60% phlebitis in one group
75 % in the other
what is the absolute risk reduction?
Relative risk reduction?
Number needed to treat???
positive likelihood ratio?
negative likelihood ratio?
in a study where 500 patients with thyroid cancer 800 patients with no thyroid cancer
what is the positive likelihod ratio associated with a serum midkine level of over 320.5. ??
note at this level, this included 375 of patients thyroid cancer testing positive and 120 patients without thyroid cancer.
+ve LR = probability diseased patient positive/probability of non diseased person testing positive
positive ratio, positive ratio, diseased, non diseased!!
-ve LR = probability of diseased patient negative / pobability of non diseased patient negative
negative, negative, diseased, non diseased
probability positive in diseased = 375/500 = 0.75
probability positive in non diseased = 120/800 = 0.15
+veLR = 0.75/0.15 = 5
The negative predicitive value equation?
positive prediictive value?
if the NPV in population A is 98% and 85% in population B for alzheimers what does this mean?
NPV = probabilty truly dont have disease given a negative results = TN/TN+FN
PPV = probabilty you have the disease, given a positive results = TP/TP+FP
only gives information on disease prevalence. as (p)revalence increases, PPV increases and the opposite for NPV. that means population A has a low disease prevalence and so the proportion of patients without alzheimers disease is higher in population A!!!
NPV and PPV doesnt give any info on sensitivty and specificity
study to determine risk factors for multidrug resistant TB
identify patients with this and patients with sensitive TB and look through records to identify risk factors for multi drug resistant TB such as HIV
then compare frequency of these risk factors amongst both groups
type of study?
case control!! - these are retrospective studies that start with the outcome/disease and non diseased groups, then look back to determine the risk factors. compare disease frequency
NOT retrospective cohort as you identify the risk first eg HIV and then look to see if they developed resistant TB. compare disease incidence
prospective cohort = risk factor, group without risk factor -> incidence
cross sectional = risk factor, group without risk factor -> prevalance
Odds ratio>1 = increased risk from exposure
if confidence interval includes 1. (ONE) = statistically insignificant
compared to normal pregnancy, in a patient with ehlers dahnlos, if the Odds ratio is 3.5 for an amniotomy, confidence interval 2-6.2
what does this mean?
change = (3.5 - 1)/1 = 2.5 = 250% increased odds of amniotomy
people with heart failure are divided into 2 qualitative/ categorical groups bases on type of care ((telemonitoring v usual care)
end point measured is death or readmission % (qualitative) in each roup
what statistical test can be used for this?
other examples of qualitiative variables = blood type
quantitative = temp, glucose level
chi square test!!!
evaluates relationship between 2 categorical variables and a depended categorical variable (outcome) is measured. requires a categorical variable used to divide participants into 2 separate groups contrast to t test where groups already independent
NOT anova as it compares the mean of a quantitative variable in at least 3 groups. eg study comparing serum ferritin levels in children, adolescents and adults
NOT correlation analysis as is used for 2 quantitative variables, eg hours of sleep and irritability score
NOT meta-analysis as it is a quantitative statistical technique used to combine and analyse data form several studies
NOT 2 sample T test as it compares the mean of quantitative variable between 2 independent groups eg comparing serum ferritin levels between males and females
effect of concentration of CSF tau on brain atrophy (measured quantitatively using 2 outcomes = ventricular volume, and total brain volume)
what type of test?
linear regression!
testing effect of >/=1 explanatory variable (quant or qual) on 1 quantitative dependent variable (outcome)
NOT anova! as it is used to compare MEANNN of a quantitative dependent variable in several independent qualitative groups eg mean serum triglyceride levels in patients with low normal or high serum uric acid levels
population level data eg county, state, country = ecological study
if risk of hyperkalemia with follow up diuretic use =
hazard ratio = 0.41 and p value = 0.006
vs risk of hyperkalemia with follow up serum potassium level of 4.7 =
hazard ratio = 7.25 p value = 0.007
then the latter significantly increases the chances of hyperkalemia!!. look at the numbers not just the p values
review confidence intervals as well!!
you are randomising to 3 different interventions/multiple (metoprolol, ramipril, amlodipine)
and then you are studing at least 2 variables. eg 2 different BP outcomes
what type of RCT study is this?
Factorial design!!!
not crossover study = one group gets a treatment, another group randomised to a separate one, and then they switch treatments/interventions
not parallell study = intervention one group, intervention/placebo the other. no multiple variables examined
not cluster analysis
carbonated beverages consumed in each household (risk factor)
and estimated PREVALENCE of obesity in the household (outcome)
most likely study?
observational study!!! -> specifically a cross sectional study, which involves looking at data at a specific snapshot in time.
other observational studies = cohort, case control, case
contrast experimental studies which assess impact of an intervention. eg RCTS
learn the diffeent types of bias. on your phone! eg berkson bias, prevalence/neyman bias
If 95% CI for mean difference includes 0 = no significant difference
If 95% CI for relative risk or odds ratio includes 1 = no significant difference.
participants change behaviour upon awareness of being observed. what type of bias is this?
hawethorne bias!!
how do you calculate relative risk?
how do you calculate relative risk reduction?
absolute risk reduction?
NNT?
high yield!!
RR = rate treatment/rate control
RRR = 1 - RR
ARR = control ratee - treatment ratee
NNT = 1/ARR
rate indicates you are using proportions
traditional schedule = 1,200 patient days, 60 non intercepted serious errors
intervention schedule = 1,250 patient days, 25 non intercepted serious errors
approximate proportion of decreased risk in non intercepted serious errors per patient day among interns in intervention schedule vs those in traditional schedule
RRR = control rate- treatment rate/ control rate
60/1200 = 0.05
25/1250 = 0.02
(0.05 -0.02)/0.05
= 0.6!!!!
a study comparing medical therapy alone to medical therapy + CABG intervention
at the end some people in the medical therapy group underwent CABG (they had deteriorated to that point) and they want to add this to the group that had medical therapy + CABG for analysis
what type of bias would this introduce?
selection bias!!!
(when the treatment regimen selected for a patient depends on the severity of their disease = a type of selection bias called succeptibility bias!!! )
counfounding by indication may occur!!
surgery patients in medical therapy group may have had underlying confounders causing their deterioration and need for surgery
sometimes in an abstract, if they
put *** next to values and the bottom says **p<0.01, this means that the values with the stars are the only statistically significant values!!!
blinding is not always possible in RCTs!! such as diet interventions and surgeries intervention, in these cases they will not introduce bias/study results should not be avoided because of bias
a confidence interval of 95% captures 95% of the distribution and has an alpha significance level of 1-0.95 = 0.05
confidence interval of 99% captures 99% of the distribution and has an alpha significance level of 1-0.99 = 0.01
so going from 95% CI to 99% CI = larger or wider data set
if a question says mean is 107 grams with a confidence interval 95% of 104-110, what is the most likley lower and upper limits for a confidence interval of 99% -> the answer would be the one with a wider lowe and upper limit eg 102 - 112
equally CI of 90% = alpha of <0.1
an association between a risk factor and an outcome is more likely to be causal if its strength increases as as the exposure level increases
eg higher reduction in hba1c the more exercise you do.
likelihood of a causal relationship is not greatly increased because some confounders are controlled for because some may not have been controlled for!
increasing (P) revalence increases (P) PV. but decreases NPV
oppositive effect when you decrease prevalence
CAREFUL!! abstract with 3 pages with go to page 2 and go to page 3 yellow button
NNT?
1/ARR