Education — a classification, not a measurement. An on-box language model (Qwen3.6-35B-A3B-FP8, prompt version 1) read this channel’s own recent posts on 10 September 2026 and assigned it the closest of 31 fixed categories, at 100% confidence. This is a model’s judgement about what the channel is likely to be about, not a fact this register measured the way a subscriber count or a view count is measured — it can be revised on a later pass, and it carries no weight anywhere else on this page. How this classification works, and why it has no browse page of its own yet.
Growth
49 measurements spanning 79 days, net +741. Dots are measurements; the straight line between them is drawn to join them, not to claim we know the path taken in between — snapshots are recorded only when a count changes, so gaps mean “no change observed”, never “interpolated”. The vertical axis spans 28,892–29,878 and does not start at zero.
Measurement log — every subscribers count we have recorded, most recent 20 of 49
Measured (UTC)
Subscribers
Change
25 Oct 2026, 12:54
29,747
-14
24 Oct 2026, 13:54
29,761
-3
23 Oct 2026, 13:41
29,764
+5
22 Oct 2026, 15:38
29,759
+8
21 Oct 2026, 09:19
29,751
+8
20 Oct 2026, 05:19
29,743
+1
19 Oct 2026, 08:06
29,742
+5
18 Oct 2026, 10:56
29,737
-4
17 Oct 2026, 12:40
29,741
+4
16 Oct 2026, 11:11
29,737
+16
15 Oct 2026, 12:55
29,721
-3
14 Oct 2026, 12:19
29,724
+6
13 Oct 2026, 02:25
29,718
+30
8 Oct 2026, 20:55
29,688
+29
4 Oct 2026, 08:16
29,659
+53
25 Sept 2026, 16:16
29,606
+80
19 Sept 2026, 04:56
29,526
+19
16 Sept 2026, 18:16
29,507
+16
14 Sept 2026, 20:21
29,491
+18
13 Sept 2026, 08:57
29,473
first reading
Engagement
31 posts held, back to 19 February 2026 — the reader has not yet reached the start of this channel’s public history, so older posts may sit further back, unread. Read across 125 pages of Telegram’s post history, 20 posts per page.
ERR · 30 days
7.12%
avg views ÷ 29,747 subscribers
Avg views / post
2,120
2 posts measured
Reaction rate
0.708%
reactions ÷ views · ER floor
Posts in window
2
of 31 held
ERR is average views per post over the last 30 days divided by subscribers, the definition TGStat uses, so this figure is comparable with the one you will see elsewhere. It falls structurally as a channel grows: a high ERR on a small channel and a low one on a large channel describe reach mathematics, not quality. We publish the figure and the sample it came from and pass no verdict on it.
ER is defined industry-wide as (forwards + reactions + comments) ÷ views — note the denominator is views, not subscribers. Telegram’s public web preview carries views and reactions but not forward or comment counts, so the reaction rate above is the reactions term only and is therefore a floor: the true ER for this channel is higher by an amount we have not measured and will not estimate.
What these figures were computed from
Window
Rolling 30 days · latest post in window 24 October 2026
Posts held
31 (19 February 2026 – 24 October 2026)
Views total
4,235
Reactions total
30
Forwards / comments
not exposed by the public surface — not measured, not estimated
Readings taken
25 Oct 2026, 05:20 UTC
Views are a single reading per post, taken at the time above. A post published in the last day or two is still accumulating views, which pulls the 30-day average down slightly. That is a property of the standard definition rather than a fault in it, so we keep the definition rather than “correcting” the number into something nobody can reproduce.
Precision. Telegram publishes view counts on its public widget in short form — 8.12K, 3.7M — so any reading at or above 1,000 reaches us rounded to three significant figures, and only counts below 1,000 are exact. Averages and rates derived from them are shown to the same precision rather than to the unit: a figure like 3,701,250 would assert digits nobody measured.
Reaction counts are published per emoji and rounded the same way, so a total below 1,000 is exact and a larger one is a sum that may carry a rounded component from each emoji above 1,000. Because it is a sum, it does not look rounded — read a large reaction total as three significant figures per contributing emoji rather than as the figure it prints.
Reaction mix
15,687 reactions across 31 posts, in 16 distinct kinds. The most used accounts for 26.4% of them.
Every reaction kind recorded on the sample, most used first
Reaction
Count
Share
Share, drawn
🥰
4,145
26.4%
❤
2,289
14.6%
🤩
1,938
12.4%
🔥
1,430
9.12%
👍
1,150
7.33%
❤🔥
1,125
7.17%
🎉
1,118
7.13%
💯
1,050
6.69%
😍
1,042
6.64%
👏
343
2.19%
😁
37
0.236%
😢
9
0.057%
🗿
4
0.025%
🙏
4
0.025%
🤯
2
0.013%
😱
1
0.006%
No sentiment is inferred, and none should be read in. This table is ordered by count and by nothing else. Emoji do not carry stable meaning across languages or communities — 🙏 is thanks in one channel and mourning in another — so we publish which ones were pressed and how often, and pass no judgement on what an audience meant by them.
Precision. Telegram publishes reaction counts per emoji and short-forms each one — 4.34K, 1.2M — so any single kind at or above 1,000 reaches us at three significant figures, and only counts below 1,000 are exact. The shares above are ratios of those figures and carry the same error. This is also why the total here can differ slightly from a reaction total printed elsewhere on the page: both are sums of the same rounded parts, taken over samples with different edges.
Coverage. Reactions were read on 31 of the 31 sampled posts in this sample. Summed by Telegram’s own count on each post — not by adding up the per-emoji breakdown above — those same posts carry 15,687 reactions in total: the kind of figure the paragraph above means by “a reaction total printed elsewhere on the page”.
Measured over the 31 most recent posts we hold, published 19 February 2026 to 24 October 2026, using the newest reading held for each. Telegram Stars are excluded: they are a payment, not a reaction, and they have their own section.
Telegram Stars
Stars received
1
across the posts below
Posts paid on
1
of 31 we hold a reading for · 3%
Most on one post
1
single highest reading
A paid reaction is a reader spending Telegram Stars — bought with money — on a post by @usmlerecallshub. Telegram publishes the count on the public post preview alongside ordinary reactions, and this register reads it there. It is the only figure on this site that measures money moving rather than attention.
Stars are not reactions, and the two are never added. They are rendered in the same strip on Telegram and counted in the same shape, but one is a tap and the other is a purchase. The reaction totals and the engagement rate elsewhere on this page exclude every figure in this section, and no rate here is computed against a reaction count.
This is not revenue, and we publish no currency figure. What a Star costs a reader and what it pays a channel are different numbers, Telegram takes a share we cannot observe, and the terms have changed. Converting a Star count into money would be an estimate dressed as a measurement, so the count is where we stop.
Counted over the 31 most recent posts we hold for this entry, published 19 February 2026 to 24 October 2026. Star counts above 1,000 reach us in Telegram’s short form and carry the same three-significant-figure rounding as everything else on this page.
Step 1 student review
Ethics: 2–3 every single block, and worded NOTHING like UWorld. Vague. Weird. Two answers that both feel “fine.” Practice NBME-style ethics only.
Micro was everywhere — close to a third of my exam.
Anatomy: way more than I prepared for. GI anatomy especially.
Nutrition = free marks. Vitamins, deficiencies, minerals. Don’t skip the notes all are covered there.
Immuno, heme, MSK hit hard. A frien…
Nobody who scores 260+ is smarter than you. They started earlier, studied the stuff what the exam actually tests, and didn't waste months on random resources.
Nobody on this here is lazy. Everyone here works hard.
The only difference is whether you work hard in the right direction — or work hard in the dark, hoping it works
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🚨 Preparing for USMLE Step 3 while working residency hours?
Step 3 isn’t just “more Step 2.” Your preparation needs to account for two very different exam days + CCS cases.
A few things worth getting right early:
📌 Day 1: Don’t neglect biostats, epidemiology, ethics & drug-ad style questions
📌 Day 2: More clinical management + 13–14 CCS cases
📌 CCS: Start practicing early — knowing the medicine isn’t enough if you’re…
Nutrition on Step 2 CK and Step 3 doesn't look like nutrition
📌 Effective June 2026, the USMLE enhanced nutrition content across all three Step exams. On Step 2 CK and Step 3 these items are double-coded — a nutrition question is also filed under Gastrointestinal, Renal, or Endocrine. It arrives as the cirrhotic you're feeding, the panel on refeeding day three, the prenatal label, the tube nobody filmed.
All premiu…
Studying more ≠ remembering more for Step 1.
A common mistake during USMLE Step 1 prep is spending hours rereading First Aid or UWorld explanations and feeling familiar with the material — but struggling to recall it when the same concept appears inside a new vignette.
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In this guide, we cover practical ways to use active recall during Step 1 prep, including:
• How to turn UWorld blocks …
Never miss a Nutrition question again
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All premium and VIP subscribers have access to this file in their drive at no additional cost.
The main file comprises 133 topics, 239 questions and vignettes, 120 questions organized into four timed b…
🎉 A recent Step 1 pass — with honest exam insights
We asked a student who recently passed Step 1 to share what the exam actually felt like. Their unfiltered response is in the screenshot above.
The biggest lesson: knowing a concept is not enough—you must be able to recall it when the question is vague, indirect, and time feels tight.
That is exactly what Recall Mastery is designed for: structured, high-yield Step …
❤293😍292🤩279❤🔥261🥰255🔥251👍249💯249
Showing the 12 most recent of 31 posts we hold for @usmlerecallshub. View and reaction counts are the latest single reading for each post, not a live figure, and a recent post is still accumulating both. A view count marked ≈ was rounded by Telegram before we ever saw it — t.me prints views in full below 1,000 and to three significant figures above, so ≈1,200,000 means somewhere between 1,150,000 and 1,249,999. Unmarked counts are exact. Text is reproduced from the public post preview and truncated for length.
Channels Telegram recommends alongside this one
Telegram’s own answer, not this register’s. When this register asks Telegram’s API what is similar to this channel, this is the list it returns, in the exact order Telegram returns it — never re-sorted by subscribers or by anything else this register measures. The relationship, and the order, are Telegram’s; we record them and date them, and make no claim of our own about which of these channels actually resemble this one.
Read from Telegram’s recommendation API, most recently 8 September 2026. Telegram holds a list like this for a small and growing share of the register — how this is measured, and why most channel pages show nothing here.
Appears in Telegram’s recommendations for other channels
The reverse of the list above, and a different kind of signal. This does not require this channel to have ever been asked about directly — each row below is a channel we DID ask Telegram about, whose Telegram-generated list happened to include this one. A channel can appear here with an empty list above it, because being named by someone else’s query is independent of having been queried itself.
USMLE RECALLS STEP 1 2and 3 2026 @USMLERECALLS2021 · 30,642 Telegram ranks this channel #1 of 73 here — alongside 72 others — read 6 September 2026
Mehlmanmedical channel @mehlmanmedical · 26,566 Telegram ranks this channel #5 of 78 here — alongside 77 others — read 13 September 2026
Pixorize Videos | USMLE Step 1 @USMLEPixorize · 26,438 Telegram ranks this channel #17 of 82 here — alongside 81 others — read 13 September 2026
KAPLAN VIDEOS @kaplanvideos · 93,117 Telegram ranks this channel #19 of 56 here — alongside 55 others — read 26 August 2026
UWorld Step 1 QBank 2024 (USMLE WORLD) @USMLEWorldStep1 · 96,183 Telegram ranks this channel #19 of 78 here — alongside 77 others — read 26 August 2026
NBME STEP 1 | USMLE 2026 @USMLE_NBME · 21,851 Telegram ranks this channel #29 of 78 here — alongside 77 others — read 22 September 2026
USMLE Anki @USMLEAnki · 48,205 Telegram ranks this channel #31 of 71 here — alongside 70 others — read 26 August 2026
OnlineMedED Videos | USMLE Step 2 CK | 1 @USMLEOnlineMedED · 30,287 Telegram ranks this channel #32 of 79 here — alongside 78 others — read 7 September 2026
NBME STEP 1 | USMLE @USMLENBME · 68,648 Telegram ranks this channel #39 of 75 here — alongside 74 others — read 26 August 2026
Pathoma Videos 2024 | USMLE @USMLEPathoma · 106,772 Telegram ranks this channel #41 of 75 here — alongside 74 others — read 26 August 2026
First aid 2026 🫡 @first_aid2026 · 24,747 Telegram ranks this channel #44 of 74 here — alongside 73 others — read 17 September 2026
Ninja Nerd Videos @ninjanerdmedical · 32,227 Telegram ranks this channel #44 of 81 here — alongside 80 others — read 6 September 2026
BoardsAndBeyondVideos @USMLEBoardsAndBeyondVideos · 55,251 Telegram ranks this channel #45 of 76 here — alongside 75 others — read 26 August 2026
This channel appears in 13 seed channels' Telegram-generated recommendation lists in total. Each is Telegram’s list for THAT channel, not this one — see how this is measured.
Cite this entry
A live page changes as we take new readings, so a citation should name the measurement it is based on, not just the URL. The line below cites the subscriber count as measured 25 October 2026 — this
entry's latest reading, not the date you are reading this.
“Usmle recalls step 1,2 &3 2025” (@usmlerecallshub), 29,747 subscribers as measured 25 October 2026. Telegram Register, tgregister.com/channel/usmlerecallshub.
Full measurement history, CC BY 4.0. Every reading this register holds for this entry, not just the latest one, as a dated, downloadable record: CSV · JSON. Free to use with attribution to tgregister.com. Each file carries its own generation timestamp, which is the figure to cite for exactly when the data was retrieved.