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Telegram profile photo for Amoon Clinical Pharmacist

Channel

Amoon Clinical Pharmacist

@Amoon1299

On this record: Topic · Growth · Engagement · Reactions · Posts · Telegram's recommendations · Cite this entry

2,366subscribers

-5 since we began measuring on 25 August 2026

Risers and fallers across the register · movement among entries of 1,000–3,162.

Register entry

Telegram ID-1002047422985
TypeChannel
Username@Amoon1299
CreatedBetween 1 November 2023 and 31 May 2024 — estimated from Telegram’s id allocation, not measured. How this range is calculated.
First recorded25 August 2026
Last confirmed live18 September 2026
Measurements held7
Confirmed unchanged1 time, most recently 18 September 2026
On Telegramt.me/Amoon1299

Topic

Education — 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 15 September 2026 and assigned it the closest of 31 fixed categories, at 99% 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

2,3662,3722,36925 August 2026 — 2,371 subscribers25 August 2026 — 2,371 subscribers30 August 2026 — 2,370 subscribers5 September 2026 — 2,372 subscribers10 September 2026 — 2,369 subscribers14 September 2026 — 2,367 subscribers18 September 2026 — 2,366 subscribers25 August 202618 September 2026
7 measurements spanning 24 days, net -5. 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 2,365–2,373 and does not start at zero.
Measurement log — every subscribers count we have recorded
Measured (UTC)SubscribersChange
18 Sept 2026, 17:592,366-1
14 Sept 2026, 16:002,367-2
10 Sept 2026, 16:402,369-3
5 Sept 2026, 19:362,372+2
30 Aug 2026, 00:332,370-1
25 Aug 2026, 20:002,371no change
25 Aug 2026, 19:452,371first reading

Engagement

19 posts held, back to 22 June 2026the reader has not yet reached the start of this channel’s public history, so older posts may sit further back, unread. Read across 1 page of Telegram’s post history, 20 posts per page.

ERR · 30 days
11.6%
avg views ÷ 2,366 subscribers
Avg views / post
274
1 post measured
Reaction rate
1.09%
reactions ÷ views · ER floor
Posts in window
1
of 19 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
WindowRolling 30 days · latest post in window 21 August 2026
Posts held19 (22 June 202621 August 2026)
Views total274
Reactions total3
Forwards / commentsnot exposed by the public surface — not measured, not estimated
Readings taken25 Aug 2026, 20:00 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

35 reactions across 15 posts, in 5 distinct kinds. The most used accounts for 60.0% of them.

Every reaction kind recorded on the sample, most used first
ReactionCountShareShare, drawn
2160.0%
👏514.3%
🥰411.4%
👍38.57%
🔥25.71%

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 15 of the 19 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 35 reactions in total: the kind of figure the paragraph above means by “a reaction total printed elsewhere on the page”.

Measured over the 19 most recent posts we hold, published 22 June 2026 to 21 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.

Recent posts

7 Aug 2026, 19:22 UTC337 views4 reactionsread 25 August 2026
Photo

🧠 Meningitis Chemoprophylaxis – High Yield ✅ Neisseria meningitidis - Rifampin - Ciprofloxacin - Ceftriaxone (Preferred in pregnancy) ✅ Haemophilus influenzae type b (Hib) - Rifampin only ❌ Streptococcus pneumoniae - No chemoprophylaxis for close contacts 📌 Remember: Neisseria → 3 drugs Hib → Rifampin Pneumococcus → No prophylaxis

4

Signed آمنة

30 Jun 2026, 07:17 UTC488 views3 reactionsread 25 August 2026
Photo

Thiazide diuretics increase calcium reabsorption in the Distal Convoluted Tubule (DCT), resulting in decreased urinary calcium excretion. • Loop diuretics (e.g., Furosemide) decrease calcium reabsorption in the Thick Ascending Limb (TAL), resulting in increased urinary calcium excretion.

2👍1

Signed آمنة

30 Jun 2026, 07:14 UTC334 views1 reactionsread 25 August 2026
Photo

إعادة امتصاص الكالسيوم (Calcium reabsorption) في الكلية تتم في عدة أجزاء من النيفرون: Proximal Convoluted Tubule (PCT) 🟢 يُعاد امتصاص 65% من الكالسيوم. يكون الامتصاص سلبيًا (Passive) مع الماء والصوديوم (Paracellular). Thick Ascending Limb of Loop of Henle (TAL) 🟡 يُعاد امتصاص حوالي 20–25%. أيضًا يكون أغلبه Paracellular، ويعتمد على الجهد الكهربائي الموجب في اللمعة. Distal Convoluted Tubule (DCT) 🔵 يُعاد امتصاص 8–10%.

🔥1

Signed آمنة

29 Jun 2026, 18:22 UTC258 views5 reactionsread 25 August 2026
Photo

📚 راح أبدأ سلسلة جديدة عن Clinical Pharmacy & NICU. كل فترة راح أنزل بوستات تعليمية مختصرة وسهلة، مثل: 🩺 GIR 💉 Glucose Concentration 💊 Insulin 🧪 TPN 👶 NICU Pearls وغيرها من المواضيع العملية. 📍تابعوني على الإنستغرام حتى توصلكم السلسلة كاملة أولًا Instagram: @a_m.o.on https://www.instagram.com/a_m.o.on?igsh=aWVhNzFubzQ3eXRx

4👏1

Signed آمنة

29 Jun 2026, 07:21 UTC311 viewsread 25 August 2026

🩺 مثال على حساب جرعة الـ Pre-meal Insulin لنفترض أن لدينا مريضة مصابة بـ Type 1 Diabetes، وكانت المعلومات كالآتي: - TDD = 24 units/day - تستخدم Insulin Aspart قبل الوجبات. - Blood glucose = 260 mg/dL - Target glucose = 120 mg/dL - ستتناول 45 g carbohydrate - ICR = 1:15 1️⃣ حساب جرعة تغطية الكارب (Carbohydrate Coverage) بما أن كل 1 وحدة تغطي 15 g كارب: 45 ÷ 15 = 3 units ✅ إذن جرعة تغطية الكارب = 3 Units --- 2️

Signed آمنة

27 Jun 2026, 14:35 UTC253 views3 reactionsread 25 August 2026

🌸 HbA1c → Estimated Average Glucose (eAG) قد تتساءل: ليش نحول HbA1c إلى eAG؟ 🤔 لأن HbA1c يُعطى كنسبة مئوية (%)، بينما المريض والطبيب يتعاملان يوميًا مع قراءات السكر بوحدة mg/dL. لذلك نحول الـ HbA1c إلى Estimated Average Glucose (eAG) حتى نعرف شنو كان متوسط سكر الدم خلال آخر 2–3 أشهر بلغة أسهل للفهم. ━━━━━━━━━━━━━━ 🤍 ✨ Quick Rule (Exam Rule) eAG (mg/dL) ≈ (HbA1c − 2) × 30 هذه معادلة تقريبية وسريعة، تُستخدم كثيرً

3

Signed آمنة

26 Jun 2026, 14:50 UTC236 views2 reactionsread 25 August 2026
Photo

🌸 معلومة سريعة ممكن تلاحظون بعض المراجع تستخدم 1700 Rule، وأخرى تستخدم 1800 Rule لحساب Correction Factor مع Rapid-Acting Insulin. ✅ القاعدتان صحيحتان، والفرق بينهما بسيط جدًا، لأن 1800 Rule تعطي قيمة أعلى قليلًا، وبالتالي تكون جرعة الـ correction أقل بشكل طفيف مقارنةً بـ 1700 Rule.

👏2

Signed آمنة

Showing the 12 most recent of 19 posts we hold for @Amoon1299. 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.

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.

حكيم hakim 💊
@hakim2398 · 49,884
Telegram ranks this channel #41 of 85 here — alongside 84 others — read 25 August 2026
Scientific pharmacists
@Scientificpharmacists · 25,167
Telegram ranks this channel #57 of 88 here — alongside 87 others — read 14 September 2026
Pharmacion 💊
@pharmaceion · 29,282
Telegram ranks this channel #61 of 84 here — alongside 83 others — read 8 September 2026
𝐂𝐎𝐒𝐌𝐄𝐓𝐈𝐂𝐒
@phfatima_5 · 34,107
Telegram ranks this channel #63 of 88 here — alongside 87 others — read 3 September 2026

This channel appears in 4 seed channels' Telegram-generated recommendation lists 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 18 September 2026 — this entry's latest reading, not the date you are reading this.

“Amoon Clinical Pharmacist” (@Amoon1299), 2,366 subscribers as measured 18 September 2026. Telegram Register, tgregister.com/channel/Amoon1299.

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.