJ 2005;173:385-390
©2005 by Canadian Medical Association
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Your clinical assessment is still critical!
Likelihood of a positive test result in a patient with the
target disorder compared that in a patient without the
disorder
LR+ = Sensitivity/1- Specificity
LR-+ 1-sensitivity/Specificity
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LR+ 2-5
LR+ 5-10
LR+ >10
LR- 0.5-0.2
LR- 0.1-0.2
LR- <0.1
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Small changes
Moderate changes
Large changes
Small changes
Moderate changes
Large changes
Victor M. Montori et al. CMAJ 2005;173:385-390
©2005 by Canadian Medical Association
The ‘power’ of the test /Likelihood
ratios depends on what you thought in
the first place.
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Radiation/blood loss
Unnecessary intervention
Inappropriate reasurrance
Confirmation bias
Cost
‘one third of health care costs could be saved without depriving any
patient of beneficial care’ Howard Brody, 10.1056/nejmp0911423 nejm.org
• When it doesn’t matter:
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Seasonal viral illness
Prostate screening in >80
Surgical conditions in people not fit for surgery
Minor facial fractures
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When pre-test probability is really low:
◦ Clinical picture
◦ Rare conditions and no risk factors
Spinning a coin to rule out malaria is a really
sensitive test in Tuktoyaktuk
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If you already know the answer
◦ Repeating normal screens too early
◦ OA in older patients
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When risk of investigation/treatment
approaches risk of illness
◦ Contrast medium
◦ Radiation
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When the test can’t answer the question you
need answered
◦ CT scan for cerebellar disease
◦ Lumbar/cervical spine x-ray for ‘sprains’
◦ Sinus x-rays
e.g. 'Ottawa rules’
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Evidence-based guidelines suggest that:
◦ We should tailor screening to individual patient
health profiles and move to "opportunistic"
screening
• We should screen only for conditions that:
 Cause serious illness or functional difficulties, and
 only when an accurate test and effective treatments are
available.
http://www.cfhi-fcass.ca/publicationsandresources/Mythbusters/
Cadman D et al. JAMA 1984;251: 1580-1585.
•
What will I do if the result is
•+ve?
•-ve?
Will it improve the management of my
patient?
• What is the benefit related to the cost?
•
I’ll just do all of the
tests and see what
you might have’
‘
‘I’m going to do a
test to supplement
my clinical
Or,
impression’
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Discussion:
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26 yr old female
Dysuria, frequency, suprapubic discomfort
Afebrile, no back pain, N/V.
Has had previous UTI’s – pretty much the
same..
Our options:
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Urine dip?
Microscopy?
Culture?
Empiric treatment?
Treat only if Positive test?
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Four symptoms and 1 sign increased the probability of UTI:
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Four symptoms and 1 sign decreased the probability of UTI:
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dysuria LR, 1.5
frequency LR, 1.8
hematuria LR, 2.0
back pain LR, 1.6
costovertebral angle tenderness LR, 1.7
absence of dysuria negative LR, 0.5;
absence of back pain NLR, 0.8;
history of vaginal discharge NLR, 0.3
history of vaginal irritation NLR, 0.2
vaginal discharge on examination NLR, 0.7
JAMA. 2002 May 22-29;287(20):2701-10.
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2 most powerful signs/symptoms - history of
vaginal discharge and history of vaginal
irritation
◦ Neg LR of UTI when present (LRs, 0.3 and 0.2,
respectively).
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Using combinations of symptoms:
◦ LRs 24.6 for the combination of dysuria and
frequency but no vaginal discharge or irritation.
◦ In patients with recurrent UTI one study found
that self-diagnosis significantly increased the
probability of UTI (LR, 4.0).
JAMA. 2002 May 22-29;287(20):2701-10.
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Reasonable to rule in infection, but not better
that clinical judgement.
Not good enough to rule it out.
◦ 57-96% sensitive and 94-98% specific for
identifying pyuria
Emerg Med J. 2003 Jul;20(4):362-3.
Am J Med. 2002 Jul 8;113 Suppl 1A:20S-28S.
Ann Emerg Med. 1989 May;18(5):560-3.
◦ In women who present with >1 symptoms of UTI,
the probability of infection is ~ 50%
 Physical exam, and tests are not able to lower the
post-test probability to a level where a UTI can be
ruled out
◦ Specific combinations of symptoms raise the
probability to >90%, effectively ruling in the
diagnosis based on history alone.
JAMA. 2002 May 22-29;287(20):2701-10.