Telegram RegisterThe public register of Telegram

Channel

Врач-флеболог Савин Эльдар

@flebologSavin

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

274subscribers

+0 since we began measuring on 7 August 2026

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

Register entry

Telegram ID-1002617814247
TypeChannel
Username@flebologSavin
CreatedBetween 1 March 2025 and 31 July 2025— estimated from Telegram’s id allocation, not measured. How this range is calculated.
First recorded7 August 2026
Last confirmed live7 August 2026
Measurements held2
Confirmed unchanged1 time, most recently 7 August 2026
On Telegramt.me/flebologSavin

Growth

2747 Aug 2026, 05:18 — 274 subscribers7 Aug 2026, 15:46 — 274 subscribers7 Aug 2026, 05:187 Aug 2026, 15:46
2 measurements taken within a single day. 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 273–275 and does not start at zero.
Measurement log — every subscribers count we have recorded
Measured (UTC)SubscribersChange
7 Aug 2026, 15:46274no change
7 Aug 2026, 05:18274first reading

Engagement

20 posts held, back to 7 April 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
57.3%
avg views ÷ 274 subscribers
Avg views / post
157
4 posts measured
Reaction rate
5.05%
reactions ÷ views · ER floor
Posts in window
4
of 20 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 2 of 4 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 29 July 2026
Posts held20 (7 April 202629 July 2026)
Views total628
Reactions total15
Forwards / commentsnot exposed by the public surface — not measured, not estimated
Readings taken7 Aug 2026, 05:18 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

92 reactions across 11 posts, in 5 distinct kinds. The most used accounts for 45.7% of them.

Every reaction kind recorded on the sample, most used first
ReactionCountShareShare, drawn
👍4245.7%
🔥3942.4%
🤝77.61%
22.17%
💔22.17%

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 11 of the 20 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 92reactions in total: the kind of figure the paragraph above means by “a reaction total printed elsewhere on the page”.

Measured over the 20 most recent posts we hold, published 7 April 2026 to 29 July 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

29 Jul 2026, 13:09 UTC110 views7 reactionsread 7 August 2026

❓ Почему у одного человека варикоз не развивается никогда, а другому операция требуется уже в 35–40 лет? Какие ещё факторы влияют на развитие варикозной болезни? Потому что наследственность — важный, но далеко не единственный фактор. 🧬 Наследственная предрасположенность Человек может унаследовать особенности строения венозной стенки, из-за которых она легче растягивается и хуже сопротивляется длительной нагрузке. Но

🔥7

20 Jul 2026, 05:48 UTC187 views8 reactionsread 7 August 2026

📊 Результаты опроса 78% подписчиков считают, что сначала перестаёт работать венозный клапан, и только потом развивается варикозная болезнь. 🩺 И это неудивительно Именно так долгое время считалось и в научном мире. Согласно классической теории, сначала развивается несостоятельность клапана. Из-за этого кровь начинает течь в обратном направлении, давление в поверхностных венах повышается, и постепенно формируется вари

👍8

8 Jul 2026, 16:20 UTC312 views5 reactionsread 7 August 2026

В прошлом посте мы разобрались, зачем в венах нужны клапаны. Но тогда возникает следующий вопрос. 🤔 Почему клапан вдруг перестаёт работать? Представьте обычную дверь. Пока петли исправны, она плотно закрывается. Но со временем дверь может немного перекоситься. Она по-прежнему закрывается, но между дверью и коробкой появляется небольшая щель. С венозными клапанами происходит похожая история. Пока стенка вены сохраняет

👍5

2 Jul 2026, 07:10 UTC386 views12 reactionsread 7 August 2026

В прошлом посте мы разобрались, что варикозная болезнь начинается с изменения направления движения крови. Но тогда возникает следующий вопрос. 🤔 А зачем вообще в венах нужны клапаны? Давайте представим, что их просто нет. Когда мы идём, мышцы голени помогают крови двигаться вверх — к сердцу. ⬆️ Но как только мы останавливаемся, начинает действовать сила тяжести. ⬇️ Без клапанов кровь каждый раз стекала бы обратн

🔥12

28 Jun 2026, 19:21 UTC359 views17 reactionsread 7 August 2026
Photo

Большинство подписчиков в опросе ответили, что пришли сюда узнать чуточку больше о варикозе. Поэтому начну именно с этого. 😊 На мой взгляд, чтобы понять варикозную болезнь, не нужно сразу разбираться в сложной анатомии или медицинских терминах. Достаточно понять одну простую вещь — как меняется направление движения крови. На схеме изображена глубокая венозная система. Именно она в норме переносит около 90% крови от н

👍17

22 Jun 2026, 06:41 UTC346 viewsread 7 August 2026

👋 Всем привет! За последние несколько дней на канал подписалось много новых людей, поэтому решил познакомиться поближе. Меня зовут Эльдар Савин, я врач-флеболог. На приёмах я часто вижу одну и ту же ситуацию. Человек приходит не только с заболеванием, но и с огромным количеством информации, которую успел прочитать до визита к врачу. Статьи в интернете, форумы, советы знакомых, ролики в социальных сетях, иногда да

Showing the 12 most recent of 20 posts we hold for @flebologSavin. 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 — 1,034,387 of 1,160,990entries 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

Republishes

Channels on the register whose posts this channel has forwarded.

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 2 registered channels — 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.

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

“Врач-флеболог Савин Эльдар” (@flebologSavin), 274 subscribers as measured 7 August 2026. Telegram Register, tgregister.com/channel/flebologSavin.

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.