Biostats Flashcards
1
Q
High sensitivity test used for ________
A
screening
2
Q
High _______ test used for confirmation after a positive screening test
A
specificity
3
Q
Probability that a person who has a positive test result actually has the disease
A
Positive predictive value PPV
4
Q
Probability that a person who has a negative test result does not has the disease
A
Negative predictive value NPV
5
Q
How does raising the Sensitivity of a test affect
Specificity
NPV
PPV
A
↑Sensitivity
↑NPV
↓specificity
↓PPV
6
Q
How does raising the Specificity of a test affect
Sensitivity
NPV
PPV
A
↑ Specificity
↑ PPV
↓sensitivity
↓NPV
7
Q
How does Lowering the cut off value affect
Sensitivity
FP
Specificity
FN
A
- ↑ Sensitivity
- ↑ FP
- ↓ Specificity
- ↓ FN
8
Q
How does Raising the cut off value affect
Specificity
FN
Sensitivity
FP
A
- ↑ Specificity
- ↑ FN
- ↓ Sensitivity
- ↓ FP
9
Q
Should Medical errors be disclosed to patients, independent of immediate outcome (harmful or not)?
A
Yes
always
Even if it is about document hand offs
10
Q
Occurs at level of frontline operator
(ex: wrong IV pump dose programmed).
Immediate impact
A
Active Error
11
Q
Occurs in processes indirect from operator but impacts patient care
(ex: different types of IV pumps used within the same hospital)
Accident waiting to happen
A
Latent Error
12
Q
Adverse Event That Is Identifiable, serious, and usually preventable
(ex: scalpel retained in a surgical patient’s abdomen).
An error that never should have happened
A
Never event
13
Q
Retrospective approach. Applied after failure event to prevent recurrence
Uses records, interviews, data
A
Root cause analysis
14
Q
Forward-looking approach. Applied before process implementation to prevent failure occurrence.
Uses inductive reasoning to foresee what may go wrong
A
Failure mode and Effects analysis
15
Q
Patient comfort is prioritized (positive effect) over potential side effects (negative effect).
A
Principle of double effects
16
Q
Program is available to patients ≥65 years old,<65 with certain disabilities, and those with end-stage renal disease
A
Medicare
(Medicare for elderly)
(Medicaid for desitute)
17
Q
Criteria to establish Decision making capacity.
(Being retarded doesn’t count as an exclusion)
A
Informed
Mentally/Mood Stable
Age is over 18
Stable decision making history
Values are consistant
Goals are consistent
Expresses a choice
(IM A SaVaGE)
18
Q
Determined by a doctor for a specific health decision
A
Capacity
19
Q
Determined by a Judge for any/all health decisions
A
Competency
*A competent Judge works with a Capable doctor
20
Q
Incapacitated patient’s prior oral statements commonly used as guide. If patient was informed, directive was specific, patient made a choice, and decision was repeated over time to multiple people, then the oral directive is more valid.
A
Oral advance directive
21
Q
Patient designates anagent to make medical decisions in the event that he/she loses decision-making capacity. Patients may also specify decisions in clinical situations. Can be revoked by the patient if decision-making capacity is intact. More flexible than a living will
A
Medical power of attoreny
22
Q
prohibits cardiopulmonary resuscitation(CPR). Other resuscitative measures that may follow (eg,feedingtube) are also typically avoided
A
DNR order
23
Q
What is the priority of surrogate decision makers if a patietn loses capacity without an advance directive in place
(5)
A
- Spouse
- Children (over 18)
- Parents
- Siblings
- relatives
SPicy CHIPS
24
Q
List 5 exceptions to patient confidentiality
A
- Suicidal/Homocidal patient
- Abused or Abusive patient (kid, senior, prisoner)
- Victims of potential harm by a patient
- Epileptic patients need to be reported so they can’t drive (other who have impaired driving skills too)
- Diseases like HIV, STIs, hepititis, Ebola, Food poisoning, TB need to be reported.
25
witholding information harmful to patient or that undermines decision making capacity
therapeutic privalege
26
List 3 things that increase in old people
Sleep latency (time to fall asleep)
Waking up early
suicide rate
27
Describe the 4 steps of disease prevention:
1. Primary disease prevention
2. Secondary disease prevention
3. Tertiary disease prevention
4. Quaternary disease prevention
1. Prevent the disease (Vaccines)
2. Screen for the disease (Pap smear/DRE)
3. Treat the disease/complications
4. Quit giving unnecessary medical treatments that can harm the patient (Imaging, polypharmy)
28
How to calculate
Case Fatality Rate
(CFR%)
Deaths from disease/ # People with the disease
x100
29
How to calculate
Number needed to harm
(NNH)
1/Attributable Risk
\*Higher number = safer exposure
30
How to calculate
Number needed to treat
(NNT)
1/ Absolute Risk Reduction
\*Lower # = Better treatment
31
How to calculate
Odds Ratio
aka: x's more likely
ad/bc
\* what are the odds that I was born: after death/before christ
32
How is Relative Risk calculated?
| (RR)
**if comparing 2 groups with 2 elements**
**(Diseased vs Healthy & Exposure vs No Exposure)**
a/(a+b) / c/(c+d)
**If comparing one group with 2 elements**
**(Diseased & Exposure vs No Exposure)**
Exposure diseased pts/No exposure diseased pts
33
RR \<1
RR =1
RR \>1
↓ disease occurence (it's good for you)
No association between risk/disease
↑ disease occurence (it's bad for you)
34
The proportion of **_reduction of risk_ because of the intervention** as **compared to a contro**l is called what and how is it calculated?
Relative Risk Reduction
**RRR = 1 - Relative Risk**
Relative risk = **a/(a+b) / c/(c+d)**
or
**treated diseased pts/untreated diseased pts**
35
Attributable Risk (AR)
is the difference in risk with exposed and unexposed groups.
How to calculate it?
a/(a+b) – c/(c+d)
36
How to calculate percent of attributable percent
(AR%)
(RR-1)/RR
x100
37
What is the **_difference in risk_** **because of the intervention** as compared to a control?
How is it calculated?
Absolute Risk Reduction (ARR)
c/(c+d) – a/(a+b)
38
Incidence looks at
New cases
39
Prevalcence looks at
all current cases
40
How is incidence is calculated
new cases/ people at risk
(per unit time)
41
How is prevalence is calculated
existing cases/total population
(at a POINT in time)
42
Prevalance \> Incidence
In what case?
Chronic disease
(ex: diabetes → larger # of existing cases)
43
Prevalence = Incidence
When?
Short course illnesses
| (Ex: the Flu)
44
How does increased survival time affect incidence & prevalence?
Increases prevalence only
45
How does Increased mortality affect incidence & prevalence?
Decreases prevalence only
46
How does Faster Recovery time affect incidence & prevalence?
Decreases Prevalence only
47
How does Extensive Vaccination affect incidence & prevalence?
Decreases
Prevalence & Incidence
48
How does decreasing risk factors affect incidence & prevalence?
Decreases
Prevalence and Incidence
49
Prevalence is increased by
increased survival time
50
Incidence is decreased by only what 2 things?
Vaccination
Less Risk Factors
51
What's the difference between precision and accuracy
**Precision:** the outcomes are all consistently the same (Reliable)
**Accuracy**: The outcomes are all at or near the target goal (Validity)
52
What decreases a test accuracy (validity)
Systematic error
53
Bias decreases what in a test?
Accuracy (Validity)
54
Non-random sampling or treatment allocation
selection bias
55
participants selected from hospital only
Berkson Selection Bias
56
participants who are lost to follow up have worse outcomes
Attrition selection bias
57
awarness of disorder alters recall
recall bias
58
information is gathered in a non-systematic way due to faulty procedure or equiptment
Measurement bias
59
subjects in different groups are not treated the same or using different resources that could be the same
Procedure bias
60
The researcher's beliefs or desires changes the outcome or documentation of the study
observer expectancy bias
61
An extra or hidden factor at play distorts the outcome of a study
Confounding bias
62
Early detection is confused with increased survival
lead-time bias
63
screening tests only effective for detecting diseases with a **_long latency_** vs those that are symptomatic earlier
have what bias?
Length time Bias
64
Randomization can reduce what two biases?
Selection bias
Length time bias
65
Placebos can reduce what three biases
Measurement
Procedure
Observer Expectancy
66
Blinding can reduce what 2 bias
Procedure
Observer-Expectancy
67
Objective, standardized, and previosuly tested methods reduce what bias
measurement bias
68
**Multiple** repeated studies, **cross over** studies, **matching** in groups reduces what bias
confounding bias
69
Measuring back-end survival
(survival according to severity)
eliminates what bias
lead time bias
70
Define Mean, Median, Mode
Mean: sum of values/total values (average)
Median: Middle value (middle)
Mode: Most common value (most)
71
(Standard deviation)2
Variance
72
Mean = Mode = Median
when
Bell shaped curve
Normal distribution
73
Mean\>Median\>Mode
Positive skewed curve
| (aka left leaning)
74
**Mean** less than **Median** less than **Mode**
Negatively skewed curve
| (aka Right leaning curve)
75
Null (H0)
means
no association
76
Alternative (H1)
means
There is an association
77
Stating that there is no effect or difference when none exists
null hypothesis not rejected
78
Stating that there is an effect or difference when one exists
null hypothes is rejected in favor of alternative hypothesis
79
Stating that there is an effect or difference when there is none
Alpha Type 1 error
80
Stating that there is NOT an effect or difference when there is one
Beta Type 2 error
81
If P \< 0.05
what does it mean?
Statistically Significant
\*results being by chance is less than 5%
82
If P \> 0.05
what does it mean?
Results NOT statistically significant
83
Checks the differences between the **means** of **2** groups
T-test
**T** is **mean**t for **2**
84
Checks the differences between the **mean** of **3** or more groups
ANOVA
**3** words: **AN**alysis **O**f **VA**riance.
85
Checks the differences between 2 or more **percentages** or proportions of **categorical** outcomes (not mean values).
Chi Squared Test
**Chi-tegorical**.
86
Checks the differences between 2 **percentages** or proportions of categorical, nominal outcomes.
Use instead of chi-square test with s**mall populations**.
FIsher's Exact Test
87
The closer the absolute value of r is to \_\_\_\_\_, the **stronger the linear correlation** between the 2 variables.
1
\*Correlation does not = causation
88
1. Positive r value =
2. Negative r value =
3. Co efficient of determination =
1. positive correlation (as one variable ↑,the other variable ↑).
2. negative correlation (as one variable↑, the other ↓ variable).
3. r2 (variance in one variable can be explained by variance in another variable).
89
LR+\> 10 indicates
LR–\<0.1 indicates
a highly **specific** test
a highly **sensitive** test.
90
LR+\> 10 =
----------------------------
LR–\<0.1 =
sensitive/ **1 – specific**
T**P**/F**P**
(sensitive TiP FiP)
--------------------------------
**1- sensitive/** specific
F**N**/T**N**
(specific FaN TaN )
91
\_\_\_\_\_\_\_\_ represents a study's strength to detect a difference (ie, effect size) between treatment groups when one truly exists. It depends on _______ (among other factors).
Statistical power
sample size
\*\* studies with greater sample sizes have greater power than studies with smaller sample sizes.
92
Cheap fast way to calculate
TP =
FN =
TP = (Sensitivity) × (Number of patients with the confirmed disease)
FN = (1 − Sensitivity) × (Number of patients with the confirmed disease)
93
Cumulative incidence (CI) is calculated as the total number of **new cases** of a disease over a _specific period_ divided by the number of \_\_\_\_\_\_\_\_\_\_
people at risk at the beginning of the period
aka
(**Total population – current cases**)
94
The _____ is the ratio of the number of people who contract an illness divided by the number of people who were exposed to the illness or at risk.
attack rate
95
In a normally distributed curve
How do you calculate % of individuals 2 standard deviations away from the mean?
The center top of graph = MEAN
Out of a group of 100 individuals
2.35% are 2 SDs away from the mean.
\*So 3 individuals (round up).
96
A _______ is a descriptive observational study design in which a group of patients with a similar diagnosis or treatment is described at a point in time or followed over a certain period. This study design has no comparison group; therefore, it cannot establish associations between risk factors (eg, treatments) and outcomes (eg, diseases).
case series
97
The power of a test is the probability of making the correct decision of rejecting a false H0 (ie determining there is a correlation when one truly exists).
If there is a **10%** chance of concluding no relationship between 2 variables **what is the power the study**?
Power = **1 – ß**
Power = 1 – .10 = **.90**
98
when ____ is assumed to be true (ie **not** rejected) it is informally interpreted as the probability that the observed results are due to chance.
H0
(not rejected = results due to chance)
99
A confidence interval (CI) that includes the null value for an RR (ie, RR = 1) is \_\_\_\_\_\_\_\_\_\_
not statistically significant
100
A Confidence Interval, CI, that **excludes** the null value
(ie, RR = 1) is \_\_\_\_\_\_\_.
statistically significant
101
Prevalence = (Incidence) x \_\_\_\_\_\_\_
(Duration of disease)
102
The odds ratio (OR) is a measure of association used in case-control studies. It quantifies the relationship **between an exposure and a disease**
(ie: everyone is exposed to same hazard, but let's compare why some got the disease and some didn't).
its null hypothesis value is always \_\_\_\_
1
(Odds Ratio = 1).
103
As disease **prevalence increase**s, the **positive predictive value** \_\_\_\_\_\_\_, and the **negative predictive value** \_\_\_\_\_\_\_\_.
increases
decreases
104
\_\_ is the maximum probability of making a type I error that a researcher is willing to accept.
α
\*The value of α is typically set at 0.05, meaning that researchers are willing to accept up to a 5% chance of making a type I error.
105
\_\_\_ is the probability of committing a type II error .Type II error occurs when researchers fail to reject the null hypothesis when it is truly false.
β
\*if β is set at 0.2, the power will be (1 – β) = 80%; there will be an 80% chance of rejecting the null hypothesis when it is truly false (BAD).
106
Case-Control compares
Risk Factor frequency of effects
107
Cross sectional compares
disease prevelance
108
Retrospective cohort uses past records to compare
disease incidence
109
\_\_\_\_ studies are organized by selecting a group of individuals, determining their exposure status, and then following them over time for development of the disease of interest.
Prospective cohort
110
The **accuracy** of screening or diagnostic tests is quantified by the **area under the ROC curve (AUC)**. The more accurate the test is (ie, higher sensitivity and specificity), the closer the **AUC value** is to \_\_\_\_.
1.0
111
To calculate the probability of a series of independent events (ie that do not affect each other in anyway) happening all at once you must.
multiply their individual probabilities together
an independent event for example is a student taking a test. How one student does on the test does NOT affect how they other two students do.
IF the probability of one student a perfect score on the exam is 9% what is the probability that all 3 students will get a perfect score?
.09x.09x.09
112
Quick way to calculate
## Footnote
True negatives =
False positives =
True negatives = (Specificity) \* (Number of patients confirmed without the disease)
False positives = (1 − Specificity) \* (Number of patients confirmed without the disease)
113
**Intention-to-treat analysis** includes each subject in their initial randomization group even if subjects ______ or shift to a different intervention. This approach tends to provide a conservative but more valid estimate of the intervention effect in real-world scenarios (ie, clinical settings).
stop the intervention
114
A 2 × 2 table is normally used to record the presence or absence of exposure and disease in research. Rows and columns represent the different levels for each categorical (ie, exposure and disease) variable. The chi-square test for independence is used to evaluate the association between 2 ____ variables.
categorical
115
(**adverse event** **rate** in the **control group**) – (**adverse event rate** in the **treatment group**)
=
**Absolute Risk Increase**
