Channel
@Dr_Bragina
On this record: Topic · Growth · Engagement · Reactions · Posts · Citations · Telegram's recommendations · Cite this entry
5,400subscribers
+58 since we began measuring on 7 August 2026
Risers and fallers across the register · movement among entries of 3,162–10,000.
| Telegram ID | -1001138521594 |
|---|---|
| Type | Channel |
| Username | @Dr_Bragina |
| Created | Between 1 June 2017 and 30 September 2020 — estimated from Telegram’s id allocation, not measured. How this range is calculated. |
| First recorded | 7 August 2026 |
| Last confirmed live | 18 September 2026 |
| Measurements held | 13 |
| Confirmed unchanged | 1 time, most recently 18 September 2026 |
| On Telegram | t.me/Dr_Bragina |
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 13 September 2026 and assigned it the closest of 31 fixed categories, at 85% 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.
| Measured (UTC) | Subscribers | Change |
|---|---|---|
| 18 Sept 2026, 16:40 | 5,400 | +9 |
| 14 Sept 2026, 06:56 | 5,391 | +7 |
| 10 Sept 2026, 09:55 | 5,384 | -1 |
| 4 Sept 2026, 21:42 | 5,385 | +11 |
| 31 Aug 2026, 20:08 | 5,374 | +5 |
| 29 Aug 2026, 04:25 | 5,369 | +7 |
| 26 Aug 2026, 06:59 | 5,362 | +17 |
| 23 Aug 2026, 00:37 | 5,345 | +3 |
| 19 Aug 2026, 17:28 | 5,342 | +3 |
| 13 Aug 2026, 04:03 | 5,339 | +3 |
| 10 Aug 2026, 09:45 | 5,336 | -6 |
| 7 Aug 2026, 16:01 | 5,342 | no change |
| 7 Aug 2026, 13:02 | 5,342 | first reading |
11 posts held, back to 30 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 7 pages of Telegram’s post history, 20 posts per page.
Nothing published in the last 30 days. ERR and ER are rolling 30-day measures, so there is nothing to compute — we hold 11 posts for this entry, the most recent from 11 August 2026. An engagement rate over an empty window would be a number about nothing.
44 reactions across 7 posts, in 4 distinct kinds. The most used accounts for 56.8% of them.
| Reaction | Count | Share | Share, drawn |
|---|---|---|---|
| ❤ | 25 | 56.8% | |
| 🔥 | 8 | 18.2% | |
| ❤🔥 | 7 | 15.9% | |
| 👍 | 4 | 9.09% |
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 7 of the 11 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 44 reactions in total: the kind of figure the paragraph above means by “a reaction total printed elsewhere on the page”.
Measured over the 11 most recent posts we hold, published 30 July 2026 to 11 August 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.
19 августа в 11:00 приглашаю врачей на бесплатный вебинар «PBM vs PDT: где заканчивается фотохимия и начинается биостимуляция?» Разберём механизмы без маркетинговых мифов и, главное, переведём фотобиологию на язык клинической практики: какие параметры действительно имеют значение, где находится терапевтическое окно и как осознанно выбирать световое воздействие под конкретную клиническую задачу. Зарегистрироваться⤵️ …
Теперь к практикуму по МОНОПОЛЯРНОМУ RF можно присоединиться онлайн Мы знаем, что многие врачи хотели попасть на практикум 22 августа в Москве, но не у всех есть возможность приехать лично. Поэтому мы открываем онлайн-участие. Это не сокращенная версия и не отдельный вебинар. Вы подключаетесь к практикуму в режиме реального времени и вместе с очными участниками проходите всю программу — от электрофизики RF и анали…
🔥6❤1
Photo, posted without a caption
22 августа на практикуме в Москве мы подробно разберем температурную биологию тканей при монополярном RF. Не по рекламным материалам производителей, а с позиции электрофизики, термобиологии и клинической безопасности. Вы научитесь понимать, какая температура полезна для каждой ткани, когда начинается терапевтический эффект и где проходит граница, за которой прогрев перестает лечить и начинает повреждать. Именно это …
❤🔥4
Photo, posted without a caption
Photo, posted without a caption
📍22 августа, Москва — практикум «Монополярный RF: от электрофизики тканей к управляемому результату». На практикуме мы подробно разберем: * почему одинаковые цифры в паспорте могут давать совершенно разные клинические результаты; * какие технические характеристики действительно имеют значение при выборе монополярного RF; * как анализировать аппарат с позиции физиотерапевта, а не маркетолога; * и как выбирать технол…
❤2🔥1
Именно этим вопросам будет посвящен мой авторский практикум в Москве 22 августа — «Монополярный RF: от электрофизики тканей к управляемому результату». Мы подробно разберем, как частота, импеданс, мощность, площадь электрода, охлаждение, скорость движения манипулы и накопление тепла меняют клинический результат, и научимся выбирать параметры, исходя из биологии тканей, а не из инструкции производителя https://bragi…
❤4
Самая большая проблема монополярного RF, о которой почти не говорят Коллеги, на поверхности кожи мы поддерживаем температуру 38-42 °C. А вот какая температура в этот момент формируется в подкожно-жировой клетчатке? И вот здесь начинается самое интересное. На поверхности кожи мы можем измерить температуру. Но температуру в глубине тканей мы напрямую не измеряем. Мы лишь предполагаем ее, исходя из многих факторов…
❤18🔥1
Video, posted without a caption
👍4
Именно поэтому на своем практикуме 22 августа «Монополярный RF: от электрофизики тканей к управляемому результату» мы будем обсуждать не только параметры аппарата. Мы разберем гораздо более важные вопросы: — как определить ткань-мишень; — когда монополярный RF действительно показан; — где его место в комплексной стратегии лечения; — как сочетать его с IPL, лазерами, коллагеностимуляторами, инъекционными и ультразву…
❤🔥3
Showing the 11 most recent of 11 posts we hold for @Dr_Bragina. 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.
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.
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.
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.
This channel appears in 5 seed channels' Telegram-generated recommendation lists in total. Each is Telegram’s list for THAT channel, not this one — see how this is measured.
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 18 September 2026 — this entry's latest reading, not the date you are reading this.
“Dr_Bragina Аппаратная физиотерапия” (@Dr_Bragina), 5,400 subscribers as measured 18 September 2026. Telegram Register, tgregister.com/channel/Dr_Bragina.
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.