exam 2 Flashcards

Question

best test for trying to rule out a disease

Answer 1

-use a test with a high sensitivity and high neg predictive value. -works best when pre test probability of disease is low. -SnNOUT

Answer 2

Use a test with high specificity and a high PPV. Works best when pre-test probability of disease is high SpPIN

Answer 3

-need high sens tests even at the expense of specificity. -false negs can have large consequences. -avoid at all costs -do multiple tests interpreted in parallel.

Answer 4

 High treatment costs  Treatments that are potentially dangerous  Euthanasia of valuable animal might be possible  Use highly specific tests  Multiple tests should be interpreted in series

Answer 5

-this is a continous outsome for a diagnostic test. ex enzyme levels. - It is impossible to find a cut-point which will perfectly discriminate between the 2 groups of animals

Answer 6

 False negative results are not acceptable  False positives could be controlled by using a second more specific test on initial positive results  Consequences of false positives are not severe  Disease can be treated, untreated cases are fatal

Answer 7

False positive results are not acceptable  False negative results are controlled by using a second test in parallel  False negative consequences are not severe  Disease is severe but confirmation has little impact in terms of therapy or prevention

Answer 8

 Cut-off values are flexible!  May vary between populations and test purposes  May have an intermediate zone (grey or “fuzzy” zone)  Animals with results in this zone are re-tested after a certain time period

Answer 9

- Graph the true-positive rate on vertical axis (Sensitivity) - Against false-positive rate on horizontal axis (1-Specificity) - Point closest to top left corner will maximize sensitivity and specificity -consider costs of false pos and negs because when we set our cut off points.

Answer 10

-Sampling volunteers or a sample of the population to detect disease -Seeking an early diagnosis when a client brings animal to veterinarian for unrelated reasons. -specificity is most important

Answer 11

 Clients that bring animals for screening tests are not the same as those that don’t  Better management, improved health status  Therefore, more likely to live longer etc.

Answer 12

 Comparing survival times after early diagnosis to survival times after conventional diagnosis  The “zero point” for the survival time is time of diagnosis.  If early diagnosis takes place before conventional diagnosis, and lead time is not taken into account = Lead time bias -does early diagnosis actually give the animal a longer life, not just a longer life from the time of diagnosis.

Answer 13

 Long pre-clinical phase diseases usually have a long clinical phase  Short pre-clinical phase diseases usually have a short clinical phase  Therefore, those diseases that are more likely to be detected by screening tests will survive longer than those that are not

Answer 14

 Marketing our treatment on clients! Need to be sure of efficacy!  False Positive Risk: Especially important if there is a debilitating treatment involved  Labeling: More important in human medicine

Answer 15

 Determine prevalence of infected herds  Certify herds as disease negative for eradication or trade  Examine risk factors for herd level disease

Answer 16

 Uncertainty around individual Se and Sp are amplified in HSe and HSp  Bias in individual Se and Sp are amplified in HSe and HSp  Impact of false results is generally greater

Answer 17

 A positive test is not a positive diagnosis  False positives can occur in clean herds  Note that as disease prevalence drops in the herd, the PPV of the screening test gets progressively worse  Need tests with very high specificity especially when prevalence is low

Answer 18

 Ideal in situations where within-herd prevalence is low -when we are pretty sure there is no disease there but we want to be sure.  Pros: -Decreased laboratory cost -Increased HSe due to increased n  Cons: - Risk of decreased Se due to dilution - Logistical challenges of mixing sample

Answer 19

 Comparing 2 tests agreement (neither of which is a gold standard)  Comparing agreement between 2 clinicians  Comparing agreement within clinicians -want to know kappa statistic -can also do latent class analysis

Answer 20

-The proportion of agreement measured beyond that expected by chance alone -higher the kappa % better the test is 70> is decent. above 80 is great.

Answer 21

* None of the tests are treated as the imperfect gold standard * Maximum Likelihood Estimation (MLE) – Independence between tests required – Observed data * Bayesian – Allows for correlated tests – Prior information + observed data

Answer 22

-a series of events clustered in time and space  A systematic procedure to identify causes (risk factors) of disease outbreaks and impaired productivity

Answer 23

1. Halt the progress of disease 2. Determine reasons for the outbreak 3. Recommend procedures to reduce the chance of future outbreaks

Answer 24

the 5 W  DEFINE THE PROBLEM – “WHAT” ( Establish the existence of the outbreak or “sub-optimal” productivity problem)  DEFINE THE GROUPS - Describe “WHO” was affected “WHEN” and “WHERE”  Collect samples -establish WHY -TAKE ACTION -FOLLOW UP

Answer 25

-gather data to make good case definition to compare cases to non-cases  Comparing clinical cases to sub- clinical cases

Answer 26

Establish herd inventory: *Body condition score *Establish pregnancy status *Record group affiliation -need to collect samples from enough animals to recognize patterns across groups. (acute vs chronic, young/old, ect.) -timing of samples can be critical

Answer 27

SUCK= blood SCOOP =poop SWAB =nose, eyes, etc. SLICE =necropsies SPOON =feed SIPHON =water SPECIFY =identify

Answer 28

-or verify the pathological and etiological diagnosis  Recognize that in many cases only establishing a definitive pathologic or etiologic diagnosis does NOT solve the producer’s problem.

Answer 29

 Identify important groups and look for patterns of disease  Look for patterns and natural experiments  Orient by subject, place, and time, location  Epidemic curves (could show point source of epidemic or if sporadic) endemic if steady.

Answer 30

-attack rate tables: compare % of sick animals across suspected risk factors (exposed vs unexposed) -get info by examining herd records, finding data is the hard part. -incidence= # new cases in period/ pop at risk (during a given period of time) = risk or ATTACK rate. -include all relevent risk factors on attack table. the risk factor with the HIGHEST RELATIVE RISK is where you start looking for cause of the problem.

Answer 31

= # existing cases/ population at risk (disease AT some point in time)

Answer 32

Cumulative Incidence = # new cases in period / total population at risk (during a given period of time)

Answer 33

-when doing a case control comparison to find disease use ODDS RATIO not RR. - Identify the key determinants for disease:  Key determinants are those risk factors causing the problem that CAN BE MODIFIED on this premises.

Answer 34

 Create a list of action items  Be very specific  Recommendations must be appropriate for individual herd management -Written report with recommendations for action, include plans for follow-up.

Answer 35

 Why be concerned with cause? – So that we can intervene and prevent disease  Basic definition of cause – Any factor that produces a change in the severity or frequency of the outcome.  Do not need to understand all causal factors to prevent or at least control disease

Answer 36

-Traditionally the “gold standard” for causation was an experiment.  In experiments, we randomize individuals to receive a factor and some to receive nothing (or a placebo or standard treatment).  We know factor precedes disease and other variables accounted for by randomization.  We contrast outcomes in treatment and control group. -we know it works but don't know if it will work in a real world situation, difficult to duplicate realistic dose, exposure pathway.

Answer 37

 In observational studies, we estimate the outcome differences between individuals that happen to vary in their exposure status. -real world applications  Use matching and restriction where appropriate to minimize differences between groups.  Measure association between changes in exposure and outcome. -best ones: meta analysis and systematic reviews. then controlled.

Answer 38

-there's an exposure, and a disease or outcome and were looking for the association. -need to compare: to nothing, to treatment, to care.

Answer 39

1. We start by defining groups (cohorts) of animals according to the exposure of the animals in the groups to the factors of interest. 2. We then follow these groups forward in time to see which animals develop the disease under investigation  Compare risk in exposed an unexposed groups and report as the relative risk.  Can look at more than one disease resulting from a specific type of exposure.  Observational study type closest to the RCCT, easiest to interpret ex. exposure + cows of BSE and exposure - cows of BSE= what % have disease.

Answer 40

1. Define groups of diseased and healthy (or control) animals 2. Then assess whether the animals in the two groups have differences in past exposure to different risk factors  We calculate the odds ratio to indirectly estimate relative risk  Good for studying rare diseases.  Can assess more than one exposure in the same study -was exposure before initiation of disease?? hard to prove

Answer 41

-dose not = causation but helps us put pieces together Demonstration of statistically significant association does not prove a factor is causal. To “prove” causal association we need to describe a chain of events, from cause to effect, at the molecular level

Answer 42

 Confounding is the effect of an outside variable that can wholly or partly account for an apparent association between variables in an investigation.  Confounding can produce a spurious association between study variables, or can mask a real association

Answer 43

1. Be associated with the response variable 2. Be associated with the risk factor (exposure or treatment) of interest 3. Not be an intervening or intermediate step between the risk factor and response. Ex: A New Zealand study revealed that wearing an apron during milking was associated with an increased risk of contracting leptospirosis, apron was not the variable it was a large herd size. larger herd size workers wore more aprons. larger herd size is associated with leptospirosis and was the confounder.

Answer 44

 ALL disease is multifactorial.  A cause is described as sufficient if it inevitably produces an effect.  A sufficient cause virtually always comprises a number of component causes.  A particular disease may be produced by different sufficient causes If a risk factor is a component of every sufficient cause then it is described as a necessary cause

Answer 45

– The shared component causes that make up a sufficient cause. * ie. equilibrium disorder, slippery walkway, no grip shoes, no handrail, strong wind, osteoporosis, and other unknown factors = fall and broken hip

Answer 46

 Two or more component causes acting in the same sufficient causes interact causally to produce disease.

Answer 47

 Removal of one or more components from a sufficient cause will then prevent disease produced by that sufficient cause

Answer 48

 Direct and indirect causes may also be thought of as representing a chain of actions with indirect causes activating direct causes producing a “web of causation” -things have to happen in a particular order.  Direct causes are often the proximal causes emphasized in therapy.  Indirect cause is one where the effects of exposure are mediated through one or more intervening variables -ex. nutrional def-> dystocias-> weak calves, no colostrum-> disease.

Answer 49

-Temporality -Strength of association -Biological gradient or dose response - Coherence or plausibility  Consistency  Specificity  Analogy  Experimental evidence

Answer 50

– Cause must always precede effect in time – But the same factor could occur again after disease in some individuals – Often difficult to establish time sequence, especially with surrogate exposure measures

Answer 51

– A strong statistically significant association between a factor and disease increases the likelihood that the factor is causal – Assumes that it is less likely residual confounding could explain the result

Answer 52

– Problem is strength of association depends on distribution of other components of the sufficient cause – Important weak associations have been considered causal: environmental tobacco smoke and lung cancer – Some strong associations are due to confounding: birth order and Down’s syndrome

Answer 53

– Repeated observations of an association in different populations under different circumstances – Associations can be causal under unusual circumstances – Statistical significance should not be used to assess consistency

Answer 54

-There must be a mathematical association between the exposure and the hypothesized effect or outcome – In most cases, the outcome (disease) have a monotonic association with the increasing exposure.  Besides temporality, there are no criteria that are either necessary or sufficient. -the observed association must NOT be due to error or chance or systematic error in the design of the study or data.

Answer 55

– A dose-response relationship between a factor and disease increases the plausibility of a factor being causal – Exceptions to linear change: threshold effects – Most should have a monotonic – a gradient that never changes direction – Exception: alcohol consumption and death – J shaped curve

Answer 56

 A susceptible host  Effective contact with an infectious host  Probability of contact with an infectious host depends on number of contacts with others in the population and prevalence of infection in that population  The likelihood of transmission given contact depends on the number of organisms to which the animal is exposed, the characteristics of the infectious agent, and route of transmission (presence of innate resistance or natural barriers)

Answer 57

Precautions taken to reduce the risk of exposure to disease Preventing introduction of infectious disease Minimizing the risk of disease transmission

Answer 58

Assess – take look at what can go wrong, do often, want to reduce, control and eliminate risk Resist – resistance Isolate – Traffic – Sanitation-

Answer 59

Resistance refers to the animal’s disease defense (immune system) mechanisms having the ability to not become infected if exposed. Increase resistance to infectious diseases implement a strategic vaccination program reduce stress on animals from other diseases, poor nutrition, housing and lack of consistency in management. -ex. getting colostrum reduces risk

Answer 60

Prevent the introduction of infected animals Keep a closed herd. A herd is not closed if: animals are purchased or boarded animals share a fence line bulls are purchased, borrowed or loaned animals are transported by someone else or in someone else’s vehicle

Answer 61

-prevent introduction of infected animals -test to prevent -transport purchased animal in herd owned truck -quarantine newly purchased animals -minimize comingling and movement of infected animals within a facility and of established groups within cattle operations. -do all in all out management -separate risk groups to decrease exposure to disease

Answer 62

-traffic onto and off the operation -includes more than vehicles All animals and people must be considered. Animals other than cattle include dogs, cats, horses, wildlife, rodents, and birds. Pest control should be reviewed

Answer 63

-Remove agent:  Removal or treatment of infected hosts -Stop transmission:  Direct contact with infected host  Indirect contact with contaminated environment  Contact with vectors -Enhance host resistance  Inherent  Acquired

Answer 64

Selective slaughter* Depopulation Quarantine Mass treatment* Mass immunization* Environmental control* Education Applied ecology Genetic improvement

Answer 65

-Test and slaughter” -Deliberate killing of a minority of infected animals to protect the health majority -Usually involves a method of case finding (ie: a diagnostic screening test) -Works well early in disease outbreaks and in slowly spreading diseases  Was used early in Brucellosis eradication in Canada -- Would NOT be used now

Answer 66

-Treating all (sick and well) -Combats diseases occurring at very high prevalence where depopulation and slaughter are not economical or viable -Need safe, cheap and effective therapeutic agent -potential problem of disease resistance

Answer 67

-Creating immunity in population which limits spread and impact of disease Has been successful in past  Canine distemper, parvo virus,

Answer 68

-R 0 ("R Zero"): The average number of susceptible individuals that are infected by each infected individual when all others are susceptible -This is a measure of the ease of transmission of an infectious agent. R 0 = p*c*D p=prob of infection on contact c = rate of contact D = duration of infectiousness

Answer 69

-For communicable infections to establish in a population, on average each infected individual must infect one or more susceptible individual.  If each infects > 1, the outbreak will take off.  If on average each infects < 1, the outbreak will die out.

Answer 70

-The average number of susceptible individuals that are infected by each infected individual in the current epidemiologic context. Depends on  Probability of contact  Probability of transmission given contact  Duration of infectiousness  % of population that is susceptible

Answer 71

-Over the long run, an R*  1 is required for an infectious agent to survive in a group. -The goal of control and prevention strategies for infectious disease is to reduce R * < 1 if not to zero.

Answer 72

fc > 1 - 1/R0 To achieve herd immunity or prevent an outbreak from progressing we need to create immunity in this proportion of the population.

Answer 73

-Utilization of the classic host/agent/ environmental triad to control disease -Includes management, environmental control, feeding, husbandry etc. -Many health management programs revolve around environmental hygiene  eg: ventilation management in barns, laminitis control in dairy cows -Disinfection of fomites: surgical sterilization etc

Answer 74

-population density -housing -environmental conditions

exam 2 Flashcards

(98 cards)