Clinical Decision Support

Generate professional clinical decision support documents with GRADE evidence grading and statistical analysis for cardiology content.

Triggers

• User needs evidence-based treatment recommendations
• User is creating clinical guideline summaries
• User wants to analyze patient cohort data
• User needs to present evidence with GRADE grading
• User is developing clinical algorithms

Document Types

1. Treatment Recommendation Reports

Structure:

1. Clinical question (PICO format)
2. Evidence summary
3. GRADE assessment
4. Recommendation statement
5. Implementation considerations

GRADE Evidence Levels:

2. Patient Cohort Analysis

Components:

• Demographics and baseline characteristics
• Biomarker stratification
• Outcome comparisons with statistics
• Subgroup analyses
• Clinical implications

3. Guideline Summaries

Elements:

• Recommendation class (I, IIa, IIb, III)
• Level of evidence (A, B, C)
• Key supporting trials
• Clinical context
• Special populations

Cardiology-Specific Applications

Heart Failure Management

• GDMT optimization pathways
• Device therapy eligibility
• Risk stratification (MAGGIC, Seattle HF Model)
• Stage-based recommendations

Coronary Artery Disease

• Revascularization decisions
• Medical therapy optimization
• Risk scores (SYNTAX, HEART, TIMI)
• Secondary prevention

Arrhythmia Management

• Anticoagulation decisions (CHA₂DS₂-VASc)
• Rate vs rhythm control
• Device therapy indications
• Ablation candidacy

Valvular Heart Disease

• Intervention timing
• Surgical vs transcatheter approach
• Risk assessment (STS, EuroSCORE)
• Surveillance recommendations

Statistical Presentation

Required Elements

• Hazard ratios with 95% CI
• Absolute risk differences
• Number needed to treat (NNT)
• P-values (exact, not just thresholds)
• Forest plots for multiple comparisons

Survival Analysis Display

• Kaplan-Meier curves
• Number at risk tables
• Median survival with CI
• Landmark analyses if appropriate

Evidence Synthesis Framework

For Single Trial

1. Study design and population
2. Intervention and comparator
3. Primary endpoint results
4. Key secondary endpoints
5. Safety profile
6. Limitations
7. Clinical implications

For Multiple Trials

1. Consistency of findings
2. Magnitude of effect across studies
3. Population differences
4. Statistical heterogeneity
5. Overall certainty assessment
6. Synthesized recommendation

GRADE Assessment Process

Factors That Lower Certainty

• Risk of bias (unblinded, high dropout)
• Inconsistency (heterogeneous results)
• Indirectness (surrogate outcomes, different population)
• Imprecision (wide CIs, few events)
• Publication bias

Factors That Raise Certainty

• Large effect (RR >2 or <0.5)
• Dose-response gradient
• All plausible confounders would reduce effect

Output Formatting

Executive Summary (Always First)

• 3-5 key findings highlighted
• Primary recommendation
• Evidence grade
• Clinical bottom line

Recommendation Statement Format

We recommend [intervention] for [population] with [condition]
to [outcome] (GRADE 1B: strong recommendation, moderate certainty).

Supporting evidence: [Key trials with effect sizes]

Best Practices

1. Specify patient population precisely
2. Use standardized outcome definitions (RECIST, CTCAE, etc.)
3. Report both relative and absolute effects
4. Include number at risk for survival data
5. Acknowledge funding sources of cited trials
6. Note guideline concordance/discordance
7. Address special populations (elderly, renal impairment, etc.)

NOT For

This skill is NOT for individual patient treatment decisions. For that, clinical judgment integrating patient preferences, comorbidities, and circumstances is required beyond evidence synthesis.