Telegram RegisterThe public register of Telegram

Channel

Medical USMLE

@kaplanusmles

On this record: Topic · Observations · Also posting the same content · Growth · Engagement · What this channel posts · Posts · Polls · Citations · Cite this entry

44,503subscribers

-75 since we began measuring on 6 August 2026

Risers and fallers across the register · movement among entries of 31,623–100,000.

Register entry

Telegram ID-1001257421194
TypeChannel
Username@kaplanusmles
DescriptionHere is place to get All Kaplan USMLE 2010, 2014,2015 2019 lecture videos
CreatedBetween 1 March 2018 and 30 June 2021— estimated from Telegram’s id allocation, not measured. How this range is calculated.
First recorded6 August 2026
Last confirmed live12 August 2026
Measurements held9
Confirmed unchanged1 time, most recently 12 August 2026
On Telegramt.me/kaplanusmles

Topic

Education — a classification, not a measurement. An on-box language model (Qwen3.6-35B-A3B-UD-Q6_K_XL, prompt version 1) read this channel’s own recent posts on 10 August 2026 and assigned it the closest of 31 fixed categories, at 98% 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.

Observations

These are measurements, not verdicts. Each one below states something we counted, alongside the evidence it was counted from, so you can check it rather than take it. None of them is graded: every observation this register holds is recorded at severity 0, because the precision of the detectors behind them has not been measured yet, and a rating we cannot support is worse than none. Read each as a fact about the data, not as a judgement about the channel. How we measure.

Content that also appears on other registered channels

Posts published here appear word for word on 7 other registered channels. The matching is on the text itself, not on Telegram’s forward marker, so it finds a copy whether or not it was labelled as one.

Matching posts — open both and compare (6 of the pairs behind the counts below)
Posted firstThenOverlapGap
@Mcat_uworld/16074 May 2023, 20:26 UTC@kaplanusmles/4551 · this entry4 May 2023, 20:35 UTC1.009 minutes
@Mcat_uworld/16094 May 2023, 20:59 UTC@kaplanusmles/4553 · this entry4 May 2023, 21:37 UTC1.0038 minutes
@Mcat_uworld/161520 May 2023, 15:15 UTC@kaplanusmles/4559 · this entry20 May 2023, 15:24 UTC1.008 minutes
@Mcat_uworld/161720 May 2023, 19:16 UTC@kaplanusmles/4561 · this entry20 May 2023, 19:25 UTC1.009 minutes
@kaplanusmles/4564 · this entry21 May 2023, 14:56 UTC@Mcat_uworld/162021 May 2023, 15:01 UTC1.005 minutes
@Mcat_uworld/162221 May 2023, 20:03 UTC@kaplanusmles/4566 · this entry21 May 2023, 20:58 UTC1.0055 minutes
Every channel this entry shares post bodies with
ChannelMatching postsText overlapTypical gapPublished first
@Mcat_uworld8 (8/8 hand-verifiable sample passed)1.0023 minutes@Mcat_uworld (53)
@pathology_videoz8 (8/8 hand-verifiable sample passed)1.0048 minutesthis entry (53)
@Becker_videos_step19 (8/8 hand-verifiable sample passed)1.00under a minutethis entry (54)
@USMLE_AMBOSS9 (8/8 hand-verifiable sample passed)1.006 minutes@USMLE_AMBOSS (54)
@Vid_Physeo_S8 (8/8 hand-verifiable sample passed)1.00under a minuteeven
@Usmle_pharma7 (7/7 hand-verifiable sample passed)1.0072 seconds@Usmle_pharma (43)
@USMLE_NBME5 (5/5 hand-verifiable sample passed)1.006.0 hoursthis entry (41)

Text overlap is the Jaccard coefficient over the set of distinct three-word phrases in the two bodies: 1.00 is identical wording, and the threshold for counting a pair at all is 0.70. Candidates are generated by simhash LSH (4 x 16-bit bands, exact Hamming <= 3) verified against the bodies with Jaccard over the SET of distinct 3-word shingles. Published first counts which side of each matching pair carries the earlier timestamp — in this corpus, which is the limitation directly below.

What this cannot establish

MEASURED, DOMINANT ERROR SOURCE: a post ingested before 2026-08-06 may have carried a forward header that was not recorded. A 45-pair hand-check against live t.me pages found 14 (31%) where the live page shows a forward header naming the other channel and the database has none, plus 4 more (9%) naming a third party. The text match itself was wrong 0 times out of 45. Read attribution_capture.items_in_trusted_window before treating the unattributed count as a claim.

Telegram lets a channel forward a post with a header naming the source, and we only began reliably recording that header on 2026-08-06. None of the 24 matches recorded here fall after that date, so for this entry we cannot say whether any of them carried a credit. The duplication is measured; the absence of attribution is not.

“Published first” means first in this corpus. We hold 15 comparable posts for this entry, running 4 May 2023 to 7 August 2026. A channel we have read one page deep will look younger than a neighbour we have read in full, and the order would flip with no change in the underlying facts.

The detector’s own notes on this observation, as it recorded them. Names in this_style are fields of the underlying evidence record, which the plain-English paragraphs above read out for this entry.

  • Verbatim republication has three causes and the text separates only two: a clone/mirror, unattributed copy-paste, or BOTH channels copying a common third source that neither attributes. The spread filter (content held by at most 8 channels) reduces the third and does not remove it.
  • 'Earliest' means earliest IN THIS CORPUS. A channel ingested one page deep will look younger than a neighbour ingested in full; corpus_coverage above is there to be checked before the direction is believed.
  • shared_verified_est extrapolates the sampled pass rate over the full narrow match count; sampled/passed are the numbers actually measured.
  • Absence of a forward header is not proof of intent: Telegram lets a channel disable forward attribution, and a credit written in the body is not parsed as attribution here (mention_edge_either_way above is the closest available signal).

Across the whole group of 8, the earliest publisher we hold is @Mcat_uworld. That is a statement about our reading window, not a claim of authorship.

Recorded under the keys clone_mutual · clone_source, last confirmed 8 August 2026. An observation that a later pass no longer finds is cleared, and a cleared observation is removed from this page rather than being shown struck through — we do not keep publishing a claim we have withdrawn. Dispute an observation.

Also posting the same content

This channel’s posts match, word for word or near enough, posts on 7 other registered channels, found by comparing text fingerprints across every channel on the register. That matching has been checked by hand against the live Telegram pages and found reliable — 0 wrong of 45 pairs re-read.

Which channel, if either, published first is deliberately not shown. The same hand-check found that reading wrong 18 of 45 times — 60%, no better than a coin flip — because it depends on how deep our own crawl happened to reach into each channel’s history, not on when the content was actually first posted. This list is ordered by subscriber count, the same as every other listing on this site, never by which channel we think came first. Word-for-word matching has several ordinary explanations besides copying — a channel mirroring itself, an unattributed repost, or two channels independently repeating the same wire story — and this measurement cannot tell those apart. How this is measured.

Growth

44,50344,57844,540.56 August 2026 — 44,578 subscribers6 August 2026 — 44,578 subscribers6 August 2026 — 44,576 subscribers7 August 2026 — 44,559 subscribers8 August 2026 — 44,548 subscribers9 August 2026 — 44,535 subscribers10 August 2026 — 44,516 subscribers11 August 2026 — 44,504 subscribers12 August 2026 — 44,503 subscribers6 August 202612 August 2026
9 measurements spanning 7 days, net -75. 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 44,492–44,589 and does not start at zero.
Measurement log — every subscribers count we have recorded
Measured (UTC)SubscribersChange
12 Aug 2026, 19:3244,503-1
11 Aug 2026, 19:5144,504-12
10 Aug 2026, 21:4144,516-19
9 Aug 2026, 19:0144,535-13
8 Aug 2026, 21:2444,548-11
7 Aug 2026, 18:4244,559-17
6 Aug 2026, 16:4244,576-2
6 Aug 2026, 05:0044,578no change
6 Aug 2026, 04:5944,578first reading

Engagement

21 posts held, back to 4 May 2023the reader has not yet reached the start of this channel’s public history, so older posts may sit further back, unread. Read across 17 pagesof Telegram’s post history, 20 posts per page.

ERR · 30 days
2.47%
avg views ÷ 44,503 subscribers
Avg views / post
1,100
1 post measured
Reaction rate
this channel exposes no reaction counts
Posts in window
1
of 21 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
WindowRolling 30 days · latest post in window 7 August 2026
Posts held21 (4 May 20237 August 2026)
Views total1,100
Reactions total
Forwards / commentsnot exposed by the public surface — not measured, not estimated
Readings taken12 Aug 2026, 20:07 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.

What this channel posts

Photos
138
Videos
683
Links
132

Lifetime counters from Telegram’s own channel header, read 12 August 2026 — not the date at the top of this page, which is when the subscriber count was last read. Below Telegram’s rounding threshold, so these counts are exact.

Recent posts

7 Aug 2026, 14:24 UTC≈1,100 viewsread 12 August 2026
Forwarded from @medicospirachPhoto

🎧 How to Access Deep Dive in Step 1 and Step 2 🥳: 1️⃣ Open Previous Tests or Create a New Test 2️⃣ Tap the Mind Map icon 🧠 3️⃣ Inside the Mind Map, tap the Explainer icon 💡 4️⃣ Select Deep Dive Explainer 🎙 — approximately 6-10 minutes 🚀 Learn the reasoning step by step with a natural, podcast-style explanation. 👇👇👇👇👇👇 usmle.medicospira.com Telegram channel 👇 👇 👇 👇 👇 👇 👇 👇 Medicospira channel

16 May 2026, 23:19 UTC≈7,710 viewsread 12 August 2026

? USMLE future doctors: join the AI-assisted Qbank. level up together.

5 Dec 2025, 02:06 UTC≈25,700 viewsread 12 August 2026
Photo

👨‍💻☄️BREAKING NEWS! 🆕🤩 NBME success stories are BACK on the channel 🥳😀 All our students study smarter, not harder — and the results speak for themselves! For weeks, many kept asking: “When will the success stories return?⁉️🤔 Today, the wait is over — and we’re bringing you real victories from real students.👍 😶Every post you’ll see isn’t luck… it’s proof that with smarter studying, focus, and the right guidance,

19 Jul 2025, 16:31 UTC≈25,600 viewsread 12 August 2026
Forwarded from @NBMECMSPhoto

🎉NBME Qbank Surprise! 🤩🤩 NBME Step 1 Qbank Mode is here 💥 4000+ NBME Qs • Smart filters • AI tools • Deep analytics 🚀 Join now & boost your Step 1 prep! ⬇️⬇️⬇️⬇️⬇️⬇️⬇️ 🔗 [Sgin up Free account] join NBMEWAY telegarm channel: @NBMECMS

10 Jun 2025, 19:13 UTC≈23,400 viewsread 12 August 2026
File

🎙 Short. Smart. Step 1. USMLE Podcast – Rapid Review Series now streaming. Listen & crush. Drug Interactions For The USMLEs (Step 1-3) @USMLEpodcast

10 Jun 2025, 19:13 UTC≈18,300 viewsread 12 August 2026
Forwarded from @USMLEpodcast

We come back again guys with new USMLE podcasts 🎇

23 May 2025, 12:22 UTC≈20,500 viewsread 12 August 2026
Forwarded from @USMLEpodcast

🎙 Welcome to the USMLE Crush Podcast Channel! 🧠📚 Hey future doctors! 👋 Welcome to the USMLE Crush Podcast — your ultimate audio course designed to help you master high-yield Step 1 concepts through real NBME & UWorld-based cases. Each episode simplifies complex topics, reinforces must-know facts, and helps you crush Step 1 with confidence. From immuno to pharm, neuro to pulm — we’ve got it all. 🎧 Listen. Learn. Cr

23 May 2025, 08:19 UTC≈9,070 viewsread 12 August 2026
Forwarded from @USMLEpodcastPhoto

Your new go-to audio series for mastering USMLE Step 1 — one high-yield case at a time. 💡 Short episodes. 🧠 Real NBME & UWorld-style questions. 📚 High-yield breakdowns across all systems. 🔥 Learn smart. Think like the test maker. Crush the exam. 📲 Follow the channel for new episodes and study drops every week. 🎧 Let’s get started — your Step 1 success begins here. https://t.me/USMLEpodcast #USMLECrushPodcast #Step

22 May 2025, 20:26 UTC≈12,000 viewsread 12 August 2026
Forwarded from @USMLEpodcastPhoto

Your new go-to audio series for mastering USMLE Step 1 — one high-yield case at a time. 💡 Short episodes. 🧠 Real NBME & UWorld-style questions. 📚 High-yield breakdowns across all systems. 🔥 Learn smart. Think like the test maker. Crush the exam. 📲 Follow the channel for new episodes and study drops every week. 🎧 Let’s get started — your Step 1 success begins here. https://t.me/USMLEpodcast #USMLECrushPodcast #Step

26 May 2023, 15:11 UTC≈95,400 viewsread 12 August 2026

Educational objective: Lesions of the jugular foramen can result in jugular foramen (Vernet) syndrome, which is characterized by the dysfunction of cranial nerves IX, X, and XI. Symptoms include dysphagia, hoarseness, loss of gag reflex on the ipsilateral side, and deviation of the uvula toward the normal side.

26 May 2023, 09:10 UTC≈81,000 viewsread 12 August 2026
Poll

A lesion involving which of the following anatomical structures is most likely responsible for this patient's symptoms?

  1. A. Cerebellopontine angle16%
  2. B. Foramen magnum13%
  3. C.Foramen ovale10%
  4. D.Foramen rotundum7%
  5. E. Hypoglossal canal23%
  6. F. Jugular foramen31%

Shares as published. No per-option vote count is published by Telegram, so none is shown.

26 May 2023, 09:10 UTC≈68,800 viewsread 12 August 2026

A 67-year-old woman with a known history of lung cancer comes to the office due to hoarseness and difficulty swallowing. She has no disturbances in vision or hearing. On examination, there is loss of the gag reflex on the left side; when the patient is prompted to say "ah," the uvula deviates to the right side. a right lower lobe lung mass and several osteolytic rib lesions. MRI of the head also demonstrates multiple

Showing the 12 most recent of 21 posts we hold for @kaplanusmles. 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.

Polls

The 4 polls we hold for this entry, as Telegram rendered them when we read the post. A poll’s figures keep moving after that, so each one is dated.

26 May 2023, 09:10 UTCAnonymous Quiz3,780 voters approx.

A lesion involving which of the following anatomical structures is most likely responsible for this patient's symptoms?

  1. A. Cerebellopontine angle16%
  2. B. Foramen magnum13%
  3. C.Foramen ovale10%
  4. D.Foramen rotundum7%
  5. E. Hypoglossal canal23%
  6. F. Jugular foramen31%

Shares as published. No per-option vote count is published by Telegram, so none is shown.

21 May 2023, 14:57 UTCAnonymous Quiz2,390 voters approx.

Accumulation of which of the following metabolites is most likely present in this patient's tissues?

  1. A. Galactocerebroside16%
  2. B. Globotriaosylceramide7%
  3. C. Glucocerebroside14%
  4. D.Glycogen10%
  5. E. GM2 ganglioside34%
  6. F. Heparan sulfate6%
  7. G .Sphingomyelin13%

Shares as published. No per-option vote count is published by Telegram, so none is shown.

20 May 2023, 15:24 UTCAnonymous Quiz2,300 voters approx.

Which of the following microbial components is directly responsible for the severity of disease in this patient?

  1. A. Capsular polysaccharide22%
  2. B. lmmunoglobulin proteas16%
  3. C. Lipo-oligosaccharide30%
  4. D.Lipoteichoic acid10%
  5. E. Superantigen exotoxin22%

Shares as published. No per-option vote count is published by Telegram, so none is shown.

4 May 2023, 20:36 UTCAnonymous Quiz1,940 voters approx.

The patient most likely suffered from which of the following?

  1. A. Amyotrophic lateral sclerosis50%
  2. B. Poliomyelitis18%
  3. C.Rabies8%
  4. D.Huntington disease11%
  5. E. Friedreich ataxia5%
  6. F. Vitamin 812 deficiency7%

Shares as published, totalling 99%. No per-option vote count is published by Telegram, so none is shown.

Percentages only — there are no per-option vote counts here, because Telegram publishes none.The public post preview gives each option’s share and a single voter total, and nothing else. Multiplying one by the other would produce a per-option tally that looks measured and is not: the shares are rounded to whole numbers before we ever see them. We print what was published and leave the column that does not exist empty.

The shares need not add up to 100.Rounding alone puts many polls at 99 or 101. A poll that allows more than one answer per voter runs well past 100 by design, and several here do. The bars are drawn against a fixed 100% track at each option’s own percentage rather than normalised to the total, so a poll that exceeds it shows that it does instead of being quietly rescaled.

Read from the 21 most recent posts we hold, published 4 May 2023 to 7 August 2026. Telegram labels each poll by kind — an anonymous poll, a quiz, a closed set of final results — and that label is reproduced rather than paraphrased.

Forward network

Built only from forwarded posts we have actually read, on both sides. Coverage is early and deliberately incomplete: a missing link means we have not read the post that would prove it, never that the relationship does not exist. Counts are distinct forwarded posts observed, so they only ever go up as we read more.

Mentions

A mention is a weaker signal than a forward and is counted separately for that reason — naming a channel is not republishing it, and a handle in a post body is easy to place deliberately. The post counts beside each row below are distinct posts in which the handle appeared, from posts we have read on both sides — the “Named by N registered channels” figure above is a different count, of distinct NAMING CHANNELS rather than posts, and is not the sum of the rows under it.

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 12 August 2026 — this entry's latest reading, not the date you are reading this.

“Medical USMLE” (@kaplanusmles), 44,503 subscribers as measured 12 August 2026. Telegram Register, tgregister.com/channel/kaplanusmles.

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.