Each card is a real, de-identified care plan turned into an explicit causal map: what the plan targets, what it misses, and the evidence behind every flag. Open the full granular report for the detail — or take the portable evidence bundle into your own ChatGPT or Claude. Research and education, not medical advice. Names and identifying details removed.
Evidence audit · causal map
PCOS · insulin resistance · ADHD
A medication & supplement stack audited end-to-end — the audit finds the unmeasured root cause (insulin resistance) and questions a metformin removal.
The bundle is the machine-readable twin of this report — the same causal map and sourced findings, formatted to load into your own AI. Want an early copy? Ask us.
Evidence audit · causal map
Cholesterol & weight plan
A second-opinion prep for a lipid + weight-loss plan — the audit flags an at-goal LDL that may rebound, a dropped drug class, and the metabolic root nobody measured.
The bundle is the machine-readable twin of this report — the same causal map and sourced findings, formatted to load into your own AI. Want an early copy? Ask us.
Evidence audit · causal map
GLP-1 plan · OpenEvidence, enriched in ChatGPT
The OpenEvidence answer, then enriched in ChatGPT into a comprehensive plan — and the audit still finds the root nobody measured, a third of the loss coming out of muscle, an unscreened sleep apnea, an appetite suppressant already in use, and no exit plan.
His aim: use GLP-1 to reach 200 lb — and get his energy and ADHD focus back.
Implicit causal map · OpenEvidence’s plan
The bundle is the machine-readable twin of this report — the same causal map and sourced findings, formatted to load into your own AI. Want an early copy? Ask us.