Core Topics in ICU

## Recently Updated Questions

* Tuesday, July 25 (2017); 2015, Paper 1 SAQs *

* Tuesday, July 25 (2017); 2012, Paper 1 SAQs *

* Tuesday, July 25 (2017); 2016, Paper 1 SAQs *

* Tuesday, July 25 (2017); 2014, Paper 2 SAQs *

* Tuesday, July 25 (2017); 2017, Paper 1 SAQs *

* Tuesday, July 25 (2017); 2015, Paper 1 SAQs *

* Monday, July 24 (2017); 2017, Paper 1 SAQs *

* Sunday, July 23 (2017); 2009, Paper 1 SAQs *

Sample size calculation; also parametric and nonparametric tests.

* Sunday, July 23 (2017); 2011, Paper 2 SAQs *

* Sunday, July 23 (2017); 2008, Paper 1 SAQs *

## Pages

The receiver operating characteristic (ROC) curve

* Tuesday, July 25 (2017); Research methods and statistics *

The ROC curve is a plot of sensitivity vs. false positive rate (1-specificity), for a range of diagnostic test results. It graphically represents the compromise between sensitivity and specificity in tests which produce results on a numerical scale. It therefore allows a graphical representation of a test's accuracy, and allows for a comparison of such tests.

At various stages, the CICM fellowship exam has expected its candidates to either define or calculate sensitivity, specificity, a predictive value or a likelihood ratio. Question 24 from the second paper of 2009 even asked about ROC curves.

Variability, dispersion and central tendency

* Tuesday, July 25 (2017); Research methods and statistics *

Quantitative data can be described by measures of central tendency, dispersion, and "shape". Central tendency is described by median, mode, and the means (there are different means- geometric and arithmetic). Dispersion is the degree to which data is distributed around this central tendency, and is represented by range, deviation, variance, standard deviation and standard error.

Critical appraisal of meta-analysis data

* Tuesday, July 25 (2017); Statistics and Interpretation of Evidence *

The idea behind these is that there may be a benefit in summing up all the evidence from several similar trials, analysing all of it together. This way, as the sample numbers grow, more subtle treatment effects may surface (because smaller trials may have been underpowered and thus many type 2 errors may have been committed).

However, the statistical analysis of the evidence in a meta-analysis of trials can occasionally produce results which contradict the actual trials. One is left wondering: which methodology is flawed? Whose statistics are faulty?

The forest plot and the box-and-whisker plot

* Tuesday, July 25 (2017); Research methods and statistics *

To quote the college, "candidates either knew this topic or knew nothing about it". We have all seen these graphs before, but when pushed to give specific definitions people tend to do poorly. Fortunately, there is not much to know.

The forest plot has appeared in many past paper questions:

Primary Exam:

Causes of shock in the trauma patient

* Monday, July 24 (2017); Trauma, Burns and Drowning *

Question 20 from the second paper of 2011 asked about the causes of shock in trauma, what distinguishing features they have, and what echocardiographic features are associated with them. The causes of shock in trauma are numerous, and the attempt to go through them systematically has led me to a tabulated form of answer, which is found in this chapter.

Parametric and non-parametric tests

* Sunday, July 23 (2017); Research methods and statistics *

Parametric and nonparametric are two broad classifications of statistical procedures. According to Hoskin (2012), *“A precise and universally acceptable definition of the term ‘nonparametric’ is not presently available". *It is generally held that it is easier to show examples of parametric and nonparametric statistical procedures than it is to define the terms.

* Sunday, July 23 (2017); Research methods and statistics *

This chapter answers parts from Section A of thePrimary Syllabus, even though study power is not specifically mentioned in any of the "abilities" there.* * This topic was examined in Question 19 from the second paper of 2011.

Bias, types of error and confounding factors

* Sunday, July 23 (2017); Research methods and statistics *

This chapter answers parts from Section A(d) of thePrimary Syllabus, *"Describe bias, types of error, confounding factors and sample size calculations, and the factors that influence them".* This topic was examined only once in Question 19&nb

Advantages and disadvantages of randomised control study design

* Sunday, July 23 (2017); Research methods and statistics *

This topic has come up in Question 8(p.2) from the first paper of 2008 and the identical Question 6 from the first paper of 2014.