Apply the GRADE framework to assess certainty of evidence in systematic reviews...
This skill teaches the GRADE (Grading of Recommendations Assessment, Development and Evaluation) framework for assessing certainty of evidence.
GRADE is the internationally recognized standard for rating the quality of evidence in systematic reviews. It provides a systematic approach to moving from evidence to recommendations.
Activate this skill when users:
| Level | Symbol | Meaning |
|---|---|---|
| High | āāāā | Very confident the true effect is close to the estimate |
| Moderate | āāā⯠| Moderately confident; true effect likely close to estimate |
| Low | āāāÆāÆ | Limited confidence; true effect may be substantially different |
| Very Low | āāÆāÆāÆ | Very little confidence; true effect likely substantially different |
| Study Design | Starting Certainty |
|---|---|
| Randomized trials | High (āāāā) |
| Observational studies | Low (āāāÆāÆ) |
What to assess:
When to downgrade:
Socratic Questions:
What to assess:
When to downgrade:
Key Teaching Point: "Inconsistency is different from imprecision. Inconsistency means studies disagree; imprecision means we're uncertain about each estimate."
Types of indirectness:
| Type | Example |
|---|---|
| Population | Studies in adults, question about children |
| Intervention | Studies of drug A, question about drug B |
| Comparator | Studies vs. placebo, question vs. active treatment |
| Outcome | Studies measure surrogate, question about clinical outcome |
When to downgrade:
What to assess:
Rules of thumb:
When to downgrade:
What to assess:
When to downgrade:
Only for observational studies starting at Low
| Magnitude | Upgrade |
|---|---|
| RR > 2 or < 0.5 | Consider +1 |
| RR > 5 or < 0.2 | Consider +2 |
Step 1: Define the Question (PICO)
ā
Step 2: Identify Study Designs
ā
āāā RCTs ā Start at HIGH
āāā Observational ā Start at LOW
ā
Step 3: Assess Downgrade Factors
ā
āāā Risk of Bias?
āāā Inconsistency?
āāā Indirectness?
āāā Imprecision?
āāā Publication Bias?
ā
Step 4: Assess Upgrade Factors (if observational)
ā
āāā Large Effect?
āāā Dose-Response?
āāā Confounding?
ā
Step 5: Determine Final Rating
ā
Step 6: Write Certainty Statement
| Outcome | ā of studies (participants) | Certainty | Relative effect (95% CI) | Anticipated absolute effects |
|---|---|---|---|---|
| Mortality | 5 RCTs (2,340) | āāā⯠Moderate | RR 0.75 (0.60-0.94) | 50 fewer per 1000 (from 80 fewer to 12 fewer) |
# From relative risk
baseline_risk <- 0.20 # 20% in control group
RR <- 0.75
RR_lower <- 0.60
RR_upper <- 0.94
# Absolute risk reduction
ARR <- baseline_risk * (1 - RR) # 5% = 50 per 1000
ARR_lower <- baseline_risk * (1 - RR_upper)
ARR_upper <- baseline_risk * (1 - RR_lower)
High certainty: "We are very confident that the true effect lies close to that of the estimate of the effect."
Moderate certainty: "We are moderately confident in the effect estimate: The true effect is likely to be close to the estimate of the effect, but there is a possibility that it is substantially different."
Low certainty: "Our confidence in the effect estimate is limited: The true effect may be substantially different from the estimate of the effect."
Very low certainty: "We have very little confidence in the effect estimate: The true effect is likely to be substantially different from the estimate of effect."
"What exactly are we trying to answer? Let's define:
"What studies do we have?
"Let's go through each GRADE domain:
"Based on our assessment:
"Now let's write what this means for decision-makers..."
Double-counting
Automatic downgrading
Ignoring context
Forgetting outcomes
Basic: "RCTs start at what GRADE certainty level?"
Intermediate: "I² = 70% with studies showing effects in opposite directions. Which domain is affected?"
Advanced: "Studies are in adults but your question is about children. The intervention and outcomes are the same. What domain and how much to downgrade?"
meta-analysis-fundamentals - Understanding effect sizesheterogeneity-analysis - Assessing inconsistencypublication-bias-detection - One of the GRADE domainsGlass (the teaching agent) MUST adapt this content to the learner:
Example Adaptations: