4 measurements spanning 7 days, net +41. 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 162–215 and does not start at zero.
Measurement log — every subscribers count we have recorded
Measured (UTC)
Subscribers
Change
14 Aug 2026, 05:28
209
+38
8 Aug 2026, 14:46
171
no change
7 Aug 2026, 17:45
171
+3
7 Aug 2026, 00:02
168
first reading
Engagement
11 posts held, back to 9 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 1 pageof Telegram’s post history, 20 posts per page.
ERR · 30 days
216.3%
avg views ÷ 209 subscribers
Avg views / post
452
10 posts measured
Reaction rate
1.59%
reactions ÷ views · ER floor
Posts in window
10
of 11 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 6 August 2026
Posts held
11 (9 June 2026 – 6 August 2026)
Views total
4,521
Reactions total
72
Forwards / comments
not exposed by the public surface — not measured, not estimated
Readings taken
8 Aug 2026, 14:46 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
72 reactions across 10 posts, in 3 distinct kinds. The most used accounts for 86.1% of them.
Every reaction kind recorded on the sample, most used first
Reaction
Count
Share
Share, drawn
❤
62
86.1%
🔥
7
9.72%
👏
3
4.17%
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 10 of the 11 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 72reactions in total: the kind of figure the paragraph above means by “a reaction total printed elsewhere on the page”.
Measured over the 11 most recent posts we hold, published 9 June 2026 to 6 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.
💉 همهچیز توی چند ثانیه اتفاق میافته...
🔴شیفت اورژانس شلوغه، عجله داری، کارت تموم شده و میخوای سوزن سوچور رو کنار بذاری که یهو...
سوزن میره توی دستت!
اولین فکری که به ذهنت میاد چیه؟ «الان باید چیکار کنم؟» «نیاز به دارو دارم؟» «خطر HIV یا هپاتیت وجود داره؟»
اگر این اتفاق برای خودت یا یکی از همکارات افتاد، فقط کافیه این چند قدم رو یادت باشه.
💉 Needlestick Injury
🚨 اول از همه به این ۳ ویروس فکر کن:
🔶 HBV (هپاتیت…
⭐️01
🎧 در این قسمت از Weekly NEJM Podcast 🎙
مهمترین پیشرفتهای هفته در حوزههای زیر مرور میشوند:
🔶 یافتههایی که میتوانند رویکرد درمان سرطان پروستات، مولتیپل میلوما، درد حاد و نفروپاتی IgA را تحت تأثیر قرار دهند. 💊
🔶 مروری بر اختلالات مرتبط با Platelet Factor 4 (PF4) و بررسی یک کیس بالینی از زخم مزمن و مقاوم بینی.
🔶 در بخش Perspective نیز به موضوعاتی همچون کمک پزشکی به پایان زندگی (Medical Aid in Dying)، اخت…
✅از این هفته یکی از معتبرترین منابع دنیای پزشکی را با هم دنبال میکنیم: 🌎📚
🩺 The New England Journal of Medicine (NEJM)
یکی از معتبرترین ژورنالهای پزشکی
جهان است که جدیدترین پژوهشهای کارآزماییهای بالینی و موضوعات مهم پزشکی را منتشر میکند و سالهاست یکی از منابع اصلی پزشکی مبتنی بر شواهد به شمار میرود. 🔬📊
🎙 از این پس، هر هفته پادکست رسمی NEJM را در کانال منتشر میکنیم؛
خلاصهای از مهمترین مقالات، یافتهها و …
🧪 مسمومیت با متانول؛
✅نکات کلیدی که باید بدانیم
متانول پس از تبدیل شدن به اسید فرمیک باعث ایجاد سمیت میشود؛ ترکیبی که میتواند به اسیدوز متابولیک و آسیب بینایی منجر شود. 👀
در این پوستر مرور میکنیم:
🔶 علائم و یافتههای مهم
🔶 درمان با فومپیزول، اتانول و فولینیک اسید
🔶 اندیکاسیونهای همودیالیز
📚 نکات کاربردی برای مرور سریع در بالین
#MedicaLead #Toxicology
🔴@medica_lead
🩺History & Physical | H&P #01
✅Approach to Acute Pharyngitis
فارنژیت حاد یکی از شایعترین علل مراجعه به درمانگاه و اورژانس است. در این اینفوگرافیک، رویکرد گامبهگام ارزیابی بیمار، از تشخیص موارد اورژانسی تا تصمیمگیری برای انجام تستهای تشخیصی و شروع درمان، بر اساس UpToDate خلاصه شده است. 📝
⬇️پیشنهاد میکنیم این تصویر را Save کنید و در گالری خود یک آلبوم با نام MedicaLead بسازید.
به مرور، این مجموعه به یک مرجع س…
🎖️ Barbara Bates | 1928–2002
🩺باربارا بیتس پزشک متخصص داخلی، مدرس، نویسنده و تاریخنگار پزشکی آمریکایی بود.
🎓او در Smith College و Cornell University تحصیل کرد و بعدها دو مدرک کارشناسی ارشد در رشته تاریخ گرفت.
📚بیتس در چندین دانشگاه آمریکا، از جمله دانشگاههای Kentucky، Rochester، Missouri–Kansas City و در نهایت University of Pennsylvania به تدریس پرداخت.
👍او در دانشگاه پنسیلوانیا هم در دانشکده پزشکی و هم در دانشک…
«زندگی کوتاه است، هنر پزشکی دراز، فرصت گذرا، تجربه فریبنده و قضاوت دشوار است.»
— بقراط
پزشکی یک هنر است ، هنری که باید تمرین کنیم تا هنرمند ماهری شویم ..هنر تشخیص و درمان و ارتباط
در آینده تنها عاملی که پزشکان رو نگه میدارد در برابر AI همین " از جای خود بلند شدن و معاینه و ارتباط خوب با بیمار است"
ارادتمند شما | مدیر تیم پزشکی مدکالید| ■ علیرضا خادم 👨⚕
سلام 🩺
به MedicaLead خوش آمدید. ✨
خوشحالیم که اینجا هستید.
⭐️پزشکی، مسیر یاد گرفتنِ مداوم است؛
مسیری که فقط به کلاس درس، جزوهها و کتابهای دانشگاهی محدود نمیشود.
با همین نگاه Medicalead شکل گرفته؛
تا جایی باشد برای یاد گرفتن، بهروز ماندن و به اشتراک گذاشتن محتوایی که در مسیر حرفهای پزشکی واقعاً به کار میآید.
🥇در این کانال، به مرور با محتواهایی مثل اینها همراه خواهیم بود:
🩺آموزشها و نکات کاربردی بالینی
🎓…
Showing the 11 most recent of 11 posts we hold for @medica_lead. 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 — 330,963 of 1,548,671entries 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.
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 14 August 2026 — this
entry's latest reading, not the date you are reading this.
“Medicalead | مدیکالید” (@medica_lead), 209 subscribers as measured 14 August 2026. Telegram Register, tgregister.com/channel/medica_lead.
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.