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 12 September 2026 and assigned it the closest of 31 fixed categories, at 86% 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.
Growth
13 measurements spanning 39 days, net +197. 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 6,933–7,190 and does not start at zero.
Measurement log — every subscribers count we have recorded
Measured (UTC)
Subscribers
Change
16 Sept 2026, 02:57
7,160
+7
12 Sept 2026, 12:56
7,153
+5
8 Sept 2026, 04:41
7,148
+7
2 Sept 2026, 23:45
7,141
+6
30 Aug 2026, 15:43
7,135
+10
27 Aug 2026, 09:18
7,125
+10
24 Aug 2026, 11:54
7,115
+32
20 Aug 2026, 14:53
7,083
+60
17 Aug 2026, 16:54
7,023
-3
14 Aug 2026, 13:39
7,026
+48
11 Aug 2026, 07:32
6,978
+10
8 Aug 2026, 06:38
6,968
+5
7 Aug 2026, 22:45
6,963
first reading
Engagement
42 posts held, back to 28 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 12 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 42 posts for this entry, the most recent from 18 August 2026. An engagement rate over an empty window would be a number about nothing.
What this channel posts
Video runtime
8s
Average length
8s
Measured directly from 1 video 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
203 reactions across 32 posts, in 5 distinct kinds. The most used accounts for 83.7% of them.
Every reaction kind recorded on the sample, most used first
Reaction
Count
Share
Share, drawn
❤
170
83.7%
👍
19
9.36%
😢
7
3.45%
🔥
6
2.96%
💔
1
0.493%
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 34 of the 42 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 203 reactions in total: the kind of figure the paragraph above means by “a reaction total printed elsewhere on the page”.
Measured over the 42 most recent posts we hold, published 28 July 2026 to 18 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.
لماذا يتوقف قلب مريض الفشل الكلوي (End-Stage Renal Disease) فجأة بعد تناول موزة أو عصير برتقال؟
مريض معروف بـ Chronic Kidney Disease (CKD) و ESRD، يلتزم بجلسات الغسيل الكلوي بانتظام. حالته مستقرة نسبياً.
في يوم ما، وبسبب شعوره بالجوع، يتناول 🍌 موزة أو برتقالة، أو ربما استخدم 🧂 بديل ملح (Salt Substitute) غني بالبوتاسيوم في طعامه.
بعد ساعة أو ساعتين، يبدأ فجأة في الشعور بـ:
🔴 Muscle Weakness
(ضعف عضلي عام)
🔴 Palpit…
إعلان مهم
تعلن كلية التمريض – جامعة المستقبل عن فتح باب التسجيل للراغبين بالتقديم إلى برنامج الماجستير في تخصص علوم في التمريض الباطني والجراحي، بالتعاون والشراكة الأكاديمية مع جامعة المنصورة – جمهورية مصر العربية.
🔹أولاً: الجامعة والاعتراف الأكاديمي
* جامعة المنصورة – جمهورية مصر العربية من الجامعات المعترف بها لدى وزارة التعليم العالي والبحث العلمي العراقية.
* حاصلة على تصنيف شنغهاي للجامعات، بما يعكس مكانتها الأ…
النائب حيدر المطيري ( اشراقة كانون ) :
على كيفك على كيفك هذا إلي أضربه ما سرق ولا أخذ حق غيره
طالع يتظاهر يطالب بحقه وفقاً للدستور.....
نساند و بقوة مطالب ذوي المهن الطبية والصحية وفقاً للقانون و لقد قدمت لجنة الأمر النيابي رقم 18 عدة حلول ناجعة لأحتوائهم وتعيينهم دون أن نكلف الموازنة أي تكاليف إضافية، لكن الحكومة لم تستجيب.
لماذا قد يدخل مريض Liver Cirrhosis في غيبوبة كبدية بعد وجبة عشاء غنية بالبروتين؟
مريض معروف بـ End-Stage Liver Disease، حالته مستقرة نسبياً.
بعد ساعات من تناول 🍖 High-Protein Meal، أو في حال حدوث 🩸 Gastrointestinal Bleeding...
فجأة، نلاحظ:
🔴 Confusion & Drowsiness
(تشوش ذهني ونعاس)
🔴 Personality Changes
(تغير حاد في المزاج)
🔴 Slurred Speech (ثقل في النطق)
🔴 Asterixis (Flapping Tremor)
(رفرفة اليدين)
السؤال المحوري…
Clindamycin:
Class: antibiotic.
Administration:
- متوفر على شكل vial بجرع 300mg و 600mg
- يعطى عضلياً كحد اقصى 600mg
- او تقطير وريدي حيث يضاف الى 100ml من محلول ملائم و غالباً (%0.9 N/S) و تعطى حسب الأتي:
1. 300mg خلال 15 دقيقة كحد ادنى.
2. 600mg خلال 30 دقيقة كحد ادنى.
3. 900mg و أكثر خلال 45 دقيقة.
الأمر الجامعي لجامعة بغداد كلية التمريض
@Nursesmed
❤1
Showing the 12 most recent of 42 posts we hold for @Nursesmed. 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.
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 16 September 2026 — this
entry's latest reading, not the date you are reading this.
“دليل الممرضين الناجح” (@Nursesmed), 7,160 subscribers as measured 16 September 2026. Telegram Register, tgregister.com/channel/Nursesmed.
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.