Telegram RegisterThe public register of Telegram

Channel

Медскан во благо

@medscanblago

On this record: Growth · Engagement · What this channel posts · Reactions · Posts · Citations · Cite this entry

27subscribers

+1 since we began measuring on 6 August 2026

Risers and fallers across the register · movement among entries of Under 1,000.

Register entry

Telegram ID-1002353640068
TypeChannel
Username@medscanblago
CreatedBetween 1 September 2024 and 31 March 2025— estimated from Telegram’s id allocation, not measured. How this range is calculated.
First recorded11 August 2026
Last confirmed live13 August 2026
Measurements held3
Confirmed unchanged1 time, most recently 13 August 2026
On Telegramt.me/medscanblago

Growth

262726.56 August 2026 — 26 subscribers11 August 2026 — 26 subscribers13 August 2026 — 27 subscribers6 August 202613 August 2026
3 measurements spanning 7 days, net +1. 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 26–27 and does not start at zero.
Measurement log — every subscribers count we have recorded
Measured (UTC)SubscribersChange
13 Aug 2026, 01:3427+1
11 Aug 2026, 08:0126no change
6 Aug 2026, 12:0226first reading

Engagement

10 posts held, back to 17 February 2026the reader has not yet reached the start of this channel’s public history, so older posts may sit further back, unread. Read across 1 pageof Telegram’s post history, 20 posts per page.

ERR · 30 days
27.8%
avg views ÷ 27 subscribers
Avg views / post
7.5
2 posts measured
Reaction rate
25.0%
reactions ÷ views · ER floor
Posts in window
2
of 10 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. It is computed over the 1 of 2 measured posts that carry a reaction reading, and over those same posts' views.

What these figures were computed from
WindowRolling 30 days · latest post in window 7 August 2026
Posts held10 (17 February 20267 August 2026)
Views total15
Reactions total2
Forwards / commentsnot exposed by the public surface — not measured, not estimated
Readings taken11 Aug 2026, 08:01 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
3m 50s
Average length
1m 55s

Measured directly from 2 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

18 reactions across 8 posts, in 6 distinct kinds. The most used accounts for 44.4% of them.

Every reaction kind recorded on the sample, most used first
ReactionCountShareShare, drawn
844.4%
👏422.2%
👍211.1%
💘211.1%
🎉15.56%
💯15.56%

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 8 of the 10 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 18reactions in total: the kind of figure the paragraph above means by “a reaction total printed elsewhere on the page”.

Measured over the 10 most recent posts we hold, published 17 February 2026 to 7 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.

Recent posts

7 Aug 2026, 14:33 UTC7 viewsread 11 August 2026
Photo

🩵 Кто такой равный консультант? Равный консультант — это человек, прошедший путь лечения заболевания, находящийся в ремиссии или стабилизации, который готов поддержать тех, кто только сталкивается с этим непростым этапом жизни. 🔹В АНО «Медскан во благо» мы развиваем проект «Равное консультирование», объединяющий людей с онкологическим опытом, которые прошли специальную подготовку. Каждый консультант обучается навык

5 Aug 2026, 14:16 UTC8 views2 reactionsread 11 August 2026
Forwarded from @Medscan_GroupVideo

«Медскан во благо»: когда желание помогать объединяет людей АНО «Медскан во благо» объединяет социальные, образовательные и благотворительные проекты ГК «Медскан». Сегодня команда развивает сразу несколько направлений: «Сообщество молодых учёных» помогает студентам-медикам делать первые шаги в науке вместе с ведущими специалистами. «Равное консультирование» объединяет людей с онкологическим опытом, чтобы каждый м

👍2

5 Jun 2026, 07:05 UTC33 views3 reactionsread 11 August 2026
Photo

📣 30 мая в Москве прошел «Зеленый марафон» Сбера 🏃‍♀️‍➡️Десятки тысяч людей по всей стране вышли на старт, но для нас главными героями стали наши равные консультанты, пациенты с опытом лечения онкологии, и их родные. За плечами участниц — диагноз «рак молочной железы» и долгий путь лечения. 🌟Своим примером они доказали главное: жизнь после диагноза не просто возможна — она может быть полна спорта, драйва и побед.

2👏1

22 May 2026, 13:25 UTC36 views2 reactionsread 11 August 2026
Forwarded from @Medscan_GroupPhoto

Музыка объединяет: студенты-волонтёры «Медскан» познакомились с музыкальными сказками русских композиторов 21 мая в фармацевтическом колледже «Новые знания» — партнёре ГК «Медскан» — прошёл концерт «Музыкальные сказки русских композиторов». Гостями вечера стали студенты Волонтёрского центра и Сообщества молодых учёных «Медскан» из Индии, Ирана, Израиля, Ботсваны и России. Пианисты Алексей Сканави и Юлия Куликова ис

2

13 May 2026, 15:04 UTC35 views3 reactionsread 11 August 2026
Photo

Искусство как терапия: волонтёры и молодые учёные «Медскан» на выставке «ВМЕСТЕ» 🔹Впервые в России столь масштабную выставку открыли прямо в медицинском учреждении. 🔹Здесь представлены более 200 произведений искусства: от скульптуры до интерактивных зон и открытых лекций. 🔹Часть картин после завершения выставки останется в Московской городской больнице, чтобы поддерживать терапевтическую атмосферу и продолжать «лечи

2💯1

27 Apr 2026, 09:51 UTC38 views1 reactionsread 11 August 2026
Forwarded from @Medscan_GroupPhoto

День донора в «Медскан»: участники Волонтерского центра Медскан | Hadassah из разных стран сдали кровь 20 апреля, в Национальный день донора крови, участники Волонтёрского центра на базе Медскан | Hadassah посетили отделение переливания крови в центре имени Бакулева. Донорская кровь нужна постоянно. И важно, что будущие врачи из разных стран включаются в эту систему уже во время обучения, разделяя ценности российск

1

17 Mar 2026, 13:22 UTC28 views1 reactionsread 11 August 2026
Forwarded from @Medscan_GroupPhoto

Весна внутри: встреча онкопациентов и равных консультантов Когда рядом врачи, люди с похожим опытом и пространство для открытого разговора — становится легче задавать вопросы, делиться переживаниями и находить опору. В клинике Медскан | Hadassah прошло мероприятие для онкопациентов, организованное при поддержке АНО «Медскан во благо». Встреча объединила пациентов, равных консультантов и врачей, чтобы обсудить совре

1

2 Mar 2026, 14:59 UTC31 views2 reactionsread 11 August 2026
Forwarded from @Hadassah_Medical_MoscowPhoto

Медскан выступил партнером благотворительного мероприятия “Добрая лыжня” Гонка объединила профессиональных спортсменов и любителей беговых лыж и активного отдыха. Она прошла уже во второй раз на одной из лучших лыжных трасс Подмосковья — на знаменитой «Лазутинке» в Одинцово. ❄️ Шатер «Медскан во благо» стал настоящей точкой притяжения для всех участников, где мы согревали гостей чаем и угощениями, собирали средства

🎉1👏1

18 Feb 2026, 11:32 UTC41 views4 reactionsread 11 August 2026
Photo

🌸 Весна внутри: встреча Равных консультантов 5 марта Каждый год в Hadassah Medical Moscow мы собираемся на встречу Равных консультантов — чтобы быть рядом, поддержать друг друга и напомнить: путь восстановления легче, когда ты не один. 🔹Наша мартовская встреча посвящена заботе о себе и маленьким шагам, которые помогают возвращаться к привычной жизни. 🔹Мы поговорим о физической реабилитации и питании, поделимся опы

👏2💘2

17 Feb 2026, 11:47 UTC33 viewsread 11 August 2026
Forwarded from @Medscan_GroupVideo

Запускаем «Энерголетие» — первый в мире медийный акселератор технологий активного долголетия Проект инициирован ГК «Медскан» при поддержке Госкорпорации «Росатом». Экспертную часть возглавляет доктор Кирилл Маслиев — он формирует пул участников и отвечает за отбор проектов. Наша задача — создать среду, в которой соединяются клиническая практика, фундаментальная наука и высокие технологии. Мы ищем тех, кто способен

Showing the 10 most recent of 10 posts we hold for @medscanblago. 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.

Citation-graph rank

Citation-graph rank — 888,965 of 1,340,412entries in the measured graph. A weighted position computed from the forward and mention edges below — republished posts weigh more than named mentions — and recomputed periodically, over the whole graph. Published only as this ordinal position, never as a score: a position is a fact, and a score printed beside one channel’s name would read as a verdict this register does not make. The two counts beneath stay separate for the same reason mentions are never summed with forwards anywhere else on this page — a named-by count costs nothing to manufacture. The top 100 by this measure, or how it is computed.

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

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.

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

“Медскан во благо” (@medscanblago), 27 subscribers as measured 13 August 2026. Telegram Register, tgregister.com/channel/medscanblago.

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.