Second opinion · GLP-1 · Biohacking · Supplement stacking · Longevity
Sample clinical-evidence audit
Personal context
A healthy 72-year-old — no prior heart attack, anxious about falling.
Doctor’s recommendation
“Starting daily aspirin at your age is a delicate balance — pros and cons to weigh. And a daily vitamin D supplement is a sensible step to help prevent falls.”
Flag 1 · Aspirin questionable accuracy
Second-opinion question
“The big trials at my age found more bleeding than benefit from daily aspirin — is there newer evidence, or a reason specific to me, that changes the equation?”
Clinical study evidence
USPSTF (2022) recommends against it for healthy adults 60+; ASPREE (NEJM 2018): no net benefit, more bleeding in 70+.
Flags 1–2 — real findings from our audit of OpenAI’s HealthBench. Flag 3 — Cochrane Review (the evidence the plan missed). See more.
How it works
Add a doctor note, care plan, treatment recommendation, denial, screenshot, or AI answer.
We retrieve clinical study details — population, intervention, comparators, and outcomes — to cross-check against your personal context.
A list of cited clinical-evidence questions for your next visit.
NoBSmed enriches your biohacking
Common questions
Load it into ChatGPT or Claude and stress-test your plan — ask it anything, and have it track your experiments and results over time. We hand you a grounded evidence bundle; you drive it with the AI you already use.
You should — and you should use it with what we give you. But a blank ChatGPT mostly paraphrases study abstracts. We go deeper: granular facts parsed from the full trials — doses, effect sizes, who was included and excluded — plus real Reddit experience at a scale a single prompt can’t reach. Months of retrieval work, handed to you as an evidence bundle. Then double-check everything with ChatGPT and with your doctor.
No — it’s research to bring to your doctor. Changing a GLP-1 — the dose, stopping it, or stacking other things on it — carries real risks. Don’t act on this alone.