🏠/MRCOG Part 1 — Study Book/Appendices/Mock Exams/Mock Exam 11

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Epidemiology (Questions 1–35)
This is a case-control study because it starts by selecting participants based on disease status (pre-eclampsia vs. no pre-eclampsia) and looks backward to assess exposure (BMI and smoking history). Cohort studies follow people forward from exposure to outcome. Cross-sectional studies measure exposure and outcome simultaneously. RCTs involve random allocation of an intervention.
In a cohort study with complete follow-up, the relative risk (risk ratio) is the most direct measure of association because we can calculate the incidence of macrosomia in exposed and unexposed groups directly. Odds ratio is the natural measure for case-control studies. Number needed to treat applies to interventional studies.
ARR = risk in control group − risk in treatment group = 25% − 15% = 10%. This represents the absolute difference in risk attributable to the intervention. The relative risk reduction would be (25−15)/25 = 40%, but the question specifically asks for absolute risk reduction.
NNT = 1 / ARR = 1 / 0.10 = 10. This means 10 women need to be treated with the tocolytic drug to prevent one additional case of preterm birth before 34 weeks. NNT is always rounded up to the nearest whole number.
Using a 2×2 table with 1000 women: 100 have GDM (prevalence 10%), 900 do not. True positives = 85% × 100 = 85. False positives = 10% × 900 = 90. PPV = TP / (TP + FP) = 85 / (85 + 90) = 85/175 = 48.6%. PPV depends heavily on disease prevalence.
Selection based on outcome status is characteristic of case-control studies, not RCTs. In an RCT, participants are selected before outcomes occur and are allocated to groups based on randomisation. Blinding, intention-to-treat analysis, and control groups are all key features of well-designed RCTs.
In cross-sectional studies, the prevalence ratio (prevalence in exposed / prevalence in unexposed) is the most appropriate measure. All participants are assessed simultaneously, so incidence cannot be calculated. Odds ratio can also be used but the prevalence ratio is more interpretable for common outcomes.
An odds ratio of 0.60 means the intervention reduces the odds of the outcome by 40% (1 − 0.60 = 0.40). The 95% confidence interval (0.50–0.72) does not cross 1, indicating statistical significance at p < 0.05. The reduction is in odds, not necessarily risk, though for rare outcomes they approximate each other.
The odds ratio of 1.8 suggests that women with ovarian cancer have 1.8 times the odds of talc use compared to controls. However, the 95% confidence interval crosses 1 (0.95 to 3.41), indicating this finding is not statistically significant at the conventional p < 0.05 level. OR approximates RR only when the disease is rare.
Effective screening requires a disease with a detectable preclinical phase during which intervention improves outcomes, plus an acceptable, accurate test and effective treatment. If a disease has very low prevalence, PPV will be poor. A balance of sensitivity and specificity is needed; extreme imbalance in either direction is problematic.
Lead-time bias occurs when screening detects disease earlier, so the interval from diagnosis to death appears longer even if the actual time of death is unchanged. This creates a spurious survival advantage. Length-time bias (slow-growing tumours detected preferentially) and selection bias are other important biases in screening studies.
The AUC represents the probability that the test will rank a randomly chosen diseased patient higher than a randomly chosen non-diseased patient. An AUC of 0.92 indicates excellent discriminatory ability (1.0 = perfect, 0.5 = no better than chance). AUC does not directly give sensitivity, specificity, PPV, or accuracy at any single threshold.
Socioeconomic status (SES) is a common confounder because it is associated with both smoking behaviour (exposure) and placental abruption (outcome) through factors like nutrition, stress, and access to antenatal care. SES is not on the causal pathway. Gestational age and birth weight are more likely intermediates or outcomes rather than confounders.
Randomisation is the gold standard for reducing confounding, but it is only possible in experimental studies (RCTs), not observational studies. Stratification, multivariable regression, matching, and restriction are all valid methods to address confounding in observational study designs.
In a 2×2 table where a = TP, b = FP, c = FN, d = TN, the false positive rate (1 − specificity) = FP / (FP + TN) = b / (b + d). It represents the proportion of disease-negative individuals who test positive. Specificity = d / (b + d) = TN / (FP + TN).
GRADE (Grading of Recommendations, Assessment, Development and Evaluations) assesses: risk of bias, inconsistency, indirectness, imprecision (not sample size calculation directly), publication bias, large effect size, dose-response gradient, and plausible confounding. A study's original sample size calculation is not part of the GRADE assessment framework.
A case-control study is efficient for rare outcomes because it starts with cases (those with the outcome) and selects controls without the outcome. For a rare outcome, a cohort study would need to follow an impractically large number of participants to observe enough events. RCTs may be unethical if the exposure is potentially harmful.
This is a prospective cohort study because participants are enrolled before the outcome develops, and they are followed forward in time. The exposure (vitamin D level) is measured at baseline, and the outcome (gestational hypertension) occurs later. The term "prospective" refers to the temporal direction of data collection relative to the study start.
LR+ = sensitivity / (1 − specificity) = probability of positive test in diseased / probability of positive test in non-diseased. LR+ > 10 generates large shifts from pre-test to post-test probability. LR− = (1 − sensitivity) / specificity. Likelihood ratios are independent of disease prevalence.
A funnel plot plots effect size against study precision (usually standard error). Asymmetry in the funnel plot suggests publication bias, typically because smaller studies with null or negative results are less likely to be published. Forest plots display individual study results and pooled estimates. Box plots show data distribution.
Intention-to-treat (ITT) analysis preserves the benefits of randomisation by analysing all participants according to their original group allocation, regardless of whether they completed the treatment, crossed over, or withdrew. ITT provides a pragmatic estimate of treatment effect in real-world settings and is the preferred primary analysis in superiority trials.
With very low prevalence, even a test with excellent specificity will generate many false positives relative to true positives. For 100,000 people: 100 have the disease (0.1%), 99,900 do not. With 99% specificity: 999 false positives (1% of 99,900). True positives depend on sensitivity but even with 100% sensitivity, only 100 true positives. So false positives outnumber true positives ~10:1.
Obesity is a modifiable risk factor. Age, previous VTE, thrombophilia, and parity are non-modifiable. Modifiable factors can potentially be changed through intervention (weight loss, though this is challenging in pregnancy). Identifying modifiable risk factors is important for prevention strategies.
The p-value is the probability of obtaining results at least as extreme as those observed, assuming the null hypothesis is true. It is NOT the probability that the null hypothesis is true. A p-value of 0.04 means there is a 4% chance of seeing this difference (or greater) if there is truly no difference between groups.
Differential loss to follow-up (attrition) introduces selection bias because the participants who remain in each group may differ systematically. If women who develop breast cancer are more likely to be lost from the exposed group, the association may be underestimated. Recall bias is specific to case-control studies. Confounding by indication applies to treatment comparisons.
PPV is strongly influenced by disease prevalence. For a given sensitivity and specificity, PPV increases as prevalence increases. Increasing sensitivity (or lowering the threshold) would increase true positives but also increase false positives, potentially worsening PPV. Improving specificity reduces false positives, which does improve PPV, but increasing prevalence has the greatest impact.
Matching in case-control studies controls for potential confounders (e.g., age, parity) by ensuring cases and controls are similar on these variables. However, matching factors cannot then be analysed as exposures. Matched studies require conditional logistic regression or McNemar's test for analysis. Matching does not allow direct RR calculation.
A fixed-effects model assumes that the true treatment effect is identical across all studies, and observed differences are due solely to random sampling error. A random-effects model, conversely, allows the true effect to vary between studies (between-study heterogeneity) and incorporates this into the analysis.
Coverage (or uptake) is the proportion of the eligible target population that actually receives the screening test. It is a key performance indicator for screening programmes — even a highly accurate test will have limited population impact if coverage is low. The WHO target for cervical screening coverage is typically ≥70%.
Nulliparity and alcohol intake are associated with both the exposure (induced abortion) and the outcome (breast cancer), and are not on the causal pathway. They are confounders. If these factors are not adjusted for, the observed association may be partially or entirely due to confounding rather than a direct causal effect.
NPV increases as prevalence decreases. NPV = TN / (TN + FN). When disease is less common, true negatives form a larger proportion of test-negative results. At 20% prevalence, NPV is 97%. At 5% prevalence (a rarer disease), more people without disease will be test-negative, so NPV will be higher (>97%).
Recall bias is a particular problem in case-control studies because cases (who have the outcome) may remember past exposures differently from controls (who do not have the outcome). For example, mothers of children with congenital anomalies may search their memory more thoroughly for potential causes than mothers of healthy children.
The point estimate (RR 0.85) suggests a 15% reduction in risk, but the 95% confidence interval (0.70–1.03) crosses 1, meaning the result is not statistically significant at p < 0.05. It would be incorrect to conclude the treatment is effective or has no effect — the study is inconclusive, possibly due to insufficient power. The trend is toward benefit.
NNH = 1 / attributable risk (absolute risk increase). An NNH of 20 means that for every 20 patients exposed to the medication, one additional case of nausea occurs that would not have occurred with placebo. Smaller NNH values indicate greater harm. NNH is the harmful analogue of number needed to treat (NNT).
The key limitation of cross-sectional studies is that exposure and outcome are measured simultaneously, so the temporal sequence cannot be established. It is unclear whether stress preceded miscarriage (causal direction) or whether experiencing a miscarriage caused higher stress levels (reverse causation). Cross-sectional studies can calculate prevalence efficiently.
Statistics (Questions 36–70)
In a negatively skewed (left-skewed) distribution, the mean is less than the median, which is less than the mode (mean < median < mode). The tail is on the left side — a few lower birth weights pull the mean downward. In positive skew, mean > median > mode. In a normal distribution, all three are approximately equal.
Standard deviation is the square root of the variance and measures the spread of data around the mean. It quantifies the average (root-mean-squared) distance of individual observations from the mean. For normally distributed data, approximately 68% of values lie within ±1 SD, 95% within ±2 SD, and 99.7% within ±3 SD.
One-way ANOVA (analysis of variance) compares means across three or more independent groups. An independent t-test is for comparing two groups only. The chi-square test is for categorical data. Mann-Whitney U is a non-parametric alternative for two groups. Ferritin levels are continuous data, and with three trimester groups, ANOVA is appropriate.
The Kruskal-Wallis test is the non-parametric equivalent of one-way ANOVA. It tests whether samples originate from the same distribution without assuming normality or equal variances. The Friedman test is the non-parametric equivalent for repeated-measures (paired) ANOVA. McNemar's test is for paired categorical data.
The chi-square test of independence assesses whether there is an association between two categorical variables. Here, both parity (2 categories) and mode of delivery (3 categories) are categorical. The test compares observed frequencies with expected frequencies under the null hypothesis of no association.
Degrees of freedom for a chi-square test of independence = (rows − 1) × (columns − 1) = (3 − 1) × (2 − 1) = 2 × 1 = 2. This reflects the number of cell frequencies that are free to vary given the fixed row and column totals.
The Wilcoxon signed-rank test is the non-parametric equivalent of the paired t-test for comparing two related samples (e.g., before-and-after measurements on the same subjects). Mann-Whitney U corresponds to the independent samples t-test. Spearman's rank correlation assesses monotonic relationships between variables.
The 95% confidence interval includes zero, meaning the null hypothesis (no difference) cannot be rejected at α = 0.05. The difference is not statistically significant. The correct interpretation of a CI is: if repeated samples were taken and CIs calculated, 95% of those intervals would contain the true population parameter.
An r-value of 0.45 indicates a moderate positive linear relationship — as BMI increases, birth weight tends to increase. The coefficient of determination (r²) = 0.2025, meaning approximately 20% (not 45%) of the variation in birth weight is explained by BMI. Correlation does not imply causation.
A Type I error (α or false positive) is rejecting a true null hypothesis — concluding there is a difference when none exists. The significance level α (conventionally 0.05) is the maximum acceptable probability of a Type I error. Type II error (β or false negative) is failing to reject a false null hypothesis.
Power = 1 − β = probability of correctly rejecting a false null hypothesis (true positive). Power depends on: sample size, effect size, significance level (α), and variability of the outcome. Studies are typically designed to achieve at least 80% power. Low power reduces the chance of detecting a true effect.
Apgar scores are ordinal data (ordered categories), not true continuous data. The Mann-Whitney U test is appropriate for comparing two independent groups on an ordinal outcome. It does not require normality assumptions. The t-test assumes continuous, normally distributed data.
Kaplan-Meier analysis estimates the survival function (probability of surviving beyond each time point) while accounting for censored data (participants lost to follow-up or event-free at study end). It generates a step-function survival curve. The log-rank test compares survival curves between groups. Cox regression provides hazard ratios.
The log-rank test compares the entire survival experience (Kaplan-Meier curves) between groups, testing the null hypothesis that there is no difference in survival. It is a non-parametric test that gives equal weight to all time points. It does not provide a hazard ratio — that requires Cox proportional hazards regression.
Cox regression models time-to-event data and produces hazard ratios. The hazard ratio is the ratio of the instantaneous event rates between groups, assumed to be constant over time (proportional hazards assumption). It is analogous to relative risk but accounts for the timing of events and censoring.
The IQR (Q3 − Q1) is a robust measure of spread that is not affected by extreme values or skewness, unlike the standard deviation which is sensitive to outliers. When data are skewed, the median and IQR provide a better summary than the mean and standard deviation, which assume normality.
An r-value of −0.85 indicates a strong negative linear correlation — as maternal age increases, fertility treatment success tends to decrease. The closer r is to −1 or +1, the stronger the linear relationship. r² = 0.7225, meaning 72% of the variation in success is explained by age.
R² quantifies the goodness-of-fit of a regression model — it is the proportion of total variability in the outcome that is accounted for by the predictor variables. R² ranges from 0 (no predictive value) to 1 (perfect prediction). In simple linear regression, R² equals the square of the Pearson correlation coefficient (r²).
Multiple logistic regression is appropriate when the outcome is binary (preterm birth: yes/no) and there are multiple predictors (age, BMI, smoking). It models the log-odds of the outcome as a linear function of the predictors and provides adjusted odds ratios for each predictor. Simple linear/logistic regression handles only one predictor.
SEM = standard deviation / √(sample size). The SEM quantifies the precision of the sample mean as an estimate of the population mean. As sample size increases, the SEM decreases, reflecting more precise estimation. SEM is always smaller than SD because it measures variability of the sampling distribution, not the data itself.
A 99% CI provides more confidence (99% vs. 95%) that the interval contains the true population parameter. To achieve higher confidence, the interval must be wider, using a larger critical value (e.g., z = 2.576 vs. z = 1.96 for large samples). The trade-off is precision for confidence.
The paired t-test requires that the differences between paired observations (post-treatment minus pre-treatment) are approximately normally distributed. This is the normality assumption on the differences. Independence between pairs is assumed by design. Equal variances (homoscedasticity) is an assumption of the independent t-test, not the paired version.
Fisher's exact test calculates the exact probability of the observed contingency table under the null hypothesis and does not rely on large-sample approximations. It is recommended when expected frequencies in any cell are less than 5, as the chi-square approximation becomes unreliable in such cases. It can be computationally intensive for large tables.
The median is resistant to outliers and skewness because it depends only on the middle value(s) of the ordered data. The mean is sensitive to extreme values — a single outlier can substantially shift the mean. For symmetric distributions without outliers, the mean and median are approximately equal.
When multiple hypothesis tests are performed, the probability of at least one false positive (Type I error) increases. With 20 independent tests at α = 0.05, the familywise error rate = 1 − (0.95)²⁰ ≈ 64%. Multiple comparison corrections (Bonferroni, Holm-Bonferroni, false discovery rate) should be applied.
A Bland-Altman plot shows the difference between two measurement methods against their mean (average). The mean difference and limits of agreement (mean ± 1.96 SD of differences) are plotted. If the differences are within clinically acceptable limits, the methods can be considered interchangeable. This assesses agreement, not correlation.
Sensitivity analysis tests whether the conclusions of a study change under different analytical scenarios — e.g., different methods of handling missing data, different model specifications, or excluding certain participants. Robust conclusions that persist across sensitivity analyses are more credible.
Logarithmic transformation is commonly applied to positively skewed data (e.g., hormone levels, antibody titres, length of stay). It compresses the right tail and makes the distribution more symmetric, often approximately normal. This satisfies assumptions for parametric tests. The choice of transformation depends on the nature of the skewness.
The null hypothesis for a chi-square test of independence is that there is no association between the two categorical variables — i.e., they are independent. The alternative hypothesis is that the variables are associated (dependent). A small p-value leads to rejection of independence.
The independent samples t-test (two-sample t-test) compares the means of a continuous outcome between two independent groups when the data are approximately normally distributed. The data are normally distributed (satisfying the parametric assumption), and the groups are independent (not paired), making the t-test appropriate.
10.5 g/dL is 1 SD below the mean (12.0 − 1.5) and 13.5 g/dL is 1 SD above the mean (12.0 + 1.5). In a normal distribution, approximately 68% of values lie within ±1 SD of the mean. 68% of 500 = 340 women. Approximately 95% lie within ±2 SD, and 99.7% within ±3 SD.
The I² statistic describes the percentage of total variation across studies that is due to true heterogeneity rather than chance. I² values of 25%, 50%, and 75% are considered low, moderate, and high heterogeneity, respectively. The Q-statistic (Cochran's Q) tests for heterogeneity, but I² quantifies its magnitude. High heterogeneity may warrant a random-effects model.
Cohen's kappa measures inter-rater agreement beyond chance. κ ranges from −1 to +1. Common interpretation: ≤0 = poor, 0.01–0.20 = slight, 0.21–0.40 = fair, 0.41–0.60 = moderate, 0.61–0.80 = substantial, 0.81–0.99 = almost perfect agreement. A κ of 0.82 represents very good/substantial agreement. Note that κ can be low even with high observed agreement if prevalence is skewed.
A ceiling effect occurs when a substantial proportion of subjects achieve the maximum possible score, limiting the instrument's ability to discriminate among high performers. This reduces variability and can obscure differences between groups. Floor effect (large proportion at minimum score) is the opposite problem. Both reduce clinical utility.
An interaction occurs when the effect of one factor depends on the level of another factor. A significant Drug A × Drug B interaction means the effect of Drug A on contraction strength differs depending on whether Drug B is co-administered. In the presence of interaction, main effects must be interpreted cautiously.
Biophysics & Imaging (Questions 71–100)
Higher frequency ultrasound waves produce shorter wavelengths, which yield better axial resolution (the ability to distinguish two closely spaced structures along the beam axis). However, higher frequencies also undergo greater attenuation in tissue, so depth of penetration is reduced. Transvaginal probes typically use 5–10 MHz for detailed pelvic imaging, while abdominal probes use 2–5 MHz.
The Doppler equation: Δf = (2f₀ v cos θ) / c, where Δf is the Doppler shift, f₀ is transmitted frequency, v is blood flow velocity, θ is the angle between the ultrasound beam and the direction of blood flow, and c is the speed of sound in tissue. The cosine of the angle is critical — at 90° (perpendicular beam), cos 90° = 0, and no Doppler shift is detected.
Baseline variability is classified as: absent (undetectable), minimal (≤5 bpm), moderate (6–25 bpm), and marked (>25 bpm). Moderate variability (6–25 bpm) is normal and reassuring, indicating an intact autonomic nervous system. Absent or minimal variability with no accelerations is a non-reassuring sign requiring further assessment.
According to FIGO 2015, a suspicious (equivocal) CTG has a baseline of 150–170 bpm (or 110–150 with other concerns) plus minimal variability (3–5 bpm) or variable decelerations, but without all pathological criteria. A pathological CTG would have baseline variability <3 bpm or repeated late decelerations or sinusoidal pattern.
Late decelerations are smooth, gradual decreases in FHR (onset to nadir ≥30 seconds) where the nadir occurs after the peak of the contraction. They reflect utero-placental insufficiency — the dip in FHR is delayed relative to the contraction. They are non-reassuring and require prompt evaluation and intervention.
The BPP consists of five components, each scored 0 or 2 for a maximum of 10: (1) fetal breathing movements, (2) gross body movements, (3) fetal tone, (4) amniotic fluid volume, and (5) non-stress test (CTG reactivity). Uterine artery Doppler is not part of the standard BPP score, though it may be used separately in fetal surveillance.
A BPP of 4/10 is considered abnormal and indicates possible fetal compromise. If the oligohydramnios component is the reason for the low score (which is the most concerning because it reflects chronic hypoxia), delivery within 24 hours is typically recommended if the fetus is viable (≥34 weeks) and the cervix is favourable. Immediate delivery is indicated for scores ≤2/10.
Acoustic impedance (Z = density × speed of sound) determines how much ultrasound energy is reflected at tissue boundaries. When two tissues have very different acoustic impedances (e.g., soft tissue-bone or soft tissue-air interface), a large proportion of the ultrasound beam is reflected, creating strong echoes. This is why gel is needed to eliminate air between the transducer and skin.
T1-weighted images emphasise differences in T1 (longitudinal/spin-lattice) relaxation times between tissues. Tissues with short T1 (e.g., fat) appear bright, while tissues with long T1 (e.g., CSF, fluid) appear dark. T2-weighted images highlight differences in T2 (transverse/spin-spin) relaxation — fluids appear bright on T2. Both are used in pelvic MRI.
ALARA (As Low As Reasonably Achievable) is the guiding principle for radiation protection. It involves three strategies: time (minimising exposure time), distance (maximising distance from the source), and shielding (using barriers between the source and personnel). This applies to all diagnostic and therapeutic uses of ionising radiation.
The period of organogenesis (approximately 2–8 weeks post-conception) is when the fetus is most sensitive to radiation-induced congenital malformations. During this period, the central nervous system is especially vulnerable. The risk of radiation-induced malformations is dose-dependent, with a threshold around 50–100 mGy. After 20 weeks, the primary risk is childhood cancer induction rather than malformation.
A standard single chest X-ray delivers about 0.02 mSv (20 μSv), which is equivalent to approximately 2–3 days of background natural radiation. For comparison: a CT chest is ~8 mSv, a pelvic X-ray is ~0.7 mSv, and a mammogram is ~0.4 mSv. The risk of inducing a fatal cancer is estimated at ~5% per Sv, making the risk from a chest X-ray extremely low.
The Nyquist limit in pulsed-wave Doppler is half the pulse repetition frequency (PRF/2). Velocities above this limit cause aliasing — the Doppler waveform wraps around and appears on the opposite side of the baseline. Lowering the transducer frequency, increasing the PRF, or using continuous-wave Doppler (which has no Nyquist limit) can address this.
Variable decelerations are abrupt decreases in FHR (onset to nadir <30 seconds) that vary in timing, depth, and duration with contractions. They are caused by umbilical cord compression leading to a vagal reflex. They are the most common deceleration in labour. Early decelerations are from head compression and are benign. Late decelerations suggest placental insufficiency.
By convention (though user-selectable), flow toward the transducer is displayed in red and flow away from the transducer in blue. This is the "BART" convention (Blue Away, Red Toward). Colour intensity typically reflects mean velocity — brighter colours indicate higher velocities. Colour Doppler is angle-dependent, like all Doppler modalities.
The thermal index (TI) is an on-screen safety indicator estimating the potential for tissue temperature rise due to ultrasound absorption. TI = acoustic power / power required to raise tissue temperature by 1°C. A higher TI indicates greater heating risk. The mechanical index (MI) relates to cavitation risk. Both should be minimised using the ALARA principle, especially in obstetrics.
Gadolinium is a paramagnetic contrast agent that shortens the T1 and T2 relaxation times of nearby water protons. On T1-weighted images, gadolinium causes enhancement (increased signal) in areas of increased blood flow, vascularity, or disrupted blood-brain barrier. However, gadolinium is generally avoided in pregnancy (crosses the placenta) unless essential.
The half-value layer (HVL) is the thickness of a specified material (usually aluminium or copper) required to reduce the intensity of the X-ray beam by 50%. It is a measure of beam quality (penetrating power). Higher kVp produces a more penetrating beam with a larger HVL. HVL is used in quality assurance of X-ray equipment.
The Frank-Starling mechanism describes how increased ventricular filling (preload) stretches cardiac myocytes, increasing the force of contraction and thus stroke volume and cardiac output. This is relevant in pregnancy due to increased blood volume. The other options relate to different physiological processes in pregnancy.
Axial resolution (resolution along the beam axis) is determined by the spatial pulse length, which is related to the ultrasound frequency. Higher frequency transducers produce shorter pulses and thus better axial resolution. Lateral resolution (perpendicular to the beam axis) is determined by beam width, which is affected by focusing. Axial resolution is typically better than lateral resolution.
Fetal bradycardia is defined as a baseline heart rate below 110 bpm for ≥10 minutes. A baseline of 100 bpm is abnormal and requires assessment. Causes include: severe hypoxia, congenital heart block (associated with maternal autoimmune disease), fetal distress, or drugs (e.g., beta-blockers). Fetal tachycardia is baseline >160 bpm.
Resistive index (RI) = (peak systolic velocity − end-diastolic velocity) / peak systolic velocity. In the uterine artery, high RI in the second trimester (e.g., >0.58) with a persistent diastolic notch suggests impaired trophoblast invasion and increased risk of pre-eclampsia and fetal growth restriction. Pulsatility index (PI) = (PSV − EDV) / mean velocity.
Absent end-diastolic flow (AEDF) in the umbilical artery indicates significantly increased placental vascular resistance. It is associated with severe fetal growth restriction, hypoxia, and adverse perinatal outcomes. Reversed end-diastolic flow (REDF) is even more ominous and often triggers urgent delivery after 32–34 weeks. These findings reflect the progression of placental insufficiency.
MCA-PSV is the most sensitive non-invasive method to detect fetal anaemia, particularly in cases of red cell alloimmunisation (e.g., anti-D, anti-c, anti-Kell). With anaemia, decreased blood viscosity leads to increased cardiac output and increased flow velocity in the MCA. A PSV >1.5 multiples of the median (MoM) indicates moderate-to-severe anaemia and may trigger fetal blood sampling or intrauterine transfusion.
AFI is the sum of the deepest vertical pocket of amniotic fluid (free of umbilical cord and fetal parts) measured in each of four abdominal quadrants (using the linea nigra and umbilicus as dividing lines). Normal AFI is 8–24 cm. Oligohydramnios is AFI <5 cm (or single deepest pocket <2 cm). Polyhydramnios is AFI >24 cm (or single deepest pocket >8 cm).
The piezoelectric effect is the property of certain crystals (e.g., lead zirconate titanate) to generate an electrical voltage when mechanically deformed, and conversely to deform (vibrate) when an electrical voltage is applied. This is the fundamental principle of ultrasound transducers — they both transmit (electrical→sound) and receive (sound→electrical) ultrasound waves.
CT uses X-rays (ionising radiation) to produce cross-sectional images. Ultrasound uses high-frequency sound waves (non-ionising). MRI uses powerful magnetic fields and radiofrequency pulses (non-ionising). Both ultrasound and MRI are safe in pregnancy when used appropriately. CT is reserved for specific indications due to radiation exposure, with abdominal shielding when possible.
A sinusoidal CTG pattern is a smooth, undulating waveform with a fixed frequency of 3–5 cycles per minute, absent variability, and no accelerations. It is most commonly associated with severe fetal anaemia (e.g., from haemolytic disease, fetomaternal haemorrhage, or twin-to-twin transfusion syndrome). It can also be seen with severe fetal hypoxia and is a pathological pattern requiring urgent evaluation.
Attenuation (reduction of sound wave intensity as it travels through tissue) is caused primarily by absorption (conversion of acoustic energy to heat) and scattering (redirection of sound waves in multiple directions). The attenuation coefficient in soft tissue is approximately 0.5–0.7 dB/cm/MHz, meaning higher frequencies attenuate more rapidly. This is why deep structures require lower frequencies.
A reactive NST (reassuring) requires at least 2 accelerations of ≥15 bpm above baseline lasting ≥15 seconds from 32 weeks' gestation. Before 32 weeks, criteria are often relaxed to 10 bpm × 10 seconds due to fetal neurological immaturity. A non-reactive NST requires further evaluation (BPP or contraction stress test). Fetal heart rate accelerations are a sign of an intact, well-oxygenated fetal autonomic nervous system.
End of Mock Exam 11

Mock Exam 11

Mock Exam 11 — Epidemiology, Statistics & Biophysics/Imaging

100 MRCOG Part 1 Single Best Answer Questions

Epidemiology (Questions 1–35)

📘 Q1 (Epidemiology) — A study recruits 500 women with pre-eclampsia and 500 women without pre-eclampsia, then retrospectively examines their antenatal records for BMI and smoking history. What type of study design is this? A) Randomised controlled trial B) Cohort study C) Case-control study D) Cross-sectional study E) Ecological study

Answer: C

This is a case-control study because it starts by selecting participants based on disease status (pre-eclampsia vs. no pre-eclampsia) and looks backward to assess exposure (BMI and smoking history). Cohort studies follow people forward from exposure to outcome. Cross-sectional studies measure exposure and outcome simultaneously. RCTs involve random allocation of an intervention.

📘 Q2 (Epidemiology) — A cohort study follows 10,000 pregnant women for 9 months to determine whether gestational diabetes (exposure) is associated with macrosomia (outcome). Which measure of association is most appropriate to report? A) Odds ratio B) Relative risk C) Prevalence ratio D) Attributable risk percent E) Number needed to treat

Answer: B

In a cohort study with complete follow-up, the relative risk (risk ratio) is the most direct measure of association because we can calculate the incidence of macrosomia in exposed and unexposed groups directly. Odds ratio is the natural measure for case-control studies. Number needed to treat applies to interventional studies.

📘 Q3 (Epidemiology) — In a randomised controlled trial of a new tocolytic drug, 200 women receive the drug and 200 receive placebo. The incidence of preterm birth before 34 weeks is 15% in the drug group and 25% in the placebo group. What is the absolute risk reduction (ARR)? A) 0.4% B) 10% C) 15% D) 25% E) 40%

Answer: B

ARR = risk in control group − risk in treatment group = 25% − 15% = 10%. This represents the absolute difference in risk attributable to the intervention. The relative risk reduction would be (25−15)/25 = 40%, but the question specifically asks for absolute risk reduction.

📘 Q4 (Epidemiology) — Using the same trial data (ARR = 10%), what is the number needed to treat (NNT) to prevent one case of preterm birth before 34 weeks? A) 1 B) 4 C) 10 D) 25 E) 100

Answer: C

NNT = 1 / ARR = 1 / 0.10 = 10. This means 10 women need to be treated with the tocolytic drug to prevent one additional case of preterm birth before 34 weeks. NNT is always rounded up to the nearest whole number.

📘 Q5 (Epidemiology) — A screening test for gestational diabetes mellitus has a sensitivity of 85% and a specificity of 90%. If the prevalence of GDM in the population is 10%, what is the positive predictive value (PPV)? A) 32.1% B) 48.6% C) 55.0% D) 85.0% E) 90.0%

Answer: B

Using a 2×2 table with 1000 women: 100 have GDM (prevalence 10%), 900 do not. True positives = 85% × 100 = 85. False positives = 10% × 900 = 90. PPV = TP / (TP + FP) = 85 / (85 + 90) = 85/175 = 48.6%. PPV depends heavily on disease prevalence.

📘 Q6 (Epidemiology) — Which of the following is NOT a characteristic of a randomised controlled trial? A) Random allocation to intervention or control groups B) Blinding of participants and/or assessors C) Analysis by intention-to-treat D) Selection of participants based on outcome status E) Use of a control group

Answer: D

Selection based on outcome status is characteristic of case-control studies, not RCTs. In an RCT, participants are selected before outcomes occur and are allocated to groups based on randomisation. Blinding, intention-to-treat analysis, and control groups are all key features of well-designed RCTs.

📘 Q7 (Epidemiology) — A cross-sectional study of 2000 postpartum women finds that 35% report symptoms of depression. The researchers want to compare the prevalence of depression among women who had operative vaginal delivery versus spontaneous vaginal delivery. Which measure of association should they use? A) Relative risk B) Odds ratio C) Prevalence ratio D) Hazard ratio E) Attributable risk

Answer: C

In cross-sectional studies, the prevalence ratio (prevalence in exposed / prevalence in unexposed) is the most appropriate measure. All participants are assessed simultaneously, so incidence cannot be calculated. Odds ratio can also be used but the prevalence ratio is more interpretable for common outcomes.

📘 Q8 (Epidemiology) — A meta-analysis of 15 RCTs concludes that antenatal corticosteroids reduce neonatal respiratory distress syndrome with a pooled odds ratio of 0.60 (95% CI 0.50–0.72). Which of the following best interprets this finding? A) Corticosteroids increase the risk of RDS by 40% B) Corticosteroids reduce the odds of RDS by 40% C) The result is not statistically significant because the CI includes 1 D) The p-value is greater than 0.05 E) Corticosteroids reduce the odds of RDS by 60%

Answer: B

An odds ratio of 0.60 means the intervention reduces the odds of the outcome by 40% (1 − 0.60 = 0.40). The 95% confidence interval (0.50–0.72) does not cross 1, indicating statistical significance at p < 0.05. The reduction is in odds, not necessarily risk, though for rare outcomes they approximate each other.

📘 Q9 (Epidemiology) — A case-control study on ovarian cancer and talc use reports an odds ratio of 1.8 (95% CI 0.95–3.41). What does this mean? A) Talc use significantly increases the risk of ovarian cancer B) There is a 1.8 times higher odds of talc use among cases, but the result is not statistically significant C) The study proves talc causes ovarian cancer D) Talc is protective against ovarian cancer E) The relative risk is also 1.8

Answer: B

The odds ratio of 1.8 suggests that women with ovarian cancer have 1.8 times the odds of talc use compared to controls. However, the 95% confidence interval crosses 1 (0.95 to 3.41), indicating this finding is not statistically significant at the conventional p < 0.05 level. OR approximates RR only when the disease is rare.

📘 Q10 (Epidemiology) — In screening for cervical cancer, which characteristic would make a screening programme most effective? A) Screening a disease with very low prevalence B) Using a test with high sensitivity but low specificity C) Screening for a disease with a long preclinical detectable phase and effective treatment D) Using a test with high specificity but low sensitivity E) Screening a population where the disease is untreatable

Answer: C

Effective screening requires a disease with a detectable preclinical phase during which intervention improves outcomes, plus an acceptable, accurate test and effective treatment. If a disease has very low prevalence, PPV will be poor. A balance of sensitivity and specificity is needed; extreme imbalance in either direction is problematic.

📘 Q11 (Epidemiology) — Lead-time bias in screening studies refers to: A) Healthy participants being more likely to participate in screening B) Earlier diagnosis creating an artificial increase in survival time without prolonging life C) Screening detecting slow-growing tumours preferentially D) Over-diagnosis of clinically insignificant disease E) Systematic differences in how outcomes are assessed between screened and unscreened groups

Answer: B

Lead-time bias occurs when screening detects disease earlier, so the interval from diagnosis to death appears longer even if the actual time of death is unchanged. This creates a spurious survival advantage. Length-time bias (slow-growing tumours detected preferentially) and selection bias are other important biases in screening studies.

📘 Q12 (Epidemiology) — A new biomarker for ovarian cancer has an area under the ROC curve (AUC) of 0.92. This means: A) The test has 92% sensitivity B) The test has 92% specificity C) The test correctly classifies 92% of patients D) The test has excellent discriminatory ability E) The positive predictive value is 92%

Answer: D

The AUC represents the probability that the test will rank a randomly chosen diseased patient higher than a randomly chosen non-diseased patient. An AUC of 0.92 indicates excellent discriminatory ability (1.0 = perfect, 0.5 = no better than chance). AUC does not directly give sensitivity, specificity, PPV, or accuracy at any single threshold.

📘 Q13 (Epidemiology) — A cohort study investigating the association between maternal smoking and placental abruption reports a relative risk of 2.5 (95% CI 1.8–3.5). Which of the following confounders is most likely to be relevant in this association? A) Gestational age at delivery B) Maternal socioeconomic status C) Fetal sex D) Neonatal birth weight E) Apgar score at 5 minutes

Answer: B

Socioeconomic status (SES) is a common confounder because it is associated with both smoking behaviour (exposure) and placental abruption (outcome) through factors like nutrition, stress, and access to antenatal care. SES is not on the causal pathway. Gestational age and birth weight are more likely intermediates or outcomes rather than confounders.

📘 Q14 (Epidemiology) — To reduce the impact of confounding in an observational study, a researcher would use all of the following EXCEPT: A) Randomisation B) Stratification C) Multivariable regression D) Matching E) Restriction

Answer: A

Randomisation is the gold standard for reducing confounding, but it is only possible in experimental studies (RCTs), not observational studies. Stratification, multivariable regression, matching, and restriction are all valid methods to address confounding in observational study designs.

📘 Q15 (Epidemiology) — In a 2×2 table for a diagnostic test, the false positive rate is calculated as: A) a / (a + b) B) b / (b + d) C) d / (b + d) D) c / (a + c) E) b / (a + b)

Answer: B

In a 2×2 table where a = TP, b = FP, c = FN, d = TN, the false positive rate (1 − specificity) = FP / (FP + TN) = b / (b + d). It represents the proportion of disease-negative individuals who test positive. Specificity = d / (b + d) = TN / (FP + TN).

📘 Q16 (Epidemiology) — The GRADE system for assessing quality of evidence considers all of the following EXCEPT: A) Risk of bias B) Publication bias C) Effect size D) Sample size calculation E) Precision of estimates

Answer: D

GRADE (Grading of Recommendations, Assessment, Development and Evaluations) assesses: risk of bias, inconsistency, indirectness, imprecision (not sample size calculation directly), publication bias, large effect size, dose-response gradient, and plausible confounding. A study's original sample size calculation is not part of the GRADE assessment framework.

📘 Q17 (Epidemiology) — Which study design is most appropriate to investigate a rare adverse outcome following a common exposure in pregnancy? A) Randomised controlled trial B) Cohort study C) Case-control study D) Cross-sectional study E) Case series

Answer: C

A case-control study is efficient for rare outcomes because it starts with cases (those with the outcome) and selects controls without the outcome. For a rare outcome, a cohort study would need to follow an impractically large number of participants to observe enough events. RCTs may be unethical if the exposure is potentially harmful.

📘 Q18 (Epidemiology) — A researcher plans a study to examine the relationship between vitamin D levels at 12 weeks' gestation and subsequent development of gestational hypertension. Blood samples are taken at 12 weeks and participants are followed until delivery. This is best described as: A) Retrospective cohort study B) Prospective cohort study C) Nested case-control study D) Historical cohort study E) Ambispective cohort study

Answer: B

This is a prospective cohort study because participants are enrolled before the outcome develops, and they are followed forward in time. The exposure (vitamin D level) is measured at baseline, and the outcome (gestational hypertension) occurs later. The term "prospective" refers to the temporal direction of data collection relative to the study start.

📘 Q19 (Epidemiology) — In a diagnostic test accuracy study, the likelihood ratio positive (LR+) is calculated as: A) Sensitivity / (1 − Specificity) B) (1 − Sensitivity) / Specificity C) Sensitivity × Specificity D) (1 − Specificity) / Sensitivity E) Positive predictive value / (1 − Positive predictive value)

Answer: A

LR+ = sensitivity / (1 − specificity) = probability of positive test in diseased / probability of positive test in non-diseased. LR+ > 10 generates large shifts from pre-test to post-test probability. LR− = (1 − sensitivity) / specificity. Likelihood ratios are independent of disease prevalence.

📘 Q20 (Epidemiology) — Publication bias in systematic reviews is best detected using: A) Forest plot B) Funnel plot C) Box plot D) Kaplan-Meier plot E) ROC curve

Answer: B

A funnel plot plots effect size against study precision (usually standard error). Asymmetry in the funnel plot suggests publication bias, typically because smaller studies with null or negative results are less likely to be published. Forest plots display individual study results and pooled estimates. Box plots show data distribution.

📘 Q21 (Epidemiology) — Intention-to-treat analysis in an RCT means: A) Analysing only participants who completed the intervention as planned B) Analysing participants according to the treatment they actually received C) Analysing all participants in the groups to which they were randomised, regardless of protocol adherence D) Analysing only those who experienced the outcome of interest E) Excluding participants who withdrew consent

Answer: C

Intention-to-treat (ITT) analysis preserves the benefits of randomisation by analysing all participants according to their original group allocation, regardless of whether they completed the treatment, crossed over, or withdrew. ITT provides a pragmatic estimate of treatment effect in real-world settings and is the preferred primary analysis in superiority trials.

📘 Q22 (Epidemiology) — A test with 99% specificity is used to screen for a disease with 0.1% prevalence. The majority of positive test results will be: A) True positives B) False positives C) True negatives D) False negatives E) Equally true and false positives

Answer: B

With very low prevalence, even a test with excellent specificity will generate many false positives relative to true positives. For 100,000 people: 100 have the disease (0.1%), 99,900 do not. With 99% specificity: 999 false positives (1% of 99,900). True positives depend on sensitivity but even with 100% sensitivity, only 100 true positives. So false positives outnumber true positives ~10:1.

📘 Q23 (Epidemiology) — Which of the following is a modifiable risk factor for venous thromboembolism in pregnancy? A) Age over 35 years B) Previous VTE C) Thrombophilia D) Obesity (BMI > 30 kg/m²) E) Parity

Answer: D

Obesity is a modifiable risk factor. Age, previous VTE, thrombophilia, and parity are non-modifiable. Modifiable factors can potentially be changed through intervention (weight loss, though this is challenging in pregnancy). Identifying modifiable risk factors is important for prevention strategies.

📘 Q24 (Epidemiology) — A study reports a p-value of 0.04 when comparing mean birth weight between two groups. Which statement is correct? A) There is a 4% probability that the null hypothesis is true B) The probability of observing the data (or more extreme) if the null hypothesis is true is 4% C) There is a 96% probability that the alternative hypothesis is true D) The probability of a Type II error is 4% E) The study has 96% power

Answer: B

The p-value is the probability of obtaining results at least as extreme as those observed, assuming the null hypothesis is true. It is NOT the probability that the null hypothesis is true. A p-value of 0.04 means there is a 4% chance of seeing this difference (or greater) if there is truly no difference between groups.

📘 Q25 (Epidemiology) — In a 5-year cohort study on hormonal contraception and breast cancer risk, 40% of participants in the exposed group are lost to follow-up compared to 10% in the unexposed group. This is most likely to cause: A) Recall bias B) Selection bias C) Observer bias D) Lead-time bias E) Confounding by indication

Answer: B

Differential loss to follow-up (attrition) introduces selection bias because the participants who remain in each group may differ systematically. If women who develop breast cancer are more likely to be lost from the exposed group, the association may be underestimated. Recall bias is specific to case-control studies. Confounding by indication applies to treatment comparisons.

📘 Q26 (Epidemiology) — A screening programme for congenital hypothyroidism has a positive predictive value of 8%. Which change would most improve the PPV? A) Increasing the sensitivity of the test B) Decreasing the specificity of the test C) Screening a population with higher disease prevalence D) Reducing the threshold for a positive test E) Increasing the sample size

Answer: C

PPV is strongly influenced by disease prevalence. For a given sensitivity and specificity, PPV increases as prevalence increases. Increasing sensitivity (or lowering the threshold) would increase true positives but also increase false positives, potentially worsening PPV. Improving specificity reduces false positives, which does improve PPV, but increasing prevalence has the greatest impact.

📘 Q27 (Epidemiology) — What is the primary advantage of a matched case-control study over an unmatched one? A) It eliminates the need for statistical analysis B) It controls for confounding by matching variables C) It allows calculation of relative risk directly D) It increases the generalisability of findings E) It reduces the cost of the study

Answer: B

Matching in case-control studies controls for potential confounders (e.g., age, parity) by ensuring cases and controls are similar on these variables. However, matching factors cannot then be analysed as exposures. Matched studies require conditional logistic regression or McNemar's test for analysis. Matching does not allow direct RR calculation.

📘 Q28 (Epidemiology) — A systematic review of 8 RCTs on magnesium sulphate for eclampsia prevention uses a fixed-effects model. What assumption does this model make? A) All studies have the same sample size B) The true treatment effect is the same across all studies C) The studies are of equal quality D) There is no publication bias E) The outcome is binary

Answer: B

A fixed-effects model assumes that the true treatment effect is identical across all studies, and observed differences are due solely to random sampling error. A random-effects model, conversely, allows the true effect to vary between studies (between-study heterogeneity) and incorporates this into the analysis.

📘 Q29 (Epidemiology) — In a community-based screening programme for cervical cancer, coverage is defined as: A) The proportion of screened women who test positive B) The proportion of the target population who have been screened C) The proportion of cervical cancer cases detected by screening D) The number of tests performed per 1000 women E) The proportion of positive results confirmed by colposcopy

Answer: B

Coverage (or uptake) is the proportion of the eligible target population that actually receives the screening test. It is a key performance indicator for screening programmes — even a highly accurate test will have limited population impact if coverage is low. The WHO target for cervical screening coverage is typically ≥70%.

📘 Q30 (Epidemiology) — A study finds a strong statistical association between induced abortion and subsequent breast cancer (OR 2.0, p < 0.001). However, the researchers note that women who had abortions were more likely to be nulliparous and have higher alcohol intake. These factors are best described as: A) Mediators B) Confounders C) Effect modifiers D) Colliders E) Instrumental variables

Answer: B

Nulliparity and alcohol intake are associated with both the exposure (induced abortion) and the outcome (breast cancer), and are not on the causal pathway. They are confounders. If these factors are not adjusted for, the observed association may be partially or entirely due to confounding rather than a direct causal effect.

📘 Q31 (Epidemiology) — A diagnostic test has a specificity of 95%. At a disease prevalence of 20%, the negative predictive value (NPV) is 97%. If the same test is applied in a population with 5% prevalence, the NPV will be: A) < 97% B) 97% C) > 97% D) Cannot be determined without sensitivity E) 95%

Answer: C

NPV increases as prevalence decreases. NPV = TN / (TN + FN). When disease is less common, true negatives form a larger proportion of test-negative results. At 20% prevalence, NPV is 97%. At 5% prevalence (a rarer disease), more people without disease will be test-negative, so NPV will be higher (>97%).

📘 Q32 (Epidemiology) — Which study design is most susceptible to recall bias? A) Randomised controlled trial B) Prospective cohort study C) Case-control study D) Cross-sectional study E) Ecological study

Answer: C

Recall bias is a particular problem in case-control studies because cases (who have the outcome) may remember past exposures differently from controls (who do not have the outcome). For example, mothers of children with congenital anomalies may search their memory more thoroughly for potential causes than mothers of healthy children.

📘 Q33 (Epidemiology) — In an RCT of a new induction of labour agent, the relative risk of caesarean section in the treatment group compared to placebo is 0.85 (95% CI 0.70–1.03). What is the most appropriate conclusion? A) The treatment significantly reduces caesarean section risk B) The treatment increases caesarean section risk C) The treatment shows a trend toward reduction but is not statistically significant D) The treatment has no effect on caesarean section risk E) The study proves the treatment is ineffective

Answer: C

The point estimate (RR 0.85) suggests a 15% reduction in risk, but the 95% confidence interval (0.70–1.03) crosses 1, meaning the result is not statistically significant at p < 0.05. It would be incorrect to conclude the treatment is effective or has no effect — the study is inconclusive, possibly due to insufficient power. The trend is toward benefit.

📘 Q34 (Epidemiology) — The number needed to harm (NNH) for a medication causing nausea is 20. This means: A) 20 patients will experience nausea B) For every 20 patients treated, 1 will develop nausea due to the medication C) For every 20 patients treated, 1 will be protected from nausea D) 20% of patients will experience nausea E) The relative risk of nausea is 20

Answer: B

NNH = 1 / attributable risk (absolute risk increase). An NNH of 20 means that for every 20 patients exposed to the medication, one additional case of nausea occurs that would not have occurred with placebo. Smaller NNH values indicate greater harm. NNH is the harmful analogue of number needed to treat (NNT).

📘 Q35 (Epidemiology) — A cross-sectional study using a self-administered questionnaire finds that women who report a history of miscarriage also report higher stress levels. The main limitation of this study design is: A) Inability to determine temporal sequence between stress and miscarriage B) High risk of selection bias C) Inability to calculate prevalence D) Poor generalisability to other populations E) High cost and long duration

Answer: A

The key limitation of cross-sectional studies is that exposure and outcome are measured simultaneously, so the temporal sequence cannot be established. It is unclear whether stress preceded miscarriage (causal direction) or whether experiencing a miscarriage caused higher stress levels (reverse causation). Cross-sectional studies can calculate prevalence efficiently.

Statistics (Questions 36–70)

📘 Q36 (Statistics) — A dataset of 100 fetal birth weights (grams) has a mean of 3400, a median of 3420, and a mode of 3450. The distribution is best described as: A) Positively skewed B) Negatively skewed C) Normally distributed D) Bimodal E) Uniformly distributed

Answer: B

In a negatively skewed (left-skewed) distribution, the mean is less than the median, which is less than the mode (mean < median < mode). The tail is on the left side — a few lower birth weights pull the mean downward. In positive skew, mean > median > mode. In a normal distribution, all three are approximately equal.

📘 Q37 (Statistics) — The standard deviation of a dataset describes: A) The average distance of each data point from the mean B) The middle value when data are ordered C) The most frequently occurring value D) The range between the smallest and largest values E) The proportion of data within a given interval

Answer: A

Standard deviation is the square root of the variance and measures the spread of data around the mean. It quantifies the average (root-mean-squared) distance of individual observations from the mean. For normally distributed data, approximately 68% of values lie within ±1 SD, 95% within ±2 SD, and 99.7% within ±3 SD.

📘 Q38 (Statistics) — Which statistical test would be most appropriate to compare mean serum ferritin levels between three groups of pregnant women (first trimester, second trimester, third trimester)? A) Independent samples t-test B) Paired t-test C) Chi-square test D) One-way ANOVA E) Mann-Whitney U test

Answer: D

One-way ANOVA (analysis of variance) compares means across three or more independent groups. An independent t-test is for comparing two groups only. The chi-square test is for categorical data. Mann-Whitney U is a non-parametric alternative for two groups. Ferritin levels are continuous data, and with three trimester groups, ANOVA is appropriate.

📘 Q39 (Statistics) — If the assumptions of ANOVA are violated (data are not normally distributed and have unequal variances), which test is the most appropriate alternative? A) Repeated measures ANOVA B) Kruskal-Wallis test C) Friedman test D) McNemar's test E) Pearson correlation

Answer: B

The Kruskal-Wallis test is the non-parametric equivalent of one-way ANOVA. It tests whether samples originate from the same distribution without assuming normality or equal variances. The Friedman test is the non-parametric equivalent for repeated-measures (paired) ANOVA. McNemar's test is for paired categorical data.

📘 Q40 (Statistics) — A researcher wants to test whether there is an association between parity (primiparous vs. multiparous) and mode of delivery (vaginal, instrumental, caesarean). Which test should be used? A) Independent t-test B) Paired t-test C) Chi-square test of independence D) Pearson correlation E) One-way ANOVA

Answer: C

The chi-square test of independence assesses whether there is an association between two categorical variables. Here, both parity (2 categories) and mode of delivery (3 categories) are categorical. The test compares observed frequencies with expected frequencies under the null hypothesis of no association.

📘 Q41 (Statistics) — In a chi-square test with 3 rows and 2 columns, the degrees of freedom are: A) 2 B) 4 C) 5 D) 6 E) 1

Answer: A

Degrees of freedom for a chi-square test of independence = (rows − 1) × (columns − 1) = (3 − 1) × (2 − 1) = 2 × 1 = 2. This reflects the number of cell frequencies that are free to vary given the fixed row and column totals.

📘 Q42 (Statistics) — Which of the following is a non-parametric alternative to the paired t-test? A) Wilcoxon signed-rank test B) Mann-Whitney U test C) Kruskal-Wallis test D) Spearman's rank correlation E) Independent samples t-test

Answer: A

📘 Q43 (Statistics) — A 95% confidence interval for the mean difference in birth weight between two groups ranges from −50 g to +250 g. Which interpretation is correct? A) There is a 95% probability that the true mean difference lies between −50 g and +250 g B) 95% of the data falls within this range C) The difference is statistically significant because zero is included in the interval D) The difference is not statistically significant at the 0.05 level E) The sample mean difference is 100 g

Answer: D

The 95% confidence interval includes zero, meaning the null hypothesis (no difference) cannot be rejected at α = 0.05. The difference is not statistically significant. The correct interpretation of a CI is: if repeated samples were taken and CIs calculated, 95% of those intervals would contain the true population parameter.

📘 Q44 (Statistics) — The correlation coefficient (r) between maternal BMI and fetal birth weight is calculated as r = 0.45, p < 0.001. Which statement is correct? A) There is no relationship between BMI and birth weight B) 45% of the variation in birth weight is explained by BMI C) There is a moderate positive linear relationship between BMI and birth weight D) A higher BMI always causes higher birth weight E) The relationship is negative

Answer: C

An r-value of 0.45 indicates a moderate positive linear relationship — as BMI increases, birth weight tends to increase. The coefficient of determination (r²) = 0.2025, meaning approximately 20% (not 45%) of the variation in birth weight is explained by BMI. Correlation does not imply causation.

📘 Q45 (Statistics) — Which of the following best describes a Type I error in hypothesis testing? A) Failing to reject the null hypothesis when it is false B) Rejecting the null hypothesis when it is true C) Accepting the alternative hypothesis when it is false D) Having insufficient statistical power E) Using the wrong statistical test

Answer: B

A Type I error (α or false positive) is rejecting a true null hypothesis — concluding there is a difference when none exists. The significance level α (conventionally 0.05) is the maximum acceptable probability of a Type I error. Type II error (β or false negative) is failing to reject a false null hypothesis.

📘 Q46 (Statistics) — Statistical power is defined as: A) The probability of making a Type I error B) The probability of making a Type II error C) The probability of rejecting the null hypothesis when it is false D) The sample size required for a study E) The magnitude of the treatment effect

Answer: C

Power = 1 − β = probability of correctly rejecting a false null hypothesis (true positive). Power depends on: sample size, effect size, significance level (α), and variability of the outcome. Studies are typically designed to achieve at least 80% power. Low power reduces the chance of detecting a true effect.

📘 Q47 (Statistics) — A researcher compares Apgar scores (0–10 scale) between two groups of neonates using the Mann-Whitney U test rather than an independent t-test because: A) The data are normally distributed B) Apgar scores are ordinal categorical data C) The sample size is large D) The variances are equal E) The groups are paired

Answer: B

Apgar scores are ordinal data (ordered categories), not true continuous data. The Mann-Whitney U test is appropriate for comparing two independent groups on an ordinal outcome. It does not require normality assumptions. The t-test assumes continuous, normally distributed data.

📘 Q48 (Statistics) — Kaplan-Meier survival analysis is used to estimate: A) Mean survival time assuming normal distribution B) Cumulative survival probability over time, accounting for censoring C) The hazard ratio between two groups D) The proportion of events at a single time point E) Linear regression of survival on covariates

Answer: B

Kaplan-Meier analysis estimates the survival function (probability of surviving beyond each time point) while accounting for censored data (participants lost to follow-up or event-free at study end). It generates a step-function survival curve. The log-rank test compares survival curves between groups. Cox regression provides hazard ratios.

📘 Q49 (Statistics) — The log-rank test is used to: A) Compare means between two groups B) Compare survival distributions between two or more groups C) Test for correlation between two variables D) Assess goodness-of-fit of a regression model E) Compare proportions between two groups

Answer: B

The log-rank test compares the entire survival experience (Kaplan-Meier curves) between groups, testing the null hypothesis that there is no difference in survival. It is a non-parametric test that gives equal weight to all time points. It does not provide a hazard ratio — that requires Cox proportional hazards regression.

📘 Q50 (Statistics) — Cox proportional hazards regression produces which measure of effect? A) Odds ratio B) Relative risk C) Hazard ratio D) Risk difference E) Incidence rate ratio

Answer: C

Cox regression models time-to-event data and produces hazard ratios. The hazard ratio is the ratio of the instantaneous event rates between groups, assumed to be constant over time (proportional hazards assumption). It is analogous to relative risk but accounts for the timing of events and censoring.

📘 Q51 (Statistics) — The interquartile range (IQR) is preferred over the standard deviation when: A) The data are normally distributed B) The data are skewed or contain outliers C) The sample size is very large D) Comparing means between groups E) The variance is known

Answer: B

The IQR (Q3 − Q1) is a robust measure of spread that is not affected by extreme values or skewness, unlike the standard deviation which is sensitive to outliers. When data are skewed, the median and IQR provide a better summary than the mean and standard deviation, which assume normality.

📘 Q52 (Statistics) — A study reports Pearson correlation r = −0.85 between maternal age and fertility treatment success. This indicates: A) A weak positive correlation B) A strong negative linear relationship C) No relationship between the variables D) 85% of the variation is explained E) The correlation is not statistically significant

Answer: B

An r-value of −0.85 indicates a strong negative linear correlation — as maternal age increases, fertility treatment success tends to decrease. The closer r is to −1 or +1, the stronger the linear relationship. r² = 0.7225, meaning 72% of the variation in success is explained by age.

📘 Q53 (Statistics) — In linear regression, the coefficient of determination (R²) represents: A) The slope of the regression line B) The correlation between observed and predicted values C) The proportion of variance in the outcome explained by the predictor(s) D) The standard error of the estimate E) The p-value of the regression model

Answer: C

R² quantifies the goodness-of-fit of a regression model — it is the proportion of total variability in the outcome that is accounted for by the predictor variables. R² ranges from 0 (no predictive value) to 1 (perfect prediction). In simple linear regression, R² equals the square of the Pearson correlation coefficient (r²).

📘 Q54 (Statistics) — Which approach would be used to investigate whether maternal age, BMI, and smoking status together predict the risk of preterm birth? A) Simple linear regression B) Multiple logistic regression C) Simple logistic regression D) Pearson correlation E) Chi-square test

Answer: B

Multiple logistic regression is appropriate when the outcome is binary (preterm birth: yes/no) and there are multiple predictors (age, BMI, smoking). It models the log-odds of the outcome as a linear function of the predictors and provides adjusted odds ratios for each predictor. Simple linear/logistic regression handles only one predictor.

📘 Q55 (Statistics) — The standard error of the mean (SEM) is calculated as: A) SD / √n B) SD × √n C) √(SD / n) D) SD / n E) n / SD

Answer: A

SEM = standard deviation / √(sample size). The SEM quantifies the precision of the sample mean as an estimate of the population mean. As sample size increases, the SEM decreases, reflecting more precise estimation. SEM is always smaller than SD because it measures variability of the sampling distribution, not the data itself.

📘 Q56 (Statistics) — A 99% confidence interval is wider than a 95% confidence interval for the same data because: A) It uses a smaller sample size B) It requires greater certainty that the interval contains the true parameter C) The effect size is larger D) The standard deviation is larger E) The significance level is smaller

Answer: B

A 99% CI provides more confidence (99% vs. 95%) that the interval contains the true population parameter. To achieve higher confidence, the interval must be wider, using a larger critical value (e.g., z = 2.576 vs. z = 1.96 for large samples). The trade-off is precision for confidence.

📘 Q57 (Statistics) — Before using a paired t-test to compare blood pressure before and after treatment, which assumption is most important to check? A) The data are independent between groups B) The differences between pairs are normally distributed C) The variances in both groups are equal D) The sample size is > 30 E) The data are ordinal

Answer: B

The paired t-test requires that the differences between paired observations (post-treatment minus pre-treatment) are approximately normally distributed. This is the normality assumption on the differences. Independence between pairs is assumed by design. Equal variances (homoscedasticity) is an assumption of the independent t-test, not the paired version.

📘 Q58 (Statistics) — Fisher's exact test is preferred over the chi-square test when: A) The sample size is very large B) More than 20% of expected cell frequencies are below 5 C) The data are continuous D) Comparing means between groups E) The outcome is ordinal

Answer: B

Fisher's exact test calculates the exact probability of the observed contingency table under the null hypothesis and does not rely on large-sample approximations. It is recommended when expected frequencies in any cell are less than 5, as the chi-square approximation becomes unreliable in such cases. It can be computationally intensive for large tables.

📘 Q59 (Statistics) — The median is a better measure of central tendency than the mean when: A) The data follow a normal distribution B) The sample size is greater than 100 C) The data contain outliers or are skewed D) The standard deviation is known E) Comparing two independent groups

Answer: C

The median is resistant to outliers and skewness because it depends only on the middle value(s) of the ordered data. The mean is sensitive to extreme values — a single outlier can substantially shift the mean. For symmetric distributions without outliers, the mean and median are approximately equal.

📘 Q60 (Statistics) — A researcher performs 20 independent statistical tests and finds two significant results (p < 0.05). The most appropriate concern is: A) Low statistical power B) Type I error inflation due to multiple testing C) Type II error D) Confounding E) Selection bias

Answer: B

When multiple hypothesis tests are performed, the probability of at least one false positive (Type I error) increases. With 20 independent tests at α = 0.05, the familywise error rate = 1 − (0.95)²⁰ ≈ 64%. Multiple comparison corrections (Bonferroni, Holm-Bonferroni, false discovery rate) should be applied.

📘 Q61 (Statistics) — In a Bland-Altman plot used to assess agreement between two methods of measuring fetal biometry, the x-axis typically represents: A) The difference between the two methods B) The average of the two methods C) The first method's values D) The second method's values E) The reference standard values

Answer: B

A Bland-Altman plot shows the difference between two measurement methods against their mean (average). The mean difference and limits of agreement (mean ± 1.96 SD of differences) are plotted. If the differences are within clinically acceptable limits, the methods can be considered interchangeable. This assesses agreement, not correlation.

📘 Q62 (Statistics) — Sensitivity analysis in the context of a clinical trial is used to: A) Test the primary hypothesis B) Assess how robust the results are to different assumptions or analytical choices C) Determine the sample size needed D) Calculate the p-value more accurately E) Identify outliers in the data

Answer: B

Sensitivity analysis tests whether the conclusions of a study change under different analytical scenarios — e.g., different methods of handling missing data, different model specifications, or excluding certain participants. Robust conclusions that persist across sensitivity analyses are more credible.

📘 Q63 (Statistics) — Which of the following transformations is appropriate if data are positively skewed (e.g., hormone levels)? A) Square transformation B) Logarithmic transformation C) Reciprocal transformation D) Adding a constant E) Linear transformation

Answer: B

Logarithmic transformation is commonly applied to positively skewed data (e.g., hormone levels, antibody titres, length of stay). It compresses the right tail and makes the distribution more symmetric, often approximately normal. This satisfies assumptions for parametric tests. The choice of transformation depends on the nature of the skewness.

📘 Q64 (Statistics) — The null hypothesis for a chi-square test of independence states that: A) The row and column variables are associated B) The row and column variables are independent (no association) C) The observed and expected frequencies are different D) The sample mean equals the population mean E) The correlation coefficient is zero

Answer: B

The null hypothesis for a chi-square test of independence is that there is no association between the two categorical variables — i.e., they are independent. The alternative hypothesis is that the variables are associated (dependent). A small p-value leads to rejection of independence.

📘 Q65 (Statistics) — A researcher wants to compare the duration of labour (in hours) between two independent groups. The data are normally distributed and the sample sizes are 25 and 30. The most appropriate parametric test is: A) Paired t-test B) Independent samples t-test C) Mann-Whitney U test D) Wilcoxon signed-rank test E) Chi-square test

Answer: B

The independent samples t-test (two-sample t-test) compares the means of a continuous outcome between two independent groups when the data are approximately normally distributed. The data are normally distributed (satisfying the parametric assumption), and the groups are independent (not paired), making the t-test appropriate.

📘 Q66 (Statistics) — In a sample of 500 women, the mean haemoglobin is 12.0 g/dL with a standard deviation of 1.5 g/dL. Assuming a normal distribution, approximately how many women have haemoglobin between 10.5 and 13.5 g/dL? A) 170 B) 240 C) 340 D) 475 E) 500

Answer: C

10.5 g/dL is 1 SD below the mean (12.0 − 1.5) and 13.5 g/dL is 1 SD above the mean (12.0 + 1.5). In a normal distribution, approximately 68% of values lie within ±1 SD of the mean. 68% of 500 = 340 women. Approximately 95% lie within ±2 SD, and 99.7% within ±3 SD.

📘 Q67 (Statistics) — Heterogeneity in a meta-analysis is quantified using which statistic? A) R² B) I² C) t-statistic D) F-statistic E) Cohen's kappa

Answer: B

The I² statistic describes the percentage of total variation across studies that is due to true heterogeneity rather than chance. I² values of 25%, 50%, and 75% are considered low, moderate, and high heterogeneity, respectively. The Q-statistic (Cochran's Q) tests for heterogeneity, but I² quantifies its magnitude. High heterogeneity may warrant a random-effects model.

📘 Q68 (Statistics) — A researcher uses Cohen's kappa (κ) to assess inter-rater reliability between two clinicians classifying CTG traces as normal, suspicious, or pathological. A κ of 0.82 indicates: A) Poor agreement B) Fair agreement C) Moderate agreement D) Good/substantial agreement E) Perfect agreement

Answer: D

Cohen's kappa measures inter-rater agreement beyond chance. κ ranges from −1 to +1. Common interpretation: ≤0 = poor, 0.01–0.20 = slight, 0.21–0.40 = fair, 0.41–0.60 = moderate, 0.61–0.80 = substantial, 0.81–0.99 = almost perfect agreement. A κ of 0.82 represents very good/substantial agreement. Note that κ can be low even with high observed agreement if prevalence is skewed.

📘 Q69 (Statistics) — Which of the following best describes a ceiling effect in a measurement instrument? A) A large proportion of participants score at the highest possible value B) A large proportion of participants score at the lowest possible value C) The instrument has poor test-retest reliability D) The instrument shows gender bias E) Scores are normally distributed

Answer: A

A ceiling effect occurs when a substantial proportion of subjects achieve the maximum possible score, limiting the instrument's ability to discriminate among high performers. This reduces variability and can obscure differences between groups. Floor effect (large proportion at minimum score) is the opposite problem. Both reduce clinical utility.

📘 Q70 (Statistics) — In a factorial ANOVA examining the effects of two drugs (Drug A and Drug B) on uterine contraction strength, a significant interaction term means: A) Both drugs have the same effect B) The effect of Drug A depends on whether Drug B is given C) Neither drug has any effect D) Drug A is more effective than Drug B E) The sample size is inadequate

Answer: B

An interaction occurs when the effect of one factor depends on the level of another factor. A significant Drug A × Drug B interaction means the effect of Drug A on contraction strength differs depending on whether Drug B is co-administered. In the presence of interaction, main effects must be interpreted cautiously.

Biophysics & Imaging (Questions 71–100)

📘 Q71 (Biophysics) — In ultrasound physics, which of the following frequencies produces the highest spatial resolution? A) 3.5 MHz B) 5.0 MHz C) 7.5 MHz D) 10.0 MHz E) 2.5 MHz

Answer: D

Higher frequency ultrasound waves produce shorter wavelengths, which yield better axial resolution (the ability to distinguish two closely spaced structures along the beam axis). However, higher frequencies also undergo greater attenuation in tissue, so depth of penetration is reduced. Transvaginal probes typically use 5–10 MHz for detailed pelvic imaging, while abdominal probes use 2–5 MHz.

📘 Q72 (Biophysics) — The Doppler shift principle states that the change in frequency of reflected ultrasound from moving blood cells is proportional to: A) The speed of sound in tissue B) The velocity of blood flow times the cosine of the angle of insonation C) The ultrasound frequency squared D) The square root of blood flow velocity E) The distance from the transducer

Answer: B

The Doppler equation: Δf = (2f₀ v cos θ) / c, where Δf is the Doppler shift, f₀ is transmitted frequency, v is blood flow velocity, θ is the angle between the ultrasound beam and the direction of blood flow, and c is the speed of sound in tissue. The cosine of the angle is critical — at 90° (perpendicular beam), cos 90° = 0, and no Doppler shift is detected.

📘 Q73 (Biophysics) — In CTG interpretation, baseline fetal heart rate variability of 6–10 bpm is classified as: A) Absent B) Minimal C) Moderate D) Marked E) Sinusoidal

Answer: C

Baseline variability is classified as: absent (undetectable), minimal (≤5 bpm), moderate (6–25 bpm), and marked (>25 bpm). Moderate variability (6–25 bpm) is normal and reassuring, indicating an intact autonomic nervous system. Absent or minimal variability with no accelerations is a non-reassuring sign requiring further assessment.

📘 Q74 (Biophysics) — A CTG shows a baseline of 155 bpm, variability of 4 bpm, no accelerations, and variable decelerations. Using the FIGO 2015 classification system, this CTG would be classified as: A) Normal B) Suspicious C) Pathological D) Pre-terminal E) Uninterpretable

Answer: B

According to FIGO 2015, a suspicious (equivocal) CTG has a baseline of 150–170 bpm (or 110–150 with other concerns) plus minimal variability (3–5 bpm) or variable decelerations, but without all pathological criteria. A pathological CTG would have baseline variability <3 bpm or repeated late decelerations or sinusoidal pattern.

📘 Q75 (Biophysics) — Late decelerations on a CTG are characterised by: A) An abrupt decrease in FHR with onset at the start of the contraction B) A gradual decrease in FHR with the nadir occurring after the peak of the contraction C) A decrease in FHR with the nadir at the peak of the contraction D) An increase in FHR followed by a decrease E) A sinusoidal waveform pattern

Answer: B

Late decelerations are smooth, gradual decreases in FHR (onset to nadir ≥30 seconds) where the nadir occurs after the peak of the contraction. They reflect utero-placental insufficiency — the dip in FHR is delayed relative to the contraction. They are non-reassuring and require prompt evaluation and intervention.

📘 Q76 (Biophysics) — The biophysical profile (BPP) scoring includes all of the following components EXCEPT: A) Fetal breathing movements B) Fetal movement C) Fetal tone D) Amniotic fluid volume E) Uterine artery Doppler

Answer: E

The BPP consists of five components, each scored 0 or 2 for a maximum of 10: (1) fetal breathing movements, (2) gross body movements, (3) fetal tone, (4) amniotic fluid volume, and (5) non-stress test (CTG reactivity). Uterine artery Doppler is not part of the standard BPP score, though it may be used separately in fetal surveillance.

📘 Q77 (Biophysics) — A BPP score of 4/10 at 34 weeks' gestation would typically warrant: A) Reassurance and routine follow-up B) Repeat BPP in 1 week C) Delivery within 24 hours D) Delivery within 48 hours E) Immediate delivery regardless of other factors

Answer: C

A BPP of 4/10 is considered abnormal and indicates possible fetal compromise. If the oligohydramnios component is the reason for the low score (which is the most concerning because it reflects chronic hypoxia), delivery within 24 hours is typically recommended if the fetus is viable (≥34 weeks) and the cervix is favourable. Immediate delivery is indicated for scores ≤2/10.

📘 Q78 (Biophysics) — The acoustic impedance (Z) of a tissue determines: A) The frequency of the ultrasound wave B) The speed of sound in that tissue C) The amount of reflection at an interface between two tissues D) The wavelength of the ultrasound beam E) The colour Doppler map

Answer: C

Acoustic impedance (Z = density × speed of sound) determines how much ultrasound energy is reflected at tissue boundaries. When two tissues have very different acoustic impedances (e.g., soft tissue-bone or soft tissue-air interface), a large proportion of the ultrasound beam is reflected, creating strong echoes. This is why gel is needed to eliminate air between the transducer and skin.

📘 Q79 (Biophysics) — In magnetic resonance imaging (MRI), T1-weighted images primarily highlight differences in: A) Proton density B) Blood flow velocity C) Tissue T1 relaxation times D) Tissue T2 relaxation times E) Magnetic field strength

Answer: C

T1-weighted images emphasise differences in T1 (longitudinal/spin-lattice) relaxation times between tissues. Tissues with short T1 (e.g., fat) appear bright, while tissues with long T1 (e.g., CSF, fluid) appear dark. T2-weighted images highlight differences in T2 (transverse/spin-spin) relaxation — fluids appear bright on T2. Both are used in pelvic MRI.

📘 Q80 (Biophysics) — The primary radiation safety principle "ALARA" stands for: A) All Levels At Risk Are Minimal B) As Low As Reasonably Achievable C) Always Limit And Reduce Accumulation D) Annual Lifetime Allowable Radiation Amount E) Absorbed Linear Attenuation Rate Adjustment

Answer: B

ALARA (As Low As Reasonably Achievable) is the guiding principle for radiation protection. It involves three strategies: time (minimising exposure time), distance (maximising distance from the source), and shielding (using barriers between the source and personnel). This applies to all diagnostic and therapeutic uses of ionising radiation.

📘 Q81 (Biophysics) — The fetus is most radiosensitive during which period of development? A) Pre-implantation (weeks 0–2) B) Organogenesis (weeks 2–8) C) Early fetal period (weeks 8–15) D) Late fetal period (weeks 15–40) E) Sensitivity is equal across all trimesters

Answer: B

The period of organogenesis (approximately 2–8 weeks post-conception) is when the fetus is most sensitive to radiation-induced congenital malformations. During this period, the central nervous system is especially vulnerable. The risk of radiation-induced malformations is dose-dependent, with a threshold around 50–100 mGy. After 20 weeks, the primary risk is childhood cancer induction rather than malformation.

📘 Q82 (Biophysics) — A typical chest X-ray delivers an effective radiation dose of approximately: A) 0.02 mSv B) 0.2 mSv C) 2 mSv D) 20 mSv E) 200 mSv

Answer: A

A standard single chest X-ray delivers about 0.02 mSv (20 μSv), which is equivalent to approximately 2–3 days of background natural radiation. For comparison: a CT chest is ~8 mSv, a pelvic X-ray is ~0.7 mSv, and a mammogram is ~0.4 mSv. The risk of inducing a fatal cancer is estimated at ~5% per Sv, making the risk from a chest X-ray extremely low.

📘 Q83 (Biophysics) — In pulsed-wave Doppler ultrasound, the Nyquist limit refers to: A) The maximum blood flow velocity that can be measured without aliasing B) The minimum blood flow velocity detectable C) The depth at which Doppler signals are strongest D) The frequency of the transducer E) The angle correction factor

Answer: A

The Nyquist limit in pulsed-wave Doppler is half the pulse repetition frequency (PRF/2). Velocities above this limit cause aliasing — the Doppler waveform wraps around and appears on the opposite side of the baseline. Lowering the transducer frequency, increasing the PRF, or using continuous-wave Doppler (which has no Nyquist limit) can address this.

📘 Q84 (Biophysics) — Which of the following CTG patterns is most suggestive of acute cord compression? A) Early decelerations B) Variable decelerations C) Late decelerations D) Prolonged decelerations E) Sinusoidal pattern

Answer: B

Variable decelerations are abrupt decreases in FHR (onset to nadir <30 seconds) that vary in timing, depth, and duration with contractions. They are caused by umbilical cord compression leading to a vagal reflex. They are the most common deceleration in labour. Early decelerations are from head compression and are benign. Late decelerations suggest placental insufficiency.

📘 Q85 (Biophysics) — In colour Doppler ultrasound, the colour map typically assigns which colours to indicate flow toward the transducer? A) Red B) Blue C) Green D) Yellow E) White

Answer: A

By convention (though user-selectable), flow toward the transducer is displayed in red and flow away from the transducer in blue. This is the "BART" convention (Blue Away, Red Toward). Colour intensity typically reflects mean velocity — brighter colours indicate higher velocities. Colour Doppler is angle-dependent, like all Doppler modalities.

📘 Q86 (Biophysics) — The thermal index (TI) in ultrasound safety indicates: A) The risk of cavitation from ultrasound exposure B) The potential for tissue heating from ultrasound absorption C) The total acoustic power output D) The frequency of the ultrasound beam E) The resolution of the image

Answer: B

The thermal index (TI) is an on-screen safety indicator estimating the potential for tissue temperature rise due to ultrasound absorption. TI = acoustic power / power required to raise tissue temperature by 1°C. A higher TI indicates greater heating risk. The mechanical index (MI) relates to cavitation risk. Both should be minimised using the ALARA principle, especially in obstetrics.

📘 Q87 (Biophysics) — In MRI, a gadolinium-based contrast agent is used to enhance imaging by: A) Blocking proton relaxation B) Shortening T1 relaxation time of nearby water protons C) Increasing the magnetic field strength D) Emitting detectable radiation E) Reducing T2 relaxation time only

Answer: B

Gadolinium is a paramagnetic contrast agent that shortens the T1 and T2 relaxation times of nearby water protons. On T1-weighted images, gadolinium causes enhancement (increased signal) in areas of increased blood flow, vascularity, or disrupted blood-brain barrier. However, gadolinium is generally avoided in pregnancy (crosses the placenta) unless essential.

📘 Q88 (Biophysics) — The half-value layer (HVL) in X-ray physics is: A) The thickness of material needed to reduce the X-ray intensity by 50% B) The distance from the X-ray tube to the patient C) The time for the radioactive source to decay by half D) The average energy of the X-ray beam E) The filtration used in the X-ray tube

Answer: A

The half-value layer (HVL) is the thickness of a specified material (usually aluminium or copper) required to reduce the intensity of the X-ray beam by 50%. It is a measure of beam quality (penetrating power). Higher kVp produces a more penetrating beam with a larger HVL. HVL is used in quality assurance of X-ray equipment.

📘 Q89 (Biophysics) — Which of the following best describes the Frank-Starling mechanism in the context of uterine blood flow? A) Uterine contractions reduce placental blood flow during peak contractions B) Increased preload leads to increased cardiac output C) Trophoblast invasion remodels spiral arteries D) The fetus produces vasoactive peptides to maintain cerebral perfusion E) Progesterone relaxes vascular smooth muscle

Answer: B

The Frank-Starling mechanism describes how increased ventricular filling (preload) stretches cardiac myocytes, increasing the force of contraction and thus stroke volume and cardiac output. This is relevant in pregnancy due to increased blood volume. The other options relate to different physiological processes in pregnancy.

📘 Q90 (Biophysics) — In ultrasound imaging, axial resolution is primarily determined by: A) The transducer frequency B) The beam width C) The depth of imaging D) The gain setting E) The frame rate

Answer: A

📘 Q91 (Biophysics) — A patient at 32 weeks' gestation has a CTG showing a baseline rate of 100 bpm. This is classified as: A) Tachycardia B) Normal C) Bradycardia D) Sinusoidal E) Undetermined

Answer: C

Fetal bradycardia is defined as a baseline heart rate below 110 bpm for ≥10 minutes. A baseline of 100 bpm is abnormal and requires assessment. Causes include: severe hypoxia, congenital heart block (associated with maternal autoimmune disease), fetal distress, or drugs (e.g., beta-blockers). Fetal tachycardia is baseline >160 bpm.

📘 Q92 (Biophysics) — The resistive index (RI) in Doppler ultrasound of the uterine artery is calculated as: A) (PSV − EDV) / PSV B) (PSV − EDV) / Mean velocity C) PSV / EDV D) (PSV + EDV) / PSV E) (PSV × EDV) / PSV

Answer: A

Resistive index (RI) = (peak systolic velocity − end-diastolic velocity) / peak systolic velocity. In the uterine artery, high RI in the second trimester (e.g., >0.58) with a persistent diastolic notch suggests impaired trophoblast invasion and increased risk of pre-eclampsia and fetal growth restriction. Pulsatility index (PI) = (PSV − EDV) / mean velocity.

📘 Q93 (Biophysics) — Loss of end-diastolic flow (AEDF) in the umbilical artery Doppler waveform is associated with: A) Normal placental function B) Severe placental insufficiency and fetal growth restriction C) Twin-to-twin transfusion syndrome D) Maternal diabetes E) Fetal anaemia

Answer: B

Absent end-diastolic flow (AEDF) in the umbilical artery indicates significantly increased placental vascular resistance. It is associated with severe fetal growth restriction, hypoxia, and adverse perinatal outcomes. Reversed end-diastolic flow (REDF) is even more ominous and often triggers urgent delivery after 32–34 weeks. These findings reflect the progression of placental insufficiency.

📘 Q94 (Biophysics) — The middle cerebral artery (MCA) Doppler peak systolic velocity is used to assess: A) Fetal lung maturity B) Fetal anaemia C) Placental perfusion D) Amniotic fluid volume E) Cervical competence

Answer: B

MCA-PSV is the most sensitive non-invasive method to detect fetal anaemia, particularly in cases of red cell alloimmunisation (e.g., anti-D, anti-c, anti-Kell). With anaemia, decreased blood viscosity leads to increased cardiac output and increased flow velocity in the MCA. A PSV >1.5 multiples of the median (MoM) indicates moderate-to-severe anaemia and may trigger fetal blood sampling or intrauterine transfusion.

📘 Q95 (Biophysics) — Amniotic fluid index (AFI) is calculated by: A) Measuring the single deepest vertical pocket of amniotic fluid B) Summing the deepest vertical pocket in each of four quadrants of the uterus C) Measuring the total volume of amniotic fluid in millilitres D) Multiplying the length of the uterus by the depth of fluid E) Assessing the colour of amniotic fluid on ultrasound

Answer: B

AFI is the sum of the deepest vertical pocket of amniotic fluid (free of umbilical cord and fetal parts) measured in each of four abdominal quadrants (using the linea nigra and umbilicus as dividing lines). Normal AFI is 8–24 cm. Oligohydramnios is AFI <5 cm (or single deepest pocket <2 cm). Polyhydramnios is AFI >24 cm (or single deepest pocket >8 cm).

📘 Q96 (Biophysics) — The piezoelectric effect in ultrasound transducers refers to: A) The conversion of electrical energy to sound waves and vice versa B) The absorption of sound by tissue C) The reflection of ultrasound at tissue boundaries D) The scattering of sound by small particles E) The attenuation of ultrasound with depth

Answer: A

The piezoelectric effect is the property of certain crystals (e.g., lead zirconate titanate) to generate an electrical voltage when mechanically deformed, and conversely to deform (vibrate) when an electrical voltage is applied. This is the fundamental principle of ultrasound transducers — they both transmit (electrical→sound) and receive (sound→electrical) ultrasound waves.

📘 Q97 (Biophysics) — Which of the following imaging modalities uses ionising radiation? A) Ultrasound B) Magnetic resonance imaging C) Computed tomography (CT) D) Both A and B E) Neither A, B, nor C

Answer: C

CT uses X-rays (ionising radiation) to produce cross-sectional images. Ultrasound uses high-frequency sound waves (non-ionising). MRI uses powerful magnetic fields and radiofrequency pulses (non-ionising). Both ultrasound and MRI are safe in pregnancy when used appropriately. CT is reserved for specific indications due to radiation exposure, with abdominal shielding when possible.

📘 Q98 (Biophysics) — In the context of CTG interpretation, a sinusoidal pattern is most commonly associated with: A) Fetal sleep cycle B) Severe fetal anaemia C) Umbilical cord compression D) Maternal fever E) Normal fetal behaviour

Answer: B

A sinusoidal CTG pattern is a smooth, undulating waveform with a fixed frequency of 3–5 cycles per minute, absent variability, and no accelerations. It is most commonly associated with severe fetal anaemia (e.g., from haemolytic disease, fetomaternal haemorrhage, or twin-to-twin transfusion syndrome). It can also be seen with severe fetal hypoxia and is a pathological pattern requiring urgent evaluation.

📘 Q99 (Biophysics) — Attenuation of ultrasound in soft tissue is primarily due to: A) Specular reflection B) Absorption and scattering C) Refraction D) Diffraction E) Interference

Answer: B

Attenuation (reduction of sound wave intensity as it travels through tissue) is caused primarily by absorption (conversion of acoustic energy to heat) and scattering (redirection of sound waves in multiple directions). The attenuation coefficient in soft tissue is approximately 0.5–0.7 dB/cm/MHz, meaning higher frequencies attenuate more rapidly. This is why deep structures require lower frequencies.

📘 Q100 (Biophysics) — A non-stress test (NST) is considered reactive if, over a 20-minute period, there are: A) At least 2 accelerations of 15 bpm above baseline lasting 15 seconds B) At least 3 accelerations of 10 bpm above baseline lasting 10 seconds C) No decelerations D) Baseline variability > 10 bpm E) At least one fetal movement

Answer: A

A reactive NST (reassuring) requires at least 2 accelerations of ≥15 bpm above baseline lasting ≥15 seconds from 32 weeks' gestation. Before 32 weeks, criteria are often relaxed to 10 bpm × 10 seconds due to fetal neurological immaturity. A non-reactive NST requires further evaluation (BPP or contraction stress test). Fetal heart rate accelerations are a sign of an intact, well-oxygenated fetal autonomic nervous system.

End of Mock Exam 11

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