BPC-157 trial data vs stacking logs — what gives?

The 120 listing is the one I want unblinded.

The part people forget with a BPC-157 + GHK-Cu stack for a tendon flare: it's easy to track pain on stairs and morning stiffness, and both can improve — but if sleep and load changed in the same window, the stack can't take the credit. Worth knowing before comparing options or reading anyone's "this fixed me" post.

Anecdotes aren’t data, but neither is an empty results field. The rotator cuff trial at 30 is too small for the claims people make.

I went down the same rabbit hole and the part that broke my brain was realizing the trials aren't measuring the thing I actually care about — I don't need a CRP number, I need to know if I can carry two grocery bags up my stairs without stopping halfway.

So my version of a spreadsheet is embarrassingly low-tech: a wall calendar where I write one number a week, my stair test, how many flights before my knee starts talking. Week one was half a flight.

Week six I did three and forgot to count, and honestly that was the real data point. The weird thing was that the weeks I felt worst subjectively were often the weeks the stair number went up, which made me trust the objective check way more than the vibe.

Curious if anyone else tracks a functional test instead of labs, because I think that's where the actual signal lives.

Quick question back — what are the columns in your spreadsheet? Mine started with about thirty and I used four. If you're pulling trial entries, are you logging the population (post-op vs tendinopathy vs healthy desk-worker shoulders) or just the n?

Lumping those feels like half the reason the stacking threads read louder than anything the data can support.

I built a 47-row tracker with drop-downs for sleep, soreness 1-10, and a photo folder, and quit it by day 19. What actually stuck was a paper calendar with three marks: green dot (moved well), gray dot (meh), and a circle on any night under six hours.

Nine weeks later the pattern was stupidly obvious — gray dots clustered two days after the circled dates, basically every time. No lab panel would have shown me that.

So my contrarian take is the thin trial data matters less than people think, because a lot of what we're chasing is a lagged sleep-and-stress effect a two-dollar calendar catches fine.

The catch is everybody's capturing different variables, so the stacking logs can't really be pooled either. Same problem, different scale.

Weekends are where every tracking attempt of mine died — five decent days, then Saturday errands and restaurant food, and by Sunday night I'd decided the whole week was a wash so why log it.

Now I only weigh Monday and Friday and compare those two numbers instead of the daily noise. Sounds dumb but it killed the spiral.

@well_sanne said:

by Sunday night I'd decided the whole week was a wash so why log it

See, that's the exact thing that got me too, just on a different clock. Two and a half inches off my waist in nine days, then 1.4 back on by day fourteen, and that bounce is why I stopped treating single readings as signal.

Now I measure at the navel every Sunday morning before I drink anything and I only care about the four-week average. Trial data is thin for the same reason my log was noisy: the real changes are slow and the fast ones are mostly fluid.

I went the opposite direction and tracked almost nothing for six weeks, no app, no rows, just the same two meals on repeat and a Wednesday walk. Lost 9 lbs and a belt notch.

Weird part is my stress dropped more than my weight did, and I quit the 9pm snacking without ever deciding to. Sometimes the log itself is the stress.

Full disclosure, New here, week one, so take this with a grain of salt. The trial/anecdote gap bugs me too. One thing I’ve started doing is a tiny “first steps” log: pain score when I get out of bed, hours slept, and whether I did my boring PT exercises.

After two weeks, my best mornings lined up with good sleep and actually doing the exercises, not with any stack changes. Which makes me wonder — for folks who stack, how do you separate real recovery from normal healing plus better sleep and more movement?

Not trying to dunk on logs, just genuinely curious how people control for that.

What’s the primary endpoint in those stacking logs? “Recovery” is doing a lot of unpaid labor there. I tried logging a rehab block with four columns: pain 0–10, sleep hours, whether I did the exercises, and one objective lift.

The only things that correlated with feeling better were sleep and actually doing the exercises, which is annoyingly unpatentable. Trial registries are thin because soft endpoints are noisy and everyone’s protocol is different.

If you’re already tracking trial entries, add “primary outcome” and “who funded it” columns. That usually explains the silence faster than any mechanism thread.

I’m six months into post-kids life: daily walks, actually using the kitchen, and a spreadsheet that started out optimistic. What helped me was tracking function, not feeling. Could I carry both grocery bags from the car? Did I take the long loop

The trial data is thin because BPC isn’t really studied as a gym-recovery drug — endpoints are usually imaging/function in diagnosed injuries, not “my shoulder felt better.” That’s a different question than stacking logs answer. My own n=1: I track sleep, protein, and estimated 1RM.

When I started a recovery kick, lifts went up, but I was also sleeping 8+ and eating in a surplus. Without a control, I can’t attribute anything.

Sharp q: does that 120-person listing have a placebo arm and a pre-registered primary endpoint? If not, it won’t settle your spreadsheet.

Tbh I’ve had the same frustration. The trials I can find seem to use pain scores or ultrasound, not hard functional endpoints, so a positive anecdote could just be less pain rather than faster healing.

What I’d want from stacking logs: a baseline and 4-week objective measure—single-leg sit-to-stand time, shoulder external rotation ROM, grip dynamometer. I started noting pain 0–10 plus how many bodyweight squats before my form breaks.

Not proof, but it separates “felt better” from “did more.” Has anyone actually logged a strength or ROM number alongside the vibes?

I keep a similar tab: registry status, enrollment, whether results ever got posted, and any linked paper. “Completed” just means the last visit happened, not that data dropped.

The stacking logs I can actually parse have dates, sleep/steps, and a before/after pain or range-of-motion score—not just “felt great.” What columns are you using? I’ve started adding shipment lag and whether the package arrived cold, because if that varies batch to batch, anecdotes get muddy fast.

Also search PubMed by the investigators listed on the NCT pages; sometimes the results live there instead. Not glamorous, but it’s the only way I can compare anything.

Tbh, one thing I’d add: on ClinicalTrials.gov, “completed” just means the study ended, not that results are available. Results are supposed to be posted within a year for many interventional trials, but small academic or sponsor-run studies often skip it or only show up in a paper years later.

Have you checked the record’s Results tab plus the sponsor’s publication list, not just PubMed? Europe PMC and Google Scholar by investigator name can catch stuff too.

If all of those are still empty, that’s a real signal—especially next to the pile of animal work. What’s the ratio in your spreadsheet between registered human trials and published human results?

Just my experience, I’ve kept a maintenance log for two years, and the pattern I trust is boring: sleep, protein, and not stacking new variables. What bugs me about the BPC-157 stacking posts is they rarely control for the obvious confounder—most people chasing recovery are also in a calorie deficit or just started training again.

In my own sheet, every “miracle” stretch lined up with a deload week, not a supplement. When I tightened protein and sleep, recovery got steadier; when I added three changes at once, I couldn’t tell what did anything.

Sharp question for OP: are any of those stacking logs recording weekly intake or training load alongside the peptide? If not, they’re basically anecdote plus optimism.

I did the same with those NCT rows and noticed the “completed” one has a completion date but no posted results — that’s not the same as a null result. My own log has columns for baseline function, sleep, and training load, because stacking reports usually leave those out and recovery looks cleaner than it is.

Are you counting only trials with results posted, or completed status too? That denominator changes everything.

The registry stuff being thin doesn’t shock me — trials usually have prespecified endpoints, and “recovery feels obvious” isn’t one. One concrete thing I do with any log that looks too clean: tally whether each entry has a baseline objective measure (imaging, PT range-of-motion,