Health & wellness — 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 11 September 2026 and assigned it the closest of 31 fixed categories, at 100% 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
53 measurements spanning 95 days, net -129. 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 10,788–10,962 and does not start at zero.
Measurement log — every subscribers count we have recorded, most recent 20 of 53
Measured (UTC)
Subscribers
Change
10 Nov 2026, 13:39
10,813
+4
7 Nov 2026, 12:22
10,809
+1
4 Nov 2026, 14:16
10,808
-2
2 Nov 2026, 16:58
10,810
-1
1 Nov 2026, 17:40
10,811
-4
31 Oct 2026, 14:29
10,815
-1
30 Oct 2026, 15:26
10,816
-2
29 Oct 2026, 16:27
10,818
+1
28 Oct 2026, 13:39
10,817
-3
27 Oct 2026, 14:04
10,820
-7
26 Oct 2026, 14:07
10,827
-2
24 Oct 2026, 19:07
10,829
-1
23 Oct 2026, 21:35
10,830
-5
22 Oct 2026, 22:09
10,835
-4
21 Oct 2026, 21:07
10,839
-3
19 Oct 2026, 14:14
10,842
+3
18 Oct 2026, 16:28
10,839
-2
17 Oct 2026, 18:31
10,841
-1
16 Oct 2026, 20:46
10,842
-4
15 Oct 2026, 18:19
10,846
first reading
Engagement
75 posts held, back to 19 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 55 pages of Telegram’s post history, 20 posts per page.
ERR · 30 days
7.25%
avg views ÷ 10,813 subscribers
Avg views / post
784
26 posts measured
Reaction rate
3.49%
reactions ÷ views · ER floor
Posts in window
27
of 75 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 23 of 26 measured posts that carry a reaction reading, and over those same posts' views.
What these figures were computed from
Window
Rolling 30 days · latest post in window 9 November 2026
Posts held
75 (19 July 2026 – 9 November 2026)
Views total
20,377
Reactions total
623
Forwards / comments
not exposed by the public surface — not measured, not estimated
Readings taken
10 Nov 2026, 09:16 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
1h 25m
Average length
1m 45s
Measured directly from 49 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
1,827 reactions across 71 posts, in 9 distinct kinds. The most used accounts for 43.9% of them.
Every reaction kind recorded on the sample, most used first
Reaction
Count
Share
Share, drawn
❤
802
43.9%
👍
646
35.4%
🔥
134
7.33%
🙏
112
6.13%
🥰
70
3.83%
👌
50
2.74%
👏
10
0.547%
🤔
2
0.109%
😍
1
0.055%
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 71 of the 75 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 1,827 reactions in total: the kind of figure the paragraph above means by “a reaction total printed elsewhere on the page”.
Measured over the 75 most recent posts we hold, published 19 July 2026 to 9 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.
Telegram Stars
Stars received
1
across the posts below
Posts paid on
1
of 74 we hold a reading for · 1%
Most on one post
1
single highest reading
A paid reaction is a reader spending Telegram Stars — bought with money — on a post by @olga_bockeria. Telegram publishes the count on the public post preview alongside ordinary reactions, and this register reads it there. It is the only figure on this site that measures money moving rather than attention.
Stars are not reactions, and the two are never added. They are rendered in the same strip on Telegram and counted in the same shape, but one is a tap and the other is a purchase. The reaction totals and the engagement rate elsewhere on this page exclude every figure in this section, and no rate here is computed against a reaction count.
This is not revenue, and we publish no currency figure. What a Star costs a reader and what it pays a channel are different numbers, Telegram takes a share we cannot observe, and the terms have changed. Converting a Star count into money would be an estimate dressed as a measurement, so the count is where we stop.
Counted over the 75 most recent posts we hold for this entry, published 19 July 2026 to 9 November 2026. Star counts above 1,000 reach us in Telegram’s short form and carry the same three-significant-figure rounding as everything else on this page.
Recent posts
Telegram’s own ‘edited’ marker: 11 of 27 posts held from the last 30 days (40.7%) 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).
🫀Атеросклероз: почему у одних сосуды стареют быстрее, чем у других?
Атеросклероз может годами развиваться незаметно, постепенно сужая артерии и повышая риск инфаркта и инсульта.
Почему образуются атеросклеротические бляшки, что ускоряет их рост и от чего зависит риск опасных осложнений? Разбираю в этом видео.
Но главное — на многие факторы риска мы можем повлиять!
Курение, повышенное давление, недостаточная физич…
HeartAge 45
План питания «Остановите атеросклероз»
Антиэйдж, контроль веса и холестерина — без голода и крайностей.
Что такое HeartAge 45?
HeartAge 45 — моя авторская программа питания для тех, кто хочет снизить вес, позаботиться о сердце и сосудах и сохранить здоровье с возрастом. В основе — средиземноморский подход к питанию, готовое меню на 45 дней и понятный план, который можно встроить в повседневную жизнь б…
Продолжаю разбирать ваши вопросы из рубрики вопрос - ответ
Именно печень производит значительную часть холестерина в нашем организме. Но обычные печёночные пробы не отражают процесс производства холестерина.
Поэтому нормальные АЛТ и АСТ вовсе не гарантируют нормальный уровень холестерина!
А ещё на липидный обмен влияет щитовидная железа. При гипотиреозе уровень ЛПНП может повышаться, даже если вы правильно питает…
Продолжаю отвечать на ваши вопросы рубрики вопрос - ответ.
Сегодня разбираем две ситуации, с которыми многие сталкиваются на практике.
🔹 Как правильно подготовиться к липидограмме? Нужно ли специально менять рацион перед анализом? И почему нам важно увидеть реальные показатели, а не результат нескольких дней ограничений?
🔹 Субклинический гипотиреоз и повышенный холестерин. Как связаны щитовидная железа и липидный …
А вы знали, что организм продолжает расходовать энергию даже после окончания тренировки? 🔥
Тренировки с высоким пульсом позволяют сжигать большое количество калорий за относительно короткое время.
Во время интенсивной нагрузки мышцы активно используют глюкозу и жирные кислоты для производства энергии. А после тренировки организм продолжает восстанавливаться, расходуя дополнительные калории — даже когда вы отдыхаете…
Принимаете кальций, чтобы укрепить кости? А что, если у вас уже обнаружили кальциноз аорты или других сосудов?
Вот тут и возникает вопрос: продолжать принимать кальций или отказаться от него?
На самом деле всё не так просто!
Кальций необходим нашему организму — без него невозможно поддерживать здоровье костей, мышц и нервной системы. Но кальцификация сосудов — совсем другой процесс, в котором участвуют сложные мех…
Продолжаю отвечать на ваши вопросы! ❤️
Сегодня у нас сразу три вопроса и каждый заслуживает отдельного разговора.
🫀 «Сосуды играют» — что это вообще означает? Можно ли по такому ощущению судить о состоянии сосудов?
❤️ Кальциноз аорты — насколько это опасно? Откуда берётся кальций в сосудистой стенке и какое отношение к этому имеет атеросклероз?
🌿 Могут ли растительные препараты снижать холестерин? Обсудим бергам…
💊 Есть ли смысл принимать статины при повышенном липопротеине - А?
Вопрос, который мне задала подписчица.
Липопротеин - А, или Lp - А, — особый фактор сердечно-сосудистого риска, уровень которого в значительной степени определяется наследственностью.
И вот что многих удивляет: статины практически не снижают Lp - А, но при этом могут существенно уменьшать риск инфаркта и инсульта!
Почему?
Потому что они снижают Л…
Холестерин снизился — можно перестать принимать статины?
Это один из самых частых вопросов, которые вы мне задаёте!
Продолжаю отвечать на вопросы подписчиков о холестерине и здоровье сердечно-сосудистой системы.
Сегодня обсуждаем:
🔹 Если холестерин нормализовался на фоне приёма статинов, можно ли уменьшить дозу или совсем отменить препарат?
🔹 Есть ли у меня самой повышенный холестерин и наследственная предраспол…
Осень в самом разгаре! 🍁 Яркие краски, семейные встречи, праздники, любимые занятия… И, конечно, сезон простуд и гриппа.
В это время многие начинают искать витамины и добавки «для иммунитета».
А я всё больше убеждаюсь, что забота о здоровье начинается не с покупки очередной баночки. ❤️
Полноценный сон, хорошее питание, движение, меньше стресса и больше времени на то, что приносит нам радость.
И, конечно, не забыв…
❤8👍5🙏1
Showing the 12 most recent of 75 posts we hold for @olga_bockeria. 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 poll we hold for this entry, as Telegram rendered it when we read the post. A poll’s figures keep moving after that, so each one is dated.
Shares as published. 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 75 most recent posts we hold, published 19 July 2026 to 9 November 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.
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.
Кардиолог Чайковская @cardiolog_chaykovskaya · 57,914 Telegram ranks this channel #6 of 94 here — alongside 93 others — read 23 August 2026
This channel appears in 1 seed channel's Telegram-generated recommendation list 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 10 November 2026 — this
entry's latest reading, not the date you are reading this.
“Кардиолог Ольга Бокерия” (@olga_bockeria), 10,813 subscribers as measured 10 November 2026. Telegram Register, tgregister.com/channel/olga_bockeria.
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.