Fellowship of the Royal College of Anaesthetists (FRCA) Physics, Clinical Measurement and Statistics Flashcards

24 sample cards from the Physics, Clinical Measurement and Statistics deck

Sampled from the end of the deck, so these are different cards from the ones shown on the syllabus page.

1. Classify the Mapleson breathing systems and state the most efficient for spontaneous versus controlled ventilation.

   Mapleson A, B, C, D, E, F. For spontaneous ventilation the Mapleson A (Magill) is most efficient (fresh gas flow ~equal to minute ventilation). For controlled ventilation the Mapleson D (and its Bain coaxial modification) is most efficient. Mapleson E/F (Ayre's T-piece/Jackson-Rees) are used in paediatrics.

2. What fresh gas flow is required for a Mapleson A during spontaneous breathing and a Mapleson D during controlled ventilation?

   Mapleson A (spontaneous): FGF ~70-100 mL/kg/min, approximately equal to alveolar minute ventilation. Mapleson D/Bain (controlled): FGF ~70 mL/kg/min (some quote 100 mL/kg/min) to prevent rebreathing. The Bain is a coaxial D system.

3. Describe how a circle breathing system works and the function of soda lime.

   A circle system recirculates gas through inspiratory and expiratory limbs with unidirectional valves, a reservoir bag, APL valve and a $\ce{CO2}$ absorber, allowing low fresh gas flows. Soda lime (~94% $\ce{Ca(OH)2}$, with $\ce{NaOH}$ and indicator) absorbs $\ce{CO2}$: $\ce{CO2 + Ca(OH)2 -> CaCO3 + H2O + heat}$, and the indicator changes colour when exhausted.

4. Classify ventilators by their cycling mechanism.

   Ventilators are classified by the variable that ends inspiration (cycling): volume-cycled (stops at set volume), pressure-cycled (stops at set pressure), time-cycled (stops after set time), and flow-cycled (stops when flow falls to a threshold, e.g. pressure support). They are also classed by power source and by minute volume divider vs bag-in-bottle design.

5. What are the hazards of theatre pollution by anaesthetic gases and how does active scavenging work?

   Chronic exposure concerns: possible teratogenicity, fertility effects, and N2O's effect on vitamin B12/methionine synthase; environmental greenhouse effect. Active scavenging uses a collecting valve, transfer tubing, a receiving system with positive and negative pressure relief, and a disposal route (e.g. vacuum) to remove waste gas. UK COSHH limits: N2O 100 ppm, isoflurane 50 ppm, sevoflurane 20 ppm (8-hr TWA).

6. Compare cleaning, disinfection and sterilisation.

   Cleaning: physical removal of visible contamination/organic matter (prerequisite). Disinfection: reduction of microorganisms to a safe level but not all spores (e.g. chemical, pasteurisation). Sterilisation: complete destruction of all microorganisms including spores and prions (e.g. autoclave, ethylene oxide, gamma irradiation).

7. Describe autoclave sterilisation parameters and when ethylene oxide or single-use devices are preferred.

   Autoclave (steam under pressure): e.g. $134\,^{\circ}\text{C}$ at 2 bar for 3 min, or $121\,^{\circ}\text{C}$ at 1 bar for 15 min. Ethylene oxide or low-temperature methods (e.g. gas plasma) are used for heat-sensitive equipment. Single-use devices are used where reprocessing is unreliable or to prevent prion (vCJD) transmission, since prions resist standard autoclaving.

8. Classify types of data: nominal, ordinal, interval and ratio.

   Nominal: categories with no order (e.g. blood group). Ordinal: ordered categories without consistent intervals (e.g. ASA grade, pain score). Interval: ordered with equal intervals but no true zero (e.g. °C). Ratio: equal intervals with an absolute zero (e.g. kelvin, weight, height).

9. Define mean, median and mode and state which is best for skewed data.

   Mean: arithmetic average (sum/n). Median: middle value when data are ranked. Mode: most frequent value. For skewed (non-normal) data the median is the most representative measure of central tendency because the mean is distorted by outliers.

10. Define standard deviation, variance and standard error of the mean, including the SEM formula.

    Variance: mean of the squared deviations from the mean ($\sigma^{2}$). Standard deviation: $\sigma = \sqrt{\text{variance}}$, describing spread of the data. Standard error of the mean: $$SEM = \frac{\sigma}{\sqrt{n}}$$ describing the precision of the estimate of the population mean.

11. Describe the properties of a normal (Gaussian) distribution including the empirical rule.

    Symmetrical bell shape where mean = median = mode. ~68% of values lie within $\pm 1$ SD, ~95% within $\pm 1.96$ SD (commonly stated $\pm 2$ SD), and ~99.7% within $\pm 3$ SD of the mean.

12. Define the null hypothesis, Type I and Type II errors.

    Null hypothesis ($H_0$): there is no difference/effect. Type I error ($\alpha$): rejecting a true null hypothesis (false positive); conventionally $\alpha = 0.05$. Type II error ($\beta$): failing to reject a false null hypothesis (false negative); conventionally $\beta = 0.2$.

13. Define statistical power and state how it is calculated and increased.

    Power $= 1 - \beta$, the probability of correctly detecting a real effect (rejecting a false null), conventionally $\geq 0.8$ (80%). Power is increased by a larger sample size, a larger effect size, lower variability, and a higher (less strict) $\alpha$.

14. Define the p-value and the 95% confidence interval.

    P-value: the probability of obtaining the observed result (or more extreme) if the null hypothesis were true; $p<0.05$ is conventionally 'significant'. 95% confidence interval: the range within which the true population value lies with 95% certainty; if it crosses the line of no effect (0 for differences, 1 for ratios) the result is non-significant.

15. Match the correct parametric test to the comparison: two groups, more than two groups, and correlation.

    Two independent groups (parametric): unpaired (Student's) t-test. Two paired measurements: paired t-test. Three or more groups: ANOVA (analysis of variance). Linear relationship between two continuous variables: Pearson correlation coefficient and linear regression.

16. Name the non-parametric equivalents of the unpaired t-test, paired t-test, ANOVA and Pearson correlation.

    Unpaired t-test → Mann-Whitney U test. Paired t-test → Wilcoxon signed-rank test. One-way ANOVA → Kruskal-Wallis test. Pearson correlation → Spearman's rank correlation. Use non-parametric tests for ordinal or non-normally distributed data.

17. When is the chi-squared test used and what does it assess?

    The chi-squared ($\chi^2$) test is used for categorical (nominal) data to assess whether observed frequencies differ from expected frequencies, i.e. association between categorical variables in a contingency table. Fisher's exact test is used instead when expected cell counts are small (<5).

18. Define sensitivity and specificity with their formulas.

    Sensitivity = true positives correctly identified $= \frac{TP}{TP+FN}$ (ability to detect disease; rules out when negative — SnNout). Specificity = true negatives correctly identified $= \frac{TN}{TN+FP}$ (ability to exclude disease; rules in when positive — SpPin).

19. Define positive and negative predictive value and how they relate to prevalence.

    Positive predictive value $PPV = \frac{TP}{TP+FP}$ (probability disease is present given a positive test). Negative predictive value $NPV = \frac{TN}{TN+FN}$. Unlike sensitivity/specificity, predictive values depend on disease prevalence: PPV falls as prevalence falls.

20. Define the likelihood ratio and what an ROC curve represents.

    Positive likelihood ratio $LR^{+} = \frac{\text{sensitivity}}{1-\text{specificity}}$; negative $LR^{-} = \frac{1-\text{sensitivity}}{\text{specificity}}$. A ROC (receiver operating characteristic) curve plots sensitivity (true positive rate) against 1 − specificity (false positive rate) at various thresholds; the area under the curve (AUC) reflects overall test accuracy (0.5 = useless, 1.0 = perfect).

21. Rank the hierarchy of clinical evidence from strongest to weakest.

    From strongest: systematic reviews/meta-analyses of RCTs → randomised controlled trials → cohort studies → case-control studies → cross-sectional/case series → case reports → expert opinion. Higher levels have lower risk of bias.

22. Define randomisation, blinding and allocation concealment in trial design.

    Randomisation: assigning participants to groups by chance to balance confounders. Allocation concealment: hiding the upcoming assignment from those enrolling, to prevent selection bias. Blinding: keeping participants (single), and also investigators/assessors (double) unaware of group allocation to prevent performance and detection bias.

23. Define number needed to treat (NNT), absolute risk reduction and relative risk.

    Absolute risk reduction $ARR = \text{risk}_{control} - \text{risk}_{treatment}$. Number needed to treat $NNT = \frac{1}{ARR}$ (patients treated to prevent one event). Relative risk $RR = \frac{\text{risk}_{treatment}}{\text{risk}_{control}}$; relative risk reduction $RRR = 1 - RR$.

24. Distinguish an odds ratio from a relative risk and state which study design uses each.

    Relative risk (RR): ratio of incidence in exposed vs unexposed — used in cohort/RCTs where incidence is known. Odds ratio (OR): ratio of odds of exposure in cases vs controls — used in case-control studies where incidence cannot be calculated. OR approximates RR when the outcome is rare.

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