Illustrative AI review sample — cardiology

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Key Points

1Nationwide Taiwan NHI claims cohort showing lower incident heart failure with NOACs versus warfarin in ≥65-year-old patients with AF and diabetes; target trial emulation strengthens causal inference but residual channelling bias, active-comparator design considerations, and HbA1c confounding remain unaddressed.

Major Issues

Methods: Prevalent NOAC users are included alongside incident initiators; this violates the new-user active-comparator design principle and introduces depletion-of-susceptibles bias, as patients who have already tolerated their anticoagulant for months differ systematically from new initiators.

Methods: HbA1c and left ventricular ejection fraction (LVEF) are not available in claims data and are omitted from the propensity model; since glycaemic control drives both anticoagulant choice (HbA1c instability favours warfarin avoidance) and HF risk, this unmeasured confounding inflates the apparent NOAC benefit.

Results: The 4:1 NOAC-to-warfarin ratio reflects post-2015 prescribing shifts; a secular time-trend analysis is not performed, leaving open the possibility that calendar-time confounding (improving overall cardiovascular care) explains part of the NOAC advantage.

Discussion: No E-value or quantitative bias analysis is provided for the primary HR 0.80; the minimum unmeasured confounding required to shift the lower CI above 1.0 should be reported to help readers gauge robustness.

Priority Action Plan

HIGH IMPACT

Problem

Implement new-user active-comparator design (12-month washout) as the primary analysis to eliminate depletion-of-susceptibles bias.

Why it matters

Prevalent user inclusion is a well-known source of bias in pharmacoepidemiological comparisons and is the primary critique expected from methodologically sophisticated reviewers.

Suggested fix

Implement new-user active-comparator design (12-month washout) as the primary analysis to eliminate depletion-of-susceptibles bias.

HIGH IMPACT

Problem

Report E-values for the primary HR and lower CI; conduct negative control outcome analysis to verify adequacy of propensity weighting.

Why it matters

Demonstrates robustness of the causal claim against unmeasured confounding — required at cardiological pharmacoepidemiology journals.

Suggested fix

Report E-values for the primary HR and lower CI; conduct negative control outcome analysis to verify adequacy of propensity weighting.

MEDIUM IMPACT

Problem

Add calendar-year period as a covariate or conduct year-stratified analyses to rule out secular-trend confounding.

Why it matters

The 2012–2019 period spans major changes in NOAC prescribing and cardiovascular care quality; disentangling these from the pharmacological effect is essential.

Suggested fix

Add calendar-year period as a covariate or conduct year-stratified analyses to rule out secular-trend confounding.

Quick win: The target trial emulation framework is a genuine strength. Focus revisions on implementing new-user design, providing E-values for robustness, and addressing calendar-time confounding. These changes would make the causal inference case substantially stronger for high-impact cardiology journals.

Risk of heart failure in elderly patients with atrial fibrillation and diabetes taking different oral anticoagulants: a nationwide cohort study

Key Points

Major Issues

Priority Action Plan

Why it matters

Why it matters

Why it matters