Paeds Vivas · clinical-assessment-and-reasoning
Diagnostic test selection and Bayesian reasoning in paediatrics — branching viva
Branching viva on pre-test probability, likelihood ratios, selective paediatric testing, contaminated samples and residual-risk communication.
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Target exams
Station map
Branch A — High-risk neonate, reassuring marker
Examiner: A 14-day-old is poorly feeding and mottled. CRP is normal. The night team wants discharge because “the bloods are fine.” [7] [9]
Strong answer should include:
- Pre-test risk is high from age and physiology. [7] [9]
- Sensitivity/NPV language: a normal marker is not automatic rule-out. [1] [2]
- Post-test probability may remain above treatment or observation thresholds. [2] [4]
- Residual-risk plan: treat/observe, senior review, timed reassessment, family explanation. [4] [9]
Trap: equating one normal number with zero disease probability. [2] [9]
Branch B — Stable bronchiolitis and “just in case” imaging
Examiner: Classic bronchiolitis, stable. Registrar requests chest radiograph and full panel. [5] [8]
Strong answer should include:
- Clinical question already answered by history/examination for typical disease. [5]
- Routine radiograph often low value and can drive unnecessary treatment. [5] [8]
- Reopen testing if the question changes (focal signs, severe course, mismatch). [5]
- Stewardship without denying needed tests for true residual risk. [8]
Trap: protocol stacking as a substitute for Bayesian indication. [5] [8]
Branch C — Incidental adult-range laboratory flag
Examiner: Asymptomatic school-age child; adult reference interval flags a value high. [6]
Strong answer should include:
- Reinterpret with age-appropriate paediatric intervals. [6]
- Avoid cascade testing for a software-labelled “abnormal” that fits childhood physiology. [6] [8]
- Only investigate further if independent clinical concern exists. [8] [9]
Trap: treating laboratory flags as diagnoses. [6] [8]
Branch D — Appraisal probe
Examiner: A paper claims 99% sensitivity from ICU cases versus healthy controls. Can you use that number tonight? [10]
Strong answer should include:
- Spectrum bias and applicability concerns. [10]
- Need for STARD/QUADAS-style appraisal of selection, reference standard and flow. [10]
- Bedside use requires match to your patient spectrum and decision thresholds. [2] [3]
Closing synthesis the candidate should say
“I name the question and pre-test risk first. I order only discriminating tests. I update probability with the result. I always state residual risk, next action and safety-net.” [2] [4] [9]
References
- [1]Akobeng AK Understanding diagnostic tests 1: sensitivity, specificity and predictive values. Acta paediatrica (Oslo, Norway : 1992), 2007.PMID 17407452
- [2]Akobeng AK Understanding diagnostic tests 2: likelihood ratios, pre- and post-test probabilities and their use in clinical practice. Acta paediatrica (Oslo, Norway : 1992), 2007.PMID 17306009
- [3]Deeks JJ Diagnostic tests 4: likelihood ratios. BMJ (Clinical research ed.), 2004.PMID 15258077
- [4]Pauker SG The threshold approach to clinical decision making. The New England journal of medicine, 1980.PMID 7366635
- [5]Schuh S Evaluation of the utility of radiography in acute bronchiolitis. The Journal of pediatrics, 2007.PMID 17382126
- [6]Adeli K The Canadian laboratory initiative on pediatric reference intervals: A CALIPER white paper. Critical reviews in clinical laboratory sciences, 2017.PMID 29017389
- [7]Burstein B Prediction of Bacteremia and Bacterial Meningitis Among Febrile Infants Aged 28 Days or Younger. JAMA, 2026.PMID 41359314
- [8]Størdal K Overtesting and overtreatment-statement from the European Academy of Paediatrics (EAP). European journal of pediatrics, 2019.PMID 31506723
- [9]Bordini BJ Overcoming Diagnostic Errors in Medical Practice. The Journal of pediatrics, 2017.PMID 28336147
- [10]Whiting PF QUADAS-2: a revised tool for the quality assessment of diagnostic accuracy studies. Annals of internal medicine, 2011.PMID 22007046