Channel
@Cardiology_Updates
On this record: Topic · Growth · Engagement · Reactions · Posts · Citations · Telegram's recommendations · Cite this entry
20,112subscribers
+1,187 since we began measuring on 6 August 2026
Risers and fallers across the register · movement among entries of 10,000–31,623.
| Telegram ID | -1001448704621 |
|---|---|
| Type | Channel |
| Username | @Cardiology_Updates |
| Created | Between 1 April 2019 and 31 October 2021 — estimated from Telegram’s id allocation, not measured. How this range is calculated. |
| First recorded | 6 August 2026 |
| Last confirmed live | 12 October 2026 |
| Measurements held | 37 |
| Confirmed unchanged | 1 time, most recently 12 October 2026 |
| On Telegram | t.me/Cardiology_Updates |
Science — 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 10 September 2026 and assigned it the closest of 31 fixed categories, at 77% 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 |
|---|---|---|
| 12 Oct 2026, 17:35 | 20,112 | +81 |
| 8 Oct 2026, 06:56 | 20,031 | +82 |
| 3 Oct 2026, 20:39 | 19,949 | +98 |
| 25 Sept 2026, 04:58 | 19,851 | +137 |
| 18 Sept 2026, 22:38 | 19,714 | +48 |
| 16 Sept 2026, 10:37 | 19,666 | +37 |
| 14 Sept 2026, 15:58 | 19,629 | +26 |
| 13 Sept 2026, 03:01 | 19,603 | +44 |
| 11 Sept 2026, 07:37 | 19,559 | +29 |
| 8 Sept 2026, 11:58 | 19,530 | +53 |
| 5 Sept 2026, 10:01 | 19,477 | +23 |
| 3 Sept 2026, 12:59 | 19,454 | +10 |
| 2 Sept 2026, 09:22 | 19,444 | +15 |
| 1 Sept 2026, 09:34 | 19,429 | +8 |
| 31 Aug 2026, 12:04 | 19,421 | +18 |
| 30 Aug 2026, 08:37 | 19,403 | +30 |
| 29 Aug 2026, 06:57 | 19,373 | +21 |
| 28 Aug 2026, 08:54 | 19,352 | +5 |
| 27 Aug 2026, 10:07 | 19,347 | +31 |
| 26 Aug 2026, 06:43 | 19,316 | first reading |
32 posts held, back to 26 June 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.
Nothing published in the last 30 days. ERR and ER are rolling 30-day measures, so there is nothing to compute — we hold 32 posts for this entry, the most recent from 2 September 2026. An engagement rate over an empty window would be a number about nothing.
32 reactions across 17 posts, in 3 distinct kinds. The most used accounts for 87.5% of them.
| Reaction | Count | Share | Share, drawn |
|---|---|---|---|
| ❤ | 28 | 87.5% | |
| 👍 | 3 | 9.38% | |
| 🙏 | 1 | 3.13% |
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 23 of the 32 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 32 reactions in total: the kind of figure the paragraph above means by “a reaction total printed elsewhere on the page”.
Measured over the 32 most recent posts we hold, published 26 June 2026 to 2 September 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.
Langendorff-free dissociation of adult mouse hearts https://www.nature.com/articles/s41569-026-01346-z Nature Reviews Cardiology, Published online: 02 September 2026; doi:10.1038/s41569-026-01346-z (https://www.nature.com/articles/s41569-026-01346-z)In this Tools of the Trade, Ackers-Johnson and Pavlovic describe a Langendorff-free approach to isolate cardiomyocytes without the technical hurdles associated with the …
Identifying the coronary metabolic dilator https://www.nature.com/articles/s41569-026-01345-0 Nature Reviews Cardiology, Published online: 01 September 2026; doi:10.1038/s41569-026-01345-0 (https://www.nature.com/articles/s41569-026-01345-0)Adam Goodwill discusses Eric Feigl’s seminal description of coronary physiology and how his paper shaped research into the mechanisms by which coronary blood flow is matched to m…
https://www.instagram.com/updates_in_medicine?igsi=eWJ2N3p2MmxvNXJ0&utm_source=qr
❤1
Dyslipidaemia and hepatic steatosis: mechanisms and implications for lipid-lowering therapy https://www.nature.com/articles/s41569-026-01336-1 Nature Reviews Cardiology, Published online: 27 August 2026; doi:10.1038/s41569-026-01336-1 (https://www.nature.com/articles/s41569-026-01336-1)Dyslipidaemia and hepatic steatosis are interconnected disorders that contribute to the burden of cardiovascular disease. Understand…
❤2
Reply to ‘Bedside epicardial adipose tissue assessment in the era of advanced adipose phenotyping’ https://www.nature.com/articles/s41569-026-01343-2 Nature Reviews Cardiology, Published online: 27 August 2026; doi:10.1038/s41569-026-01343-2 (https://www.nature.com/articles/s41569-026-01343-2)Reply to ‘Bedside epicardial adipose tissue assessment in the era of advanced adipose phenotyping’
Bedside epicardial adipose tissue assessment in the era of advanced adipose phenotyping https://www.nature.com/articles/s41569-026-01344-1 Nature Reviews Cardiology, Published online: 27 August 2026; doi:10.1038/s41569-026-01344-1 (https://www.nature.com/articles/s41569-026-01344-1)Bedside epicardial adipose tissue assessment in the era of advanced adipose phenotyping
Nicotine-containing products and the cardiovascular system: mechanisms and global health implications https://www.nature.com/articles/s41569-026-01331-6 Nature Reviews Cardiology, Published online: 20 August 2026; doi:10.1038/s41569-026-01331-6 (https://www.nature.com/articles/s41569-026-01331-6)In this Review, Münzel and colleagues discuss the available mechanistic, biomarker, preclinical and clinical data on the c…
Cardiovascular research in China: pathways, incentives and editorial implications https://www.nature.com/articles/s41569-026-01341-4 Nature Reviews Cardiology, Published online: 19 August 2026; doi:10.1038/s41569-026-01341-4 (https://www.nature.com/articles/s41569-026-01341-4)The cardiovascular research landscape in China is shaped by a tiered, hospital-centred system, expanding funding opportunities and strong clin…
❤1
Cardiac fibroblast diversity in HFpEF: states, niches, interorgan drivers and targets https://www.nature.com/articles/s41569-026-01335-2 Nature Reviews Cardiology, Published online: 18 August 2026; doi:10.1038/s41569-026-01335-2 (https://www.nature.com/articles/s41569-026-01335-2)Myocardial fibrosis is a key structural and prognostically adverse feature of heart failure with preserved ejection fraction (HFpEF). In t…
❤1
Atherosclerotic plaque-derived microparticles as exporters of thrombotic risk https://www.nature.com/articles/s41569-026-01340-5 Nature Reviews Cardiology, Published online: 18 August 2026; doi:10.1038/s41569-026-01340-5 (https://www.nature.com/articles/s41569-026-01340-5)Tipack Shanmugam discusses a study showing that microparticles released from atherosclerotic plaque can increase thrombotic risk and proposes that…
Uncovering the role of chromatin organization and dynamics in heart disease https://www.nature.com/articles/s41569-026-01338-z Nature Reviews Cardiology, Published online: 11 August 2026; doi:10.1038/s41569-026-01338-z (https://www.nature.com/articles/s41569-026-01338-z)Two studies published in Science explore how 3D chromatin organization and structure can influence cardiac development and promote heart failure.
The biomechanical environment of coronary atherosclerotic plaque rupture https://www.nature.com/articles/s41569-026-01337-0 Nature Reviews Cardiology, Published online: 11 August 2026; doi:10.1038/s41569-026-01337-0 (https://www.nature.com/articles/s41569-026-01337-0)Tsiartas and Bennett discuss the discovery that atheroclerotic plaque vulnerability to rupture arises from the interaction between plaque composition a…
Showing the 12 most recent of 32 posts we hold for @Cardiology_Updates. 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.
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.
Names
Channels on the register whose handles appear in this channel's posts.
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.
Telegram’s own answer, not this register’s. When this register asks Telegram’s API what is similar to this channel, this is the list it returns, in the exact order Telegram returns it — never re-sorted by subscribers or by anything else this register measures. The relationship, and the order, are Telegram’s; we record them and date them, and make no claim of our own about which of these channels actually resemble this one.
Read from Telegram’s recommendation API, most recently 30 September 2026. Telegram holds a list like this for a small and growing share of the register — how this is measured, and why most channel pages show nothing here.
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 49 seed channels' Telegram-generated recommendation lists in total, of which the 24 where it ranks highest are shown above. 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 12 October 2026 — this entry's latest reading, not the date you are reading this.
“Cardiology Updates” (@Cardiology_Updates), 20,112 subscribers as measured 12 October 2026. Telegram Register, tgregister.com/channel/Cardiology_Updates.
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.