Health & wellness — a classification, not a measurement. An on-box language model (Qwen3.6-35B-A3B-UD-Q6_K_XL, prompt version 1) read this channel’s own recent posts on 20 August 2026 and assigned it the closest of 31 fixed categories, at 98% 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 the other topics.
Observations
These are measurements, not verdicts. Each one below states something we counted, alongside the evidence it was counted from, so you can check it rather than take it. None of them is graded: every observation this register holds is recorded at severity 0, because the precision of the detectors behind them has not been measured yet, and a rating we cannot support is worse than none. Read each as a fact about the data, not as a judgement about the channel. How we measure.
Content that also appears on other registered channels
Posts published here appear in near-verbatim form on 1 other registered channel. This entry also forms a group of 2 channels linked by matching posts. The matching is on the text itself, not on Telegram’s forward marker, so it finds a copy whether or not it was labelled as one.
Matching posts — open both and compare (5 of the pairs behind the counts below)
Channels this entry shares post bodies with, where at least one matching post pair has no forward credit between the two channels, or to a common source, recorded in our data
Text overlap is the Jaccard coefficient over the set of distinct three-word phrases in the two bodies: 1.00 is identical wording, and the threshold for counting a pair at all is 0.70. Candidates are generated by simhash LSH (4 x 16-bit bands, exact Hamming <= 3) verified against the bodies with Jaccard over the SET of distinct 3-word shingles. Published first counts which side of each matching pair carries the earlier timestamp — in this corpus, which is the limitation directly below.
What this cannot establish
MEASURED, DOMINANT ERROR SOURCE: a post ingested before 2026-08-06 may have carried a forward header that was not recorded. A 45-pair hand-check against live t.me pages found 14 (31%) where the live page shows a forward header naming the other channel and the database has none, plus 4 more (9%) naming a third party. The text match itself was wrong 0 times out of 45. Read attribution_capture.items_in_trusted_window before treating the unattributed count as a claim.
Telegram lets a channel forward a post with a header naming the source, and we only began reliably recording that header on 2026-08-06. 3 of the 3 matches recorded here fall after that date and carried no header when we read them. The rest predate reliable capture and are not evidence either way.
“Published first” means first in this corpus. We hold 77 comparable posts for this entry, running 16 July 2026 to 10 November 2026. A channel we have read one page deep will look younger than a neighbour we have read in full, and the order would flip with no change in the underlying facts.
The detector’s own notes on this observation, as it recorded them. Names in this_style are fields of the underlying evidence record, which the plain-English paragraphs above read out for this entry.
Verbatim republication has three causes and the text separates only two: a clone/mirror, unattributed copy-paste, or BOTH channels copying a common third source that neither attributes. The spread filter (content held by at most 8 channels) reduces the third and does not remove it.
'Earliest' means earliest IN THIS CORPUS. A channel ingested one page deep will look younger than a neighbour ingested in full; corpus_coverage above is there to be checked before the direction is believed.
shared_verified_est extrapolates the sampled pass rate over the full narrow match count; sampled/passed are the numbers actually measured.
Absence of a forward header is not proof of intent: Telegram lets a channel disable forward attribution, and a credit written in the body is not parsed as attribution here (mention_edge_either_way above is the closest available signal).
Of the group of 2 channels, the one whose matching posts we hold earliest is @hakim2398 — which is this entry. That is a statement about our reading window, not a claim of authorship.
Recorded under the key clone_source, last confirmed 11 November 2026. An observation that a later pass no longer finds is cleared, and a cleared observation is removed from this page rather than being shown struck through — we do not keep publishing a claim we have withdrawn. Dispute an observation.
Channels linked by matching posts
This channel is in a group of 2 registered channels linked by matching posts. Links are found by comparing text fingerprints across every channel on the register.
Which channel, if either, published first is deliberately not shown in this list. “First” could only mean first in our own crawl, which depends on how deep we happened to reach into each channel’s history, not on when the content was actually first posted. Our one hand-check read 45 of the highest-confidence flagged pairs against the live Telegram pages. In 18 of them the live page showed a “Forwarded from” credit that our database had no record of, so reading that pair as an unattributed copy was wrong; the check did not measure who published first. This list is ordered by subscriber count, the same as every other listing on this site, never by which channel we think came first. Near-verbatim matching has several ordinary explanations besides copying — a channel mirroring itself, an unattributed repost, or two channels independently repeating the same wire story — and this measurement cannot tell those apart. How this is measured.
61 measurements spanning 97 days, net +415. 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 49,361–49,952 and does not start at zero.
Measurement log — every subscribers count we have recorded, most recent 20 of 61
Measured (UTC)
Subscribers
Change
11 Nov 2026, 09:38
49,846
+42
9 Nov 2026, 13:07
49,804
+4
8 Nov 2026, 03:07
49,800
+1
6 Nov 2026, 22:40
49,799
-4
5 Nov 2026, 21:04
49,803
-9
4 Nov 2026, 22:51
49,812
-11
4 Nov 2026, 00:56
49,823
+3
2 Nov 2026, 23:56
49,820
-7
1 Nov 2026, 20:27
49,827
+1
31 Oct 2026, 19:56
49,826
-13
30 Oct 2026, 17:16
49,839
-17
29 Oct 2026, 14:06
49,856
-14
28 Oct 2026, 11:55
49,870
-5
27 Oct 2026, 08:27
49,875
-5
26 Oct 2026, 09:06
49,880
+11
25 Oct 2026, 09:08
49,869
+34
24 Oct 2026, 07:20
49,835
+34
22 Oct 2026, 08:01
49,801
-13
21 Oct 2026, 00:38
49,814
-27
19 Oct 2026, 22:15
49,841
first reading
Engagement
83 posts held, back to 16 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 196 pages of Telegram’s post history, 20 posts per page.
ERR · 30 days
9.65%
avg views ÷ 49,846 subscribers
Avg views / post
4,810
33 posts measured
Reaction rate
0.925%
reactions ÷ views · ER floor
Posts in window
34
of 83 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 November 2026
Posts held
83 (16 July 2026 – 10 November 2026)
Views total
158,760
Reactions total
1,468
Forwards / comments
not exposed by the public surface — not measured, not estimated
Readings taken
11 Nov 2026, 02:58 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
12m 34s
Average length
2m 06s
Measured directly from 6 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
5,365 reactions across 82 posts, in 25 distinct kinds. The most used accounts for 82.6% of them.
Every reaction kind recorded on the sample, most used first
Reaction
Count
Share
Share, drawn
❤
4,433
82.6%
👍
165
3.08%
❤🔥
162
3.02%
💊
144
2.68%
👏
126
2.35%
💯
86
1.60%
👌
36
0.671%
🔥
28
0.522%
🎉
19
0.354%
💘
19
0.354%
✍
18
0.336%
🍓
15
0.28%
⚡
14
0.261%
🙏
14
0.261%
🤷
13
0.242%
🏆
12
0.224%
💔
12
0.224%
🕊
11
0.205%
😢
10
0.186%
🤝
9
0.168%
5 further kinds
19
0.354%
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 82 of the 83 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 5,365 reactions in total: the kind of figure the paragraph above means by “a reaction total printed elsewhere on the page”.
Measured over the 83 most recent posts we hold, published 16 July 2026 to 10 November 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.
Telegram Stars
Stars received
8
across the posts below
Posts paid on
5
of 82 we hold a reading for · 6%
Most on one post
2
single highest reading
A paid reaction is a reader spending Telegram Stars — bought with money — on a post by @hakim2398. Telegram publishes the count on the public post preview alongside ordinary reactions, and this register reads it there. It is the only figure on this site that measures money moving rather than attention.
Stars are not reactions, and the two are never added. They are rendered in the same strip on Telegram and counted in the same shape, but one is a tap and the other is a purchase. The reaction totals and the engagement rate elsewhere on this page exclude every figure in this section, and no rate here is computed against a reaction count.
This is not revenue, and we publish no currency figure. What a Star costs a reader and what it pays a channel are different numbers, Telegram takes a share we cannot observe, and the terms have changed. Converting a Star count into money would be an estimate dressed as a measurement, so the count is where we stop.
Counted over the 83 most recent posts we hold for this entry, published 16 July 2026 to 10 November 2026. Star counts above 1,000 reach us in Telegram’s short form and carry the same three-significant-figure rounding as everything else on this page.
Recent posts
Telegram’s own ‘edited’ marker: 25 of 34 posts held from the last 30 days (73.5%) carried it when this register last read them. The marker says a post was changed after publishing, not what it said before — this register holds the earlier wording only where an edit fell between two of its own reads (see the edit ledger and how it is measured).
رسالة بسيطة بكلمات طيبة وصادقة تكفي عن الف رسالة
والله ممحتاج احد يشكرني على الي نقدمه وهو في سبيل الله ومن فضل الله ابدا ممتكلفين بالي نقدمة لخدمة الجميع بس هاي الكلمات الطيبة والصادقة هي وحدها تخليني استمر بتقديم الافضل وان شاء الله مستمرين وياكم بكل خير واحسان من فضل الله واليكم والحمدالله ونتمنى ماقصرنه ويه الجميع واعذرونه اذا قصرنه ❤️👏
حكيم hakim 💊
شنو الادوية الوريدية الي نجنب اعطائهم بشكل سريع ومباشر بدون تخفيف ضروري تخلوهم بالكم دائما 🧠
الموضوع سهل ومبسط المجموعة الاولى راح نختصرها بالحروف
A B C D
A➡️Aminophylin
B➡️Beta agonist like Dobutamin
C➡️Calcium
D➡️Digoxin
⚪️هذني الادوية الي بهاي المحموعة اعطائهم بشكل سريع ممكن يسبب خفقان واعطاء الكالسيوم بشكل مباشر ممكن يسبب توقف القلب الله يكفيكم الشر
المجموعة الثانية
PCI-L
P➡️Potassium iv
C➡️Calcium iv
I➡️Iron
…
شغلتين مهمة اذكرها ويه البلاسيل امبول او
▫️Metoclopramide ampoule
1️⃣الاولى انو الجرعة بالاطفال والاشخاص الي عمرهم اقل من 20 سنة تنحسب على اساس الوزن
0.1 mg/kg
حتة نقلل من تاثيرها على الاعصاب ومشاكل dystonia…
2️⃣الثانية والاهم من تنطي بطريقة iv يفضل اعصاءها slow iv injection او الافضل iv infusion ممكن نخففها ويه normal saline وبسهولة لان اذا نطيتها direct and rapid iv injection ممكن تسبب بحصول
🔸Restlessness هستري…
شراب زيكوف يحتوي على مستخلص عرق السوس
💊Licorice (Glycyrrhiza glabra)
1️⃣ممنوع ❌ لمرضى ضغط الدم الغير مسيطر عايع ومرضى القلب 🫀لان يرفع ضغط الدم بثلاث اليات مختلفة
2️⃣ممنوع للمرضى او يستخدم بحذر للمرضى الي ياخذون علاجات مناعية او ادوية عصبية وادوية كيميائية مثل
💊MTX
💊Prednisolone &medrol
💊Tegretol
💊Digoxin
💊CNS medicine
💊Tacrolimus
💊Contraceptive
3️⃣اخر شي هو ممنوع للحامل 💊 لان يسبب مشاكل تتعلق بارتفاع ضغط الدم خلال …
جزء من ارائكم الحلوة الخاصة باستخدام الموقع مالتنه الجديد الحمدالله وعلى الرغم بعدنه مموضحين الادوات بس لبساطتها الشديدة بسهولة تكدرون تستخدموها 💊💊
🪧Lexiclone
هنا الدكتورة مستخدمة الاداة الخاصة بحل وتوافق واستقرار الادوية الوريدية متاكدة من استقرار العلاج بعد الحل بكل سهولة وثقة الاداة بيها اكثر من مليون دراسة موثوقة لكل الادوية الوريدية بالعالم 💊 وعلى اهم المصادر معتمدين بيها موفقين يارب ويفرحنه كلامكم عن الموقع …
هل شراب زيكوف او مستخلص عرق سوس (Glycyrrhiza glabra) 🪵 يؤثر على ضغط الدم❔
✔️Zecuf syrup
نعم شراب زيكوف غير امن لمرضى ضغط الدم وخصوصا المرضى الي عدهم مشاكل قلبية او خفقان وضغط الدم غير مستقر او غير مسيطر عليه ولثلاث اسباب اساسية
1️⃣اولا مستخلص عرق سوس اله تاثير على منع تنشيط الكورتيزول وهالشي بحد ذاته اله تاثير على احتباس الاملاح والماء داخل الجسم
2️⃣ثانيا زيادة حجم الدم بسبب تاثيره على ايض cortisol وتاثيرة على flu…
بصراحة موضوع جدا مهم موضوع التخفيف وحل الادوية الوريدية بالمستشفيات والمراكز لازم يكون الصيدلاني ملم جدا بمحاليل الحل والتخفيف والاستقرارية بعد الحل والتوافق الوريدي
▫️iv compatibility stability after reconstitution and dilution
اوضحها الكم اكثر يعني اني هذا العلاج لازم اعرف بيمن احله اذا كان powder واذا حليته ويامن اخففه ويه NS او GW 5% او RL وغيرها واذا حليته وخففته شكد يبقى مستقر بعد حله واقصى فترة يبقى بيها مست…
Showing the 12 most recent of 83 posts we hold for @hakim2398. 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.
Stars beside a post are paid reactions — Telegram Stars, bought with money and spent on that post. They are a different unit from reactions and are never added to them, here or anywhere else on this page.
Posts edited after publishing
@hakim2398 edited 3 posts after it first published — the same permalink now carries different wording than the one this register originally read, caught because our own crawl held a copy of the earlier text.
An edit is not deception. Typo fixes, price updates and corrections look exactly like this too — this register can tell you the wording changed and when, not why. How this is measured.
First edit seen
14 August 2026
Most recent edit
30 October 2026
Posts recorded as deleted after publishing
We recorded 3 posts on @hakim2398 as deleted — posts this register held that were missing from the channel’s public page on two separate reads, taken from different network addresses at least an hour apart.
A deletion is not wrongdoing. This register can see that a post it held is no longer on the channel’s public page, and when — not why. Expired ad placements, reposts, rotating links and corrections all look the same. This is a count of recorded detections, not an exact total: it misses deletions we could not see, because only a post we held and later re-read inside the page can be seen to go, and it may include a small number of wrong records. How this is measured.
First seen missing
13 August 2026
Most recent seen missing
22 September 2026
Median time before seen missing
21 hours
Seen missing in the last 30 days
0
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 9 registered channels — 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.
Channels Telegram recommends alongside this one
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 25 August 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.
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.
Pharmacion 💊 @pharmaceion · 29,218 Telegram ranks this channel #4 of 84 here — alongside 83 others — read 8 September 2026
The Injectable Drug @Drug_injectable · 22,203 Telegram ranks this channel #7 of 88 here — alongside 87 others — read 21 September 2026
panadol_Xtra 💊 @panadol_extra1 · 19,526 Telegram ranks this channel #11 of 81 here — alongside 80 others — read 1 October 2026
Future pharmacists @pharmacy_2021_3 · 19,389 Telegram ranks this channel #11 of 85 here — alongside 84 others — read 1 October 2026
𝐂𝐎𝐒𝐌𝐄𝐓𝐈𝐂𝐒 @phfatima_5 · 34,152 Telegram ranks this channel #13 of 88 here — alongside 87 others — read 3 September 2026
محمود ميعاري @MahmoudMiariRT · 21,687 Telegram ranks this channel #16 of 62 here — alongside 61 others — read 21 September 2026
حسين سريرية || Hussein Clinical @clinicalhussein · 26,892 Telegram ranks this channel #16 of 86 here — alongside 85 others — read 11 September 2026
وصــــــRXــــفات @wasffati99 · 31,830 Telegram ranks this channel #17 of 84 here — alongside 83 others — read 6 September 2026
Vitamin's @Vit3mins · 21,275 Telegram ranks this channel #21 of 84 here — alongside 83 others — read 23 September 2026
كيسات @Caseblu · 23,615 Telegram ranks this channel #21 of 87 here — alongside 86 others — read 19 September 2026
Farmakon @Farma1kon · 42,930 Telegram ranks this channel #21 of 90 here — alongside 89 others — read 29 August 2026
Pharmacy 87 💊 @pharmacy87 · 73,012 Telegram ranks this channel #21 of 88 here — alongside 87 others — read 19 August 2026
PharmacyDrug @pharmacy_drug2 · 61,725 Telegram ranks this channel #22 of 85 here — alongside 84 others — read 22 August 2026
يوميات صيدلاني💊💉 @Waelology2025 · 77,928 Telegram ranks this channel #22 of 87 here — alongside 86 others — read 21 August 2026
Scientific pharmacists @Scientificpharmacists · 24,985 Telegram ranks this channel #24 of 88 here — alongside 87 others — read 14 September 2026
اعلانات للتواجد للصيادلة حصرا في بغداد @worktopharmacists · 30,402 Telegram ranks this channel #25 of 78 here — alongside 77 others — read 8 September 2026
Pharmacy World @pharmacy_world · 95,195 Telegram ranks this channel #27 of 88 here — alongside 87 others — read 16 August 2026
اعلانات تواجد صيادلة @MC_Pharmacist · 24,323 Telegram ranks this channel #31 of 81 here — alongside 80 others — read 18 September 2026
Dermatology in Iraq @saadm1999 · 26,130 Telegram ranks this channel #32 of 88 here — alongside 87 others — read 13 September 2026
مهند فارما 💊💉 @muhanad_pharma · 63,062 Telegram ranks this channel #32 of 91 here — alongside 90 others — read 21 August 2026
health professions🧠 @helath · 42,322 Telegram ranks this channel #44 of 90 here — alongside 89 others — read 31 August 2026
Medical Field @Medical_Field · 111,968 Telegram ranks this channel #49 of 82 here — alongside 81 others — read 14 August 2026
𝐄𝐗𝐂𝐄𝐋𝐋𝐄𝐍𝐂𝐄 𝐈𝐍 𝐏𝐇𝐀𝐑𝐌𝐀𝐂𝐘 @physsiccaallpharmaccyy · 18,589 Telegram ranks this channel #54 of 90 here — alongside 89 others — read 5 October 2026
Doctors & pharmacists @Doctors_pharm_Med · 40 Telegram ranks this channel #59 of 83 here — alongside 82 others — read 5 September 2026
This channel appears in 27 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.
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 11 November 2026 — this
entry's latest reading, not the date you are reading this.
“حكيم hakim 💊” (@hakim2398), 49,846 subscribers as measured 11 November 2026. Telegram Register, tgregister.com/channel/hakim2398.
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.