4 measurements spanning 9 days, net -14. 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 5,335–5,353 and does not start at zero.
Measurement log — every subscribers count we have recorded
Measured (UTC)
Subscribers
Change
16 Aug 2026, 04:54
5,337
-8
12 Aug 2026, 07:06
5,345
-6
6 Aug 2026, 22:44
5,351
no change
6 Aug 2026, 19:32
5,351
first reading
Engagement
21 posts held, back to 4 December 2025 — the reader has not yet reached the start of this channel’s public history, so older posts may sit further back, unread. Read across 8 pagesof Telegram’s post history, 20 posts per page.
ERR · 30 days
10.2%
avg views ÷ 5,337 subscribers
Avg views / post
543
3 posts measured
Reaction rate
0.983%
reactions ÷ views · ER floor
Posts in window
3
of 21 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.
What these figures were computed from
Window
Rolling 30 days · latest post in window 10 August 2026
Posts held
21 (4 December 2025 – 10 August 2026)
Views total
1,628
Reactions total
16
Forwards / comments
not exposed by the public surface — not measured, not estimated
Readings taken
12 Aug 2026, 04:25 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
15m 36s
Average length
7m 48s
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
245 reactions across 18 posts, in 7 distinct kinds. The most used accounts for 25.7% of them.
Every reaction kind recorded on the sample, most used first
Reaction
Count
Share
Share, drawn
👍
63
25.7%
🤩
60
24.5%
👏
33
13.5%
😢
30
12.2%
💯
28
11.4%
🔥
25
10.2%
⚡
6
2.45%
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 18 of the 21 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 245reactions in total: the kind of figure the paragraph above means by “a reaction total printed elsewhere on the page”.
Measured over the 21 most recent posts we hold, published 4 December 2025 to 10 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.
📌 اختر المجلة العلمية الأنسب لبحثك وقدّمه للنشر بثقة
فإن اختيار المجلة الخطأ قد يؤخر نشر بحثك لأشهر طويلة أو يوقعك في إحدى المجلات المفترسة!
لذلك ندعوك للانضمام الآن لورشتنا التفاعلية التطبيقية المميزة والمكثفة في نسختها الثانية بعنوان:
Smart Journal Selection for Researchers ✔️
المعتمدة من The British CPD Standards Office 🎓
ومناسبة للباحثين بكل التخصصات؛ الطبية وغير الطبية ✅
(مناسبة أكثر لمن سينشر ورقته باللغة ا…
إنجاز أكاديمي متميز للدكتور أيمن القنة في الإحصاء الحيوي التطبيقي
تتقدم MedOne Academy بالتهنئة والتبريك للدكتور أيمن القنة، رئيس قسم الاستشارات البحثية في الأكاديمية، بمناسبة حصوله على:
Professional Certificate in Applied Biostatistics: Methods & Applications – Core Curriculum and Advanced Topics
وهي شهادة مهنية متقدمة صادرة عن Harvard Catalyst | The Harvard Clinical and Translational Science Center، مركز هارفارد لل…
🩺 تدريب في الكتابة البحثية للتخصصات الطبية والصحية فقط
موجه لكل من يرغب بالانتقال من مسودة بحثية ضعيفة إلى ورقة أقوى وأكثر جاهزية للنشر .. وهذا بشكل مستقل عن الذكاء الاصطناعي ✅
▪️استجابة لطلب الكثير من الباحثين فإنه يسر منصة MedOne Academy أن توفر هذا التدريب العملي المكثف والذي يهدف إلى تطوير مهارات كتابة الأوراق البحثية الطبية وتحويل الأفكار والمسودات الأولية إلى أوراق أكثر قوة ووضوحًا وجاهزية للنشر .. بعنوان:
📄 …
📌 هل انتهيت من كتابة بحثك لكنك لا تعرف أي مجلة هي الأنسب للنشر؟
اختيار المجلة المناسبة لا يقل أهمية عن جودة البحث نفسه. فالاختيار الخاطئ قد يؤدي إلى رفض البحث، أو تأخير النشر لأشهر طويلة، أو حتى الوقوع في فخ المجلات غير الموثوقة.
📢 لذلك يسرنا أن نعلن عن اطلاق ورشة تفاعلية جديدة بعنوان:
Smart Journal Selection for Researchers ✔️
ورشة تفاعلية مكثفة تساعدك على اختيار المجلة المناسبة لبحثك بثقة، وفهم كيفية تقييم المج…
⚠️ البرنامج تفاعلي والمقاعد محدودة فلا تنتظر اللحظة الأخيرة
واغتنم الآن فرصتك البحثية المميزة ⭐️:
🔬 مع برنامجنا التدريبي المكثف والمحدث
والأول من نوعه بالبلاد العربية .. بعنوان:
AI-Assisted Scientific Writing – From Literature Search to Publication
📄 يسير معك خطوة بخطوة ليساعدك على الاستعانة بالذكاء الاصطناعي بدقة وكفاءة في كتابة أوراقك البحثية
🧠 يشتمل على أكثر من 30 مهارة دقيقة مدعّمة بتطبيقات عملية
🚀 يساعدك لتضاع…
✅ يسرنا أنه تم إنهاء فعاليات ورشة:
Methodological Errors in Medical Research: Independent and Using #AI
مع أ.د. إياد #قنيبي و د. أيمن القنة، بحضور وتفاعل مميز من زملاء من تخصصات #طبية منوعة.
✨ إنجاز علمي جديد يُضاف لمسيرتنا في MedOne Academy.
حيث تم نشر ورقة علمية مميزة لإحدى فرقنا البحثية في مجلة:
JMIR Medical Education
وهي مجلة عالمية ذات التصنيف الأعلى في مجال التعليم الطبي ✅
البحث تناول تأثير استخدام الذكاء الاصطناعي بشكل منهجي على الكفاءة السريرية للأطباء، وأُنجز تحت إشراف:
✓ الأستاذ الدكتور إياد قنيبي
✓ الدكتور أيمن القنة
وذلك ضمن برنامجنا البحثي الفريد من نوعه في العالم العربي:
International …
🔥13👏6👍2💯1
Showing the 12 most recent of 21 posts we hold for @MedOneAcademy. 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 — 812,523 of 1,481,346entries 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
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.
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.
فِقْهُ الطَّبِيب"ما لا يسَعُ المسلم الطبيب جهله" @fiqh_altabib · 96,160 Telegram ranks this channel #24 of 97 here — alongside 96 others — read 16 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 16 August 2026 — this
entry's latest reading, not the date you are reading this.
“MedOne Academy” (@MedOneAcademy), 5,337 subscribers as measured 16 August 2026. Telegram Register, tgregister.com/channel/MedOneAcademy.
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.