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 12 September 2026 and assigned it the closest of 31 fixed categories, at 73% 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 the other topics.
Growth
23 measurements spanning 90 days, net -64. 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 5,985–6,098 and does not start at zero.
Measurement log — every subscribers count we have recorded, most recent 20 of 23
Measured (UTC)
Subscribers
Change
5 Nov 2026, 21:41
6,021
+23
30 Oct 2026, 21:00
5,998
-8
27 Oct 2026, 19:48
6,006
-3
24 Oct 2026, 23:31
6,009
-8
22 Oct 2026, 02:48
6,017
+5
18 Oct 2026, 19:47
6,012
-1
15 Oct 2026, 09:55
6,013
+3
12 Oct 2026, 12:04
6,010
-5
5 Oct 2026, 18:37
6,015
-10
28 Sept 2026, 08:57
6,025
-7
19 Sept 2026, 02:41
6,032
-6
14 Sept 2026, 22:18
6,038
-7
11 Sept 2026, 03:56
6,045
-5
6 Sept 2026, 10:59
6,050
-2
1 Sept 2026, 23:16
6,052
-4
29 Aug 2026, 22:12
6,056
-10
26 Aug 2026, 13:34
6,066
-2
20 Aug 2026, 02:53
6,068
+6
17 Aug 2026, 11:05
6,062
-6
14 Aug 2026, 03:17
6,068
first reading
Engagement
36 posts held, back to 13 July 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 11 pages of Telegram’s post history, 20 posts per page.
ERR · 30 days
6.87%
avg views ÷ 6,021 subscribers
Avg views / post
414
14 posts measured
Reaction rate
2.31%
reactions ÷ views · ER floor
Posts in window
14
of 36 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 4 November 2026
Posts held
36 (13 July 2026 – 4 November 2026)
Views total
5,791
Reactions total
134
Forwards / comments
not exposed by the public surface — not measured, not estimated
Readings taken
5 Nov 2026, 02:08 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
Video runtime
9m 22s
Average length
1m 34s
Measured directly from 6 videos with a duration reading, out of the posts we hold for this channel — not this channel’s whole posting history, only the sample this register has actually read. An exact reading to the second, taken from the post itself rather than from Telegram’s own rounded chrome, so it carries no ≈ mark.
Reaction mix
549 reactions across 35 posts, in 17 distinct kinds. The most used accounts for 43.0% of them.
Every reaction kind recorded on the sample, most used first
Reaction
Count
Share
Share, drawn
❤
236
43.0%
👍
144
26.2%
🔥
53
9.65%
❤🔥
39
7.10%
😍
21
3.83%
💘
12
2.19%
💔
10
1.82%
😁
7
1.28%
💯
6
1.09%
🥰
5
0.911%
👀
4
0.729%
👏
3
0.546%
😢
3
0.546%
👨💻
2
0.364%
🤔
2
0.364%
👌
1
0.182%
😨
1
0.182%
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 35 of the 36 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 549 reactions in total: the kind of figure the paragraph above means by “a reaction total printed elsewhere on the page”.
Measured over the 36 most recent posts we hold, published 13 July 2026 to 4 November 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.
Recent posts
Telegram’s own ‘edited’ marker: 1 of 14 posts held from the last 30 days (7.14%) carried it when this register last read them. The marker says a post was changed after publishing, not what it said before — this register holds the earlier wording only where an edit fell between two of its own reads (see the edit ledger and how it is measured).
Шесть потоков позади. Седьмой станет финальным 💙
«Аллергия в большом городе» за это время стала чем-то большим, чем просто образовательный курс.
Три дня живого общения с коллегами, клинических разборов и отработки практических навыков.
Шесть потоков, каждый из которых объединил врачей, готовых глубже погружаться в аллергологию.
И сегодня у нас важная новость 🔥️️️️️️
Седьмой поток курса «Аллергия в большом городе»…
Ноябрь в Докмед Академии обещает быть насыщенным 🍁
Возвращение Елисея Осина, новые образовательные продукты по РПП, очные мероприятия и любимые курсы, к которым можно присоединиться в любое время.
Рассказываем обо всём по порядку!
Новинки ноября:
📎Елисей Осин возвращается в Докмед Академию!
Да-да, вы всё правильно прочитали! После долгого перерыва Елисей снова с нами и готовит новый онлайн-интенсив о депрессии.
…
EADV 2026: главное с международного конгресса дерматологов 👩🏻⚕️
Какие исследования могут изменить клиническую практику? Что нового появилось в диагностике и лечении дерматологических заболеваний? И на какие открытия стоит обратить внимание уже сейчас?
🖇️ 19 ноября команда NAOS совместно с врачами сети клиник docmed и docdeti приглашает коллег обсудить ключевые итоги конгресса EADV 2026, который этой осенью прошёл …
Иногда самое сложное на приёме начинается не с диагноза
🖇️ А с момента, когда пациент не хочет говорить. Когда родители не согласны с рекомендациями. Когда разговор заходит в тупик или привычный сценарий общения просто не работает.
И именно такие ситуации хочется не просто обсуждать в теории, а разбирать вместе с коллегами: что произошло, почему разговор пошёл именно так и что врач мог бы сделать иначе.
Именно это…
Вопрос возник на приеме — разберитесь в нем вечером 💻
Не успели на мастерскую? Хотели пройти курс, но не успели на прошедший поток? Ищете обучение, которое можно проходить в удобном формате?
Загляните в каталог Докмед Академии!
Мы собрали там видеокурсы, клинические разборы и интенсивы от практикующих врачей сети клиник DocMed и DocDeti 🖇️
Среди продуктов Академии: нейросонография глазами невролога, БОС-терапия т…
Иногда самое сложное назначение педиатра — ничего не назначать
Ребёнок с температурой третий день. Родители переживают, ждут лечения и спрашивают, почему врач не назначает антибиотик 💊
А педиатру нужно оценить состояние ребёнка, исключить тревожные признаки и объяснить, почему в конкретной ситуации наблюдение может быть правильной тактикой.
Именно такие решения составляют большую часть амбулаторной практики. Когда…
Ребёнок не говорит и редко откликается на имя. Всегда ли дело в РАС? 🤔
На приём к врачу-психиатру Александре Печенкиной привели мальчика 2,5 лет.
🖇️ У ребёнка практически отсутствовала речь, он редко отзывался на имя, и поэтому его родители начали подозревать у ребёнка расстройство аутистического спектра.
При этом сомнений в его слухе у семьи не возникало. Аудиоскрининг в роддоме был пройден успешно, в бытовой обс…
Мелатонин действительно безопасен? А ночные пробуждения всегда связаны с нарушениями сна? 😴
На мастерской «Ловцы снов: Сложные случаи» вместе с Ольгой Шемятовской, врачом-неврологом и сомнологом, мы разобрали вопросы, с которыми сталкиваются врачи при диагностике и лечении нарушений сна.
И теперь запись мастерской доступна для тех, кто не смог присоединиться к нам в прямом эфире!
Что обсудили на встрече?
🔹Мелатон…
Когда женскую боль наконец смогли увидеть 🩺
Долгое время тазовая боль у женщин оставалась одной из сложных диагностических задач. Пациентки жаловались на боль, но установить её причину удавалось далеко не всегда.
Ситуация начала меняться с развитием лапароскопии, которая позволила врачам исследовать органы малого таза изнутри и выявлять изменения, ранее недоступные для визуальной оценки.
Как лапароскопия изменила …
От практикума по аллергологии до открытия целого аллергоцентра
Сегодня хотим познакомить вас с Екатериной Траньковой, врачом-аллергологом-иммунологом из Читы и участницей прошлого потока нашего очного практикума по аллергологии 🖇️
Екатерина приехала на обучение, чтобы увереннее проводить диагностические пробы и освоить процедуры, с которыми раньше не работала.
Сейчас она уже применяет полученные знания на приёме, …
Уже через полтора часа начинаем 😍️️️️️️
Сегодня в 18:00 встречаемся на онлайн-мастерской «Ловцы снов: Сложные случаи» с Ольгой Шемятовской.
Будем разбирать непростые клинические ситуации, обсуждать современные подходы к диагностике и лечению нарушений сна и искать ответы на вопросы, которые возникают в практике.
💙 Если вы ещё не успели зарегистрироваться, присоединиться к мастерской можно по ссылке
🔥3❤1❤🔥1
Showing the 12 most recent of 36 posts we hold for @docmed_universe. 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.
Forward network
Republished by
Channels on the register that have forwarded this channel's posts into their own feed.
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
Named by 1 registered channel — every channel on the register whose own posts have named this one, by its current username or any other username it currently holds, merged from two separately captured readings of the same fact so a namer caught by only one of them is not missed and a namer both caught is not counted twice. A username this channel has since dropped is not matched — that handle may belong to someone else now, and crediting today’s namer to yesterday’s owner would misattribute it.
Named by
Channels on the register whose posts name this channel's handle.
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.
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.
Невролог Стецкая Татьяна | ️doctor_steckaya 💊🩺 @doctor_steckaya · 32,623 Telegram ranks this channel #22 of 96 here — alongside 95 others — read 4 September 2026
DocDeti & DocMed @docdeti_docmed · 62,956 Telegram ranks this channel #24 of 94 here — alongside 93 others — read 21 August 2026
Заметки детского врача @DrButriy · 137,626 Telegram ranks this channel #27 of 95 here — alongside 94 others — read 13 August 2026
MD.school | Медицинский онлайн-университет | Доказательная медицина @medicina_discendi · 21,248 Telegram ranks this channel #28 of 98 here — alongside 97 others — read 25 September 2026
Справочник педиатра @pediatrhelp · 19,277 Telegram ranks this channel #36 of 92 here — alongside 91 others — read 2 October 2026
Помощник педиатра | МедикУм @pomoshnik_pediatra · 23,739 Telegram ranks this channel #46 of 94 here — alongside 93 others — read 17 September 2026
Занудная педиатрия — Роман Шиян @drshnr · 37,027 Telegram ranks this channel #48 of 94 here — alongside 93 others — read 1 September 2026
Шура, выручай! @shura_help · 34,561 Telegram ranks this channel #57 of 95 here — alongside 94 others — read 3 September 2026
ninavaccina @ninavaccina · 90,349 Telegram ranks this channel #59 of 96 here — alongside 95 others — read 17 August 2026
Краснощеков | Детская психиатрия @doc_kras · 19,312 Telegram ranks this channel #68 of 97 here — alongside 96 others — read 4 October 2026
Аллергология для чайников с Ольгой Жоголевой @allergo_doc · 39,376 Telegram ranks this channel #71 of 96 here — alongside 95 others — read 31 August 2026
Доктор Лесков @doctorleskov · 27,764 Telegram ranks this channel #74 of 92 here — alongside 91 others — read 10 September 2026
Доктор Неешпапа 🫁 /doctor_neeshpapa/ @doctor_neeshpapa · 31,811 Telegram ranks this channel #89 of 96 here — alongside 95 others — read 5 September 2026
Профессия – педиатр @profpediatrician · 19,646 Telegram ranks this channel #92 of 98 here — alongside 97 others — read 1 October 2026
Юрист для врача Ангелина Романовская @mfcexpert_news · 29,892 Telegram ranks this channel #93 of 96 here — alongside 95 others — read 8 September 2026
This channel appears in 15 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 5 November 2026 — this
entry's latest reading, not the date you are reading this.
“Докмед Академия” (@docmed_universe), 6,021 subscribers as measured 5 November 2026. Telegram Register, tgregister.com/channel/docmed_universe.
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.