What GLP-1 Users Actually Report: Side-Effect Mentions in Our Community Corpus

Our first two pieces in this series covered what clinical sources say about GLP-1 side effects: which effects have enough evidence to calibrate a statistical model, and the pooled clinical rate for each. This one is about the other track of Magistra's real-world evidence database: what people actually taking these medications talk about, counted rather than anecdotally quoted.

> Correction, 29 August 2026. This article was published on 24 August with a pool of 185 community reports. On 29 August we found that our Reddit collector's subreddit restriction was not holding: it searched generic symptom words ("nausea vomiting", "gallbladder", "constipation diarrhea") and stored whatever the search returned, from anywhere on Reddit, while labelling each post with the subreddit we had queried rather than the one it was actually in. 159 of the 185 reports were posts from communities we never collect from — r/gallbladders, r/AskDocs, r/pregnant, r/HyperemesisGravidarum — where a nausea post is pregnancy nausea, not a GLP-1 report. Every figure below has been recomputed over the 26 reports that genuinely come from the GLP-1, weight-management and diabetes communities we collect from, and one of this article's original findings did not survive it (noted in place). The mislabelling is fixed at the collector, and the corrected labels are live in the public API.

> Restated, 25 September 2026. The 29 August screen admitted a Reddit post only from the 16 subreddits our collector was configured for. That also excluded 16 reports from ten communities that are plainly about GLP-1 drugs — r/mounjarouk, r/TirzepatideRX, r/Retatrutide, r/RetatrutideTalk, r/GLP1India, r/CompoundedSemaglutide, r/Mounjaro_ForType2, r/liraglutide, r/antidietglp1 and r/TirzepatidePH — which our collector had never been told to read. On the founder's approval we added all ten to the collector's list and to the screen, and recomputed every figure below over 42 reports (37 Reddit threads plus 5 Drugs.com review pages). Every share moved. The ordering at the top barely changed; the 29 August table is kept as a record at the end of this article.

The measure is a reporting frequency: of the 42 distinct community reports in our corpus (as of 25 September 2026), what share mention each effect at all. One report = one source URL — a Reddit thread or a Drugs.com patient review, hosted on the platform itself, from a GLP-1, weight-management or diabetes community. A report that mentions three effects counts once in each of those three rows, so the column does not sum to 100%; across all 15 tracked effects the 42 reports carry 110 mentions, so on average a report mentions between two and three of them.

42 is a small number, and we would rather print it than dress it up. These shares move by 2.4 percentage points every time a single report does or does not mention an effect, so treat the ordering as indicative and the precise percentages as provisional. The pool cannot currently grow — Reddit has blocked our collector since 28 May 2026 — so this is what the community track honestly holds, not a sample we chose to stop at.

What this number is not: it is not an incidence rate, and we never present it as one. A mention is not a diagnosis, and the share of reports that talk about nausea is a different quantity from the share of patients who get nausea. The two tracks are published side by side and never averaged, divided, or "converged" — the clinical rates article has the incidence numbers.

All 15 reporting frequencies (as of 25 September 2026)

Every row is served live at the link beside it (field `reportingFrequency` — mentions, distinct reports, share, and the current platform list). The predictor tool's real-world track serves the same shares with a Wilson 95% interval around each.

What stands out

A finding this article originally reported did not survive the correction. The 24 August version led with "abdominal pain out-mentions nausea" (27.6% vs 24.9%) and offered an interpretation for it. On the corrected pool the ordering reverses and is not close: nausea 38.5%, abdominal pain 15.4% on 29 August (33.3% and 19.0% on today's 42 reports). The original result was an artifact of the contamination — r/gallbladders and r/AskDocs posts, which dominated the old pool, are overwhelmingly about abdominal pain. We are leaving this note in rather than quietly deleting the paragraph, because a retracted finding is part of the record.

The GI cluster leads, as the trial literature also finds. Vomiting (35.7%) and nausea (33.3%) are the two most-mentioned effects, with reduced appetite (31.0%) and diarrhoea (28.6%) close behind, and nausea also tops our clinical evidence table. On this pool the two tracks broadly agree about what dominates — which is a weaker and less interesting claim than the one we published on 24 August, and a true one.

Fatigue was, when this was written, the effect patients raised that trials did not quantify. 14.3% of community reports mention it — 6 of 42 (3 of 26 on 29 August). On 29 August our corpus held zero eligible clinical rate points for it, so the API fell back to a labelled published-literature figure. (Updated 25 September 2026: that is no longer true. The trial-registry re-collection in September brought in registry arm tables that do state fatigue rates, and the live API now serves a corpus-derived clinical estimate for fatigue — 99 stated rates from 28 distinct studies as of 19:15 UTC on 3 October 2026 (it was 91 rates / 23 studies at 14:44 UTC on 30 September, before that 84 rates / 20 studies at 23:43 UTC on 29 September, and fatigue was 76 rates / 17 studies at 23:51 UTC on 26 September, 74/16 after the 25 September registry batch, and 67/13 the day before). Read the current figure at the link, not here.) Emotional blunting has zero eligible clinical points, and on the corrected pool it had zero mentions too — its earlier 8.6% came entirely from off-topic communities. Admitting the ten GLP-1 communities on 25 September gave it one: an r/mounjarouk post that our extraction model labelled emotional blunting when it was collected. The part of that post we store is cut off before any mention of mood, and Reddit's block means we cannot re-read the rest, so we count it as the method counts every other report and do not lean on it. Per our methodology, a reporting frequency is a pointer — a signal that something may matter to patients and deserves study — not evidence about true incidence, and a single mention is the faintest pointer there is.

Why we count mentions instead of averaging what posts claim

Because averaging what individual posts claim produces confident-looking nonsense, and we know because we did it. Until 14 August 2026 our real-world track averaged self-reported percentages scraped from posts — and one X/Twitter post claiming "76%" hair loss pulled a two-source average to 39%. Averaging what one anecdote claims is not a measurement no matter how the average is weighted, so we replaced the computation with the reporting frequency above and published the correction. A second correction followed on 17 August: 47 of what were then 232 "community reports" turned out to be Google News search results about social posts rather than posts on the platform itself; removing them moved the nausea figure from 32.5% to 24.9%. The third is the one at the top of this article, on 29 August. All three are kept publicly in our llms.txt correction history — we publish corrections rather than quietly overwrite them. The pattern across all three is the same and worth naming: every one of them was a question about which rows belong in the denominator, not about the arithmetic.

Honest limitations

The pool is small, dated, and frozen. 42 distinct reports as of 25 September 2026 (26 from 29 August until then). Reddit has blocked automated collection since 28 May 2026, so the community corpus grows only when a new collection route works. Cite these figures with their date and their denominator, and do not read a 2.4-point gap between two rows as a difference.

Self-selection. People post about experiences that bother them. That skews mentions toward negative and dramatic experiences, in ways we cannot quantify — one more reason this is a reporting frequency, not an incidence estimate.

Two platforms. Today's reports come from Reddit and Drugs.com patient reviews (the live list is the `platforms` field at every API link above). Those communities are not a random sample of GLP-1 patients.

The denominator is a screened subset, not everything we hold. (Added 21 September 2026 — this limitation had never been stated in this section, the place readers come to for what the denominator means. The screen itself has run since 29 August 2026 and is described in the methodology page and the `note` field of every `/api/data` reporting-frequency response; what was missing was this article saying it, and saying how much it removes.) A Reddit post counts only if its subreddit is one of the GLP-1, weight-management and diabetes communities our collector is configured for — 26 since 25 September 2026, 16 before. (The rest of this paragraph is the 20 September 2026 measurement that led to the change, kept as written; its open question was settled on 25 September by admitting all ten communities, which took the denominator to 42.) On the 20 September 2026 corpus that screen takes 184 distinct non-seed community report URLs down to the 26 these shares are computed over — 21 Reddit threads plus 5 Drugs.com per-drug review pages. Of the 158 removed, 142 are off-topic — posts matched on a bare symptom word in r/gallbladders, r/AskDocs, r/pregnant and similar, where post-surgical pain and pregnancy nausea were being counted as GLP-1 patient reports until the screen was added. The other 16 are not off-topic at all: they are posts in r/mounjarouk, r/TirzepatideRX, r/Retatrutide, r/GLP1India, r/CompoundedSemaglutide, r/Mounjaro_ForType2, r/antidietglp1, r/TirzepatidePH, r/RetatrutideTalk and r/liraglutide — unambiguously GLP-1 communities that our collector was simply never configured to read, so posts from them arrived only as spillover from a search and are excluded by a rule written to catch something else. Admitting them would raise the denominator by more than half and move every share on this page, so it is an open question we are deciding deliberately rather than quietly — not a settled exclusion. (Corrected 21 September 2026: this paragraph said 143 and 15, across nine communities. A re-derivation of the screen the next cycle found r/liraglutide — the drug community for a GLP-1 receptor agonist sold as Saxenda and Victoza — missing from the list, which meant its one report was being counted among the off-topic 143. Admitting the set takes the denominator 26 → 42, not 26 → 41.) Both figures were computed against the live database on 20 September 2026 and agree exactly with the repo corpus file.

The clinical track — 71 eligible stated rates from 22 distinct studies as of 31 August 2026 (restated 8 September 2026 from 74 / 23, when three rates attributed to a Nature genome-wide association study that states no incidence rate were withheld; until 8 September 2026 this sentence read "51 distinct sources": that figure counted one entry per source per effect, so a trial registry record reporting seven effects counted seven times — see the methodology page; and corrected from the 143/65 this sentence originally cited: the April-2026 seeding pass had written rate rows restating our own static literature table under real trial and study URLs, and the 31 August correction excluded them — see the pooled rates article for the full account) — has grown a great deal since, as the trial-registry re-collection ran through September: 887 eligible rates across 29 distinct studies (180 name-keyed source entries) as of 14 September 2026, read from the live overview endpoint — is the other half of the picture: see the pooled rates, or query everything yourself at magistra.health/en/data-api.

The 29 August 2026 table (superseded 25 September 2026)

Kept as published, over 26 reports, so the restatement above can be checked against it.