Evidence-Based Medicine and Research in Anaesthesia

Quick Answer

Evidence-based medicine (EBM) integrates individual clinical expertise with the best available external clinical evidence from systematic research. Hierarchy of evidence: Systematic reviews and meta-analyses of RCTs (highest) > individual RCTs > cohort studies > case-control studies > case series > expert opinion (lowest). Study designs: Randomized controlled trials (RCTs) minimize bias through randomization and blinding; cohort studies (prospective/retrospective) observe outcomes without intervention; case-control studies (retrospective, odds ratios) useful for rare diseases; cross-sectional studies (prevalence); qualitative research (exploratory). Statistical concepts: Relative risk (RR), odds ratio (OR), number needed to treat (NNT = 1/absolute risk reduction), confidence intervals, p-values, power, sample size. Critical appraisal: Validity (internal validity - bias control; external validity - generalizability), importance (clinical significance), applicability (to your patient). Research ethics: ANZCA Research Committee approval, Human Research Ethics Committee (HREC), informed consent, data safety monitoring, Good Clinical Practice (GCP). [1-10]

Evidence Hierarchy

Levels of Evidence

Level I (Highest):

• Systematic reviews and meta-analyses of randomized controlled trials (RCTs)
• High-quality RCTs with narrow confidence intervals

Level II:

• Systematic reviews of cohort studies
• Individual cohort studies with concurrent controls
• Low-quality RCTs (e.g., <80% follow-up, no blinding)

Level III:

• Systematic reviews of case-control studies
• Individual case-control studies
• Retrospective cohort studies
• Ecological studies

Level IV:

• Case series (without control group)
• Case reports
• Expert opinion based on bench research

Level V (Lowest):

• Expert opinion without explicit critical appraisal
• Based on physiology or "first principles"

Systematic Reviews and Meta-Analyses

Systematic Review:

• Definition: Rigorous, transparent synthesis of all relevant studies on specific question
• Method: Explicit search strategy, inclusion/exclusion criteria, quality assessment
• Advantage: Reduces bias compared to narrative reviews

Meta-Analysis:

• Definition: Statistical pooling of results from multiple studies
• Outcome: Single estimate of effect with increased precision
• Heterogeneity:
• Statistical (I² statistic): 0-25% (low), 25-50% (moderate), 50-75% (substantial), >75% (considerable)
• Clinical: Differences in populations, interventions, outcomes
• Methodological: Study quality differences
• Forest plot: Visual representation of individual and pooled results
• Funnel plot: Assesses publication bias (asymmetry suggests missing negative studies)
• Fixed vs random effects: Fixed assumes one true effect; random assumes distribution of effects

Cochrane Collaboration:

• International organization producing high-quality systematic reviews
• Methodologically rigorous
• Regular updates

Study Designs

Randomized Controlled Trials (RCTs)

Design:

• Randomization: Allocates participants to intervention or control by chance
• Minimizes selection bias
• Balances known and unknown confounders
• Methods: Simple randomization, blocked, stratified, cluster
• Control group: Standard care, placebo, or no intervention
• Blinding:
• Single: Patient unaware of allocation
• Double: Patient and assessor unaware
• Triple: Patient, assessor, statistician unaware
• Allocation concealment: Prevents foreknowledge of assignment (central randomization, sealed envelopes)

Analysis:

• Intention-to-treat (ITT): Analyze all participants in originally assigned groups (conservative, preserves randomization)
• Per-protocol: Analyze only completers (biased if dropouts differ)
• As-treated: Analyze according to actual treatment received (biased)

Advantages:

• Minimizes confounding and bias
• Causality can be inferred
• Gold standard for therapeutic interventions

Limitations:

• Expensive, time-consuming
• May lack external validity (highly selected populations)
• Ethical constraints (cannot randomize harm)
• Short follow-up often

Key Appraisal Questions:

1. Was randomization truly random?
2. Was allocation concealed?
3. Were groups similar at baseline?
4. Was blinding adequate?
5. Was follow-up complete?
6. Was ITT analysis used?

Cohort Studies

Prospective Cohort:

• Design: Expose groups defined by exposure, follow forward for outcomes
• Example: "Does smoking cause lung cancer?" Follow smokers and non-smokers
• Analysis: Relative risk (RR), incidence rates
• Advantages: Can assess multiple outcomes, good for common outcomes
• Disadvantages: Expensive, time-consuming, loss to follow-up

Retrospective Cohort:

• Design: Look back at existing records to define exposure and outcome
• Example: Review medical records of patients who received drug X vs Y
• Advantages: Quick, inexpensive
• Disadvantages: Limited data quality, selection bias

Key Measures:

• Relative Risk (RR): Incidence in exposed / Incidence in unexposed
• RR = 1: No association
• RR > 1: Increased risk
• RR < 1: Decreased risk (protection)
• Attributable Risk: Incidence in exposed - Incidence in unexposed
• Population Attributable Risk: Proportion of disease in population due to exposure

Case-Control Studies

Design:

• Cases: People with outcome (disease)
• Controls: People without outcome (matched)
• Look back: Determine prior exposure
• Example: "Do oral contraceptives cause DVT?" Compare OC use in DVT patients vs controls

Analysis:

• Odds Ratio (OR): Odds of exposure in cases / Odds of exposure in controls
• OR approximates RR when disease rare
• OR = 1: No association
• OR > 1: Increased odds
• OR < 1: Decreased odds

Advantages:

• Efficient for rare diseases
• Quick, inexpensive
• Can study multiple exposures

Disadvantages:

• Cannot calculate incidence or prevalence
• Prone to bias (recall, selection)
• Temporal ambiguity (exposure before outcome?)

Other Study Designs

Cross-Sectional Studies:

• Design: Snapshot in time - exposure and outcome measured simultaneously
• Use: Prevalence studies
• Limitation: Cannot determine causality

Case Series/Reports:

• Design: Description of single or series of cases
• Use: Hypothesis generation, rare events
• Limitation: No control, no inference

Qualitative Research:

• Methods: Interviews, focus groups, observation
• Use: Understanding experiences, beliefs, behaviors
• Analysis: Thematic analysis, grounded theory
• Rigor: Trustworthiness (credibility, transferability, dependability, confirmability)

Statistical Concepts

Measures of Effect

Absolute Risk Reduction (ARR):

• Definition: Risk in control - Risk in treatment
• Example: Control event rate 10%, treatment 6% → ARR = 4%

Relative Risk Reduction (RRR):

• Definition: (Risk control - Risk treatment) / Risk control
• Example: (10% - 6%) / 10% = 40%

Number Needed to Treat (NNT):

• Definition: 1 / ARR
• Interpretation: Number of patients to treat to prevent one adverse outcome
• Example: ARR 4% → NNT = 25
• Number Needed to Harm (NNH): For adverse effects

Relative Risk (RR):

• Definition: Risk exposed / Risk unexposed
• Example: 2.0 means twice the risk

Odds Ratio (OR):

• Definition: (a×d) / (b×c) from 2×2 table
• Interpretation: Similar to RR when outcome rare

Statistical Significance vs Clinical Importance

P-value:

• Definition: Probability of observing data if null hypothesis true
• Conventional threshold: p < 0.05 (statistically significant)
• Limitations:
• Depends on sample size (large N → trivial differences significant)
• Does not indicate clinical importance
• 1 in 20 chance of false positive

Confidence Intervals (CI):

• Definition: Range within which true effect likely lies (usually 95%)
• Interpretation: Narrow CI = precise estimate; wide CI = imprecise
• If CI includes null value (1.0 for RR/OR): Not statistically significant
• Advantage over p-value: Shows precision and range of plausible values

Clinical vs Statistical Significance:

• Statistically significant ≠ clinically important
• Small effect with large N may be significant but meaningless
• Large effect with small N may not reach significance

Power and Sample Size

Power (1-β):

• Definition: Probability of detecting true effect if it exists
• Conventional: 80% or 90%
• β: Probability of Type II error (false negative)

Type I and Type II Errors:

• Type I (α): False positive (conclude treatment works when it doesn't)
• α usually set at 0.05 (5% chance)
• Type II (β): False negative (miss true treatment effect)
• β usually set at 0.20 (20% chance)

Sample Size Calculation:

• Factors:
• Power desired (usually 80%)
• Significance level (usually 0.05)
• Expected effect size (minimum clinically important difference)
• Variability (standard deviation)
• Event rate in control group
• Underpowered studies: Risk of false negative, waste of resources

Statistical Tests

Comparing Means:

• T-test: Two groups (paired or unpaired)
• ANOVA: Three or more groups
• Mann-Whitney U / Wilcoxon: Non-parametric (data not normally distributed)

Comparing Proportions:

• Chi-squared: Two or more groups
• Fisher's exact: Small expected cell counts

Correlation and Regression:

• Pearson r: Linear relationship (parametric)
• Spearman rho: Rank correlation (non-parametric)
• Linear regression: Predict continuous outcome
• Logistic regression: Predict binary outcome
• Cox proportional hazards: Survival analysis

Survival Analysis:

• Kaplan-Meier: Survival probability over time
• Log-rank test: Compare survival curves
• Hazard ratio: Instantaneous risk

Critical Appraisal

CASP (Critical Appraisal Skills Programme) Tools

For Systematic Reviews:

1. Did the review address clearly focused question?
2. Did authors look for right type of papers?
3. Do you think important relevant studies were included?
4. Was quality assessment of studies rigorous?
5. If results combined, was it reasonable?
6. What are overall results?
7. How precise are results?
8. Can results be applied to local population?
9. Were all important outcomes considered?
10. Are benefits worth harms and costs?

For RCTs:

1. Did trial address clearly focused issue?
2. Was assignment to treatment randomized?
3. Were all participants who entered accounted for?
4. Were participants, staff, and clinicians blinded?
5. Were groups similar at start?
6. Aside from experimental intervention, were groups treated equally?
7. How large was treatment effect?
8. How precise was estimate of treatment effect?
9. Can results be applied in your context?
10. Were all clinically important outcomes considered?
11. Are benefits worth harms and costs?

Validity, Importance, Applicability

Internal Validity:

• Definition: Truthfulness for this specific study
• Threats: Bias (selection, performance, detection, attrition, reporting)
• Assessment: Study design, conduct, analysis

External Validity (Generalizability):

• Definition: Can results be applied to other populations/settings?
• Factors: Study population, setting, intervention, outcomes
• Relevance: Similar to your patients?

Clinical Importance:

• Magnitude of effect: Large enough to matter to patients?
• NNT/NNH: Practical for clinical use?
• Outcomes measured: Patient-important outcomes (mortality, QoL) vs surrogate?

Applicability to Your Patient:

• Similar to study population?
• Likely benefits vs harms?
• Patient values and preferences?

Research in Anaesthesia

ANZCA Research Requirements

Fellowship Training:

• Research component: All trainees must complete research training
• Options:
• Formal research project (prospective study, systematic review, etc.)
• Research methodology course + critical appraisal
• ANZCA Research Committee: Oversees research activities

Conducting Research

Study Protocol:

• PIPER format:
• Population: Who studied?
• Intervention: What done?
• Comparison: Control group?
• Outcome: What measured?
• Timeframe: Duration?

Ethics Approval:

• Human Research Ethics Committee (HREC): Mandatory for human research
• ANZCA Research Committee: College oversight
• Multi-center research: Lead site + participating sites

Trial Registration:

• Mandatory: All clinical trials must be registered before enrollment
• Australian New Zealand Clinical Trials Registry (ANZCTR): Primary registry
• International: clinicaltrials.gov
• Publication requirement: Journals require registration

Informed Consent:

• Elements: Purpose, procedures, risks/benefits, alternatives, confidentiality, voluntary, questions
• Capacity: Patient must understand and retain information
• Documentation: Written consent usually required
• Exceptions: Emergency research (community consultation, delayed consent)

Data Safety Monitoring:

• DSMB (Data Safety Monitoring Board): Independent committee for large trials
• Interim analyses: Stopping rules for efficacy or harm
• Adverse event reporting: Timely to ethics and regulatory bodies

Good Clinical Practice (GCP):

• International standard: Ethical and scientific quality standards
• Principles:
• Trial conducted per protocol
• Data accurate and verifiable
• Rights and safety of subjects protected
• Compliance with regulatory requirements

Research Ethics

Declaration of Helsinki:

• World Medical Association: Ethical principles for medical research
• Key principles:
• Research must be justified
• Risks proportionate to benefits
• Informed consent required
• Privacy and confidentiality protected
• Vulnerable populations protected

National Statement on Ethical Conduct in Human Research (NHMRC):

• Australian document: Governs all human research in Australia
• Values: Research merit and integrity, justice, beneficence, respect

Conflict of Interest:

• Definition: Financial or other interests that could influence research
• Disclosure: Mandatory in publications, presentations, ethics applications
• Management: Recusal, independent oversight

Research Misconduct

Fabrication:

• Making up data or results

Falsification:

• Manipulating research materials, equipment, processes
• Changing or omitting data

Plagiarism:

• Appropriating another person's ideas, processes, results, or words without giving credit

Consequences:

• Institutional sanctions
• Loss of registration/funding
• Criminal charges (fraud)
• Reputational damage

Publishing Research

Authorship Criteria (ICMJE):

1. Substantial contributions to conception/design, data acquisition, analysis, interpretation
2. Drafting or critically revising for intellectual content
3. Final approval of version published
4. Agreement to be accountable for accuracy and integrity

Not authors: Technical help, writing assistance, funding acquisition, general supervision

Acknowledgments: Contributors who don't meet authorship criteria

Peer Review:

• Process: Anonymous evaluation by experts
• Types: Single-blind, double-blind, open
• Purpose: Quality control, improve manuscripts

Predatory Journals:

• Characteristics: Fake peer review, rapid acceptance, high fees, low quality
• Avoid: Check Beall's List, DOAJ, think.Check.Submit

Indigenous Research Ethics

Aboriginal and Torres Strait Islander Research

NHMRC Guidelines:

• Values and Ethics: Guidelines for research with Aboriginal and Torres Strait Islander peoples
• Key principles:
• Spirit and integrity
• Reciprocity
• Respect
• Equality
• Survival and protection
• Responsibility

Community Engagement:

• Essential: Research must benefit community
• Consultation: Early and ongoing with community
• Approval: Community endorsement beyond individual consent
• Indigenous researchers: Involvement in conduct and analysis
• Data governance: Community control over data

Māori Research Ethics

Health Research Council:

• Te Ara Tika: Guidelines for Māori health research
• Principles:
• Whakapapa (relationships)
• Tika (research design)
• Manaakitanga (cultural respect)
• Mana (recognition of leaders)

Whānau Consent:

• Family involvement in research decisions
• Collective benefit and protection

ANZCA Final Exam Focus

SAQ Patterns

Common Questions:

• "Describe the hierarchy of evidence."
• "What are the features of a well-conducted randomized controlled trial?"
• "Explain the difference between relative risk and absolute risk reduction."
• "How would you calculate sample size for a clinical trial?"

Marking Scheme Priorities:

• Evidence hierarchy (systematic reviews > RCTs > cohort > case-control)
• RCT design elements (randomization, blinding, allocation concealment, ITT analysis)
• Statistical measures (RR, OR, ARR, NNT, NNH)
• Critical appraisal (validity, importance, applicability)
• Research ethics (informed consent, ethics approval, trial registration)

Viva Scenarios

Scenario 1: Interpreting a Trial

• Presented with study results
• Calculate NNT from given data
• Assess validity (was randomization adequate?)
• Determine applicability to your patient

Scenario 2: Study Design

• Design study to answer clinical question
• Choose appropriate study type
• Describe how to minimize bias
• Calculate sample size

Scenario 3: Ethics

• Research scenario with ethical dilemma
• Apply Declaration of Helsinki principles
• Discuss consent in emergency research
• Manage conflict of interest

Key Points for Examination Success

1. Evidence hierarchy: Systematic reviews and meta-analyses of RCTs = highest
2. RCT gold standard: Randomization, blinding, allocation concealment, ITT analysis
3. NNT: 1/ARR (number needed to treat to prevent one event)
4. Power: Usually 80%, determines sample size
5. Confidence intervals: More informative than p-values (show precision)
6. Research ethics: HREC approval, informed consent, trial registration mandatory
7. Indigenous research: Community engagement, benefit sharing, data sovereignty
8. Critical appraisal: Validity (internal and external), importance, applicability
9. Study design choice: RCT for therapy, cohort for etiology, case-control for rare disease
10. Statistical vs clinical significance: Not the same thing

References

1. ANZCA. Research Training Handbook. 2023.
2. NHMRC. National Statement on Ethical Conduct in Human Research. 2018.
3. Straus SE et al. Evidence-Based Medicine. 5th ed. Churchill Livingstone; 2019.
4. Guyatt G et al. Users' Guides to the Medical Literature. 3rd ed. McGraw-Hill; 2015.
5. CASP. Critical Appraisal Skills Programme Checklists. Available at: casp-uk.net
6. Schulz KF et al. CONSORT 2010 Statement. BMJ. 2010;340:c332.
7. Moher D et al. PRISMA Statement. PLoS Med. 2009;6(7):e1000097.
8. NHMRC. Values and Ethics: Guidelines for Research with Aboriginal and Torres Strait Islander Peoples. 2018.