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 9 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 the other topics.
Growth
60 measurements spanning 93 days, net +420. 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 33,576–34,293 and does not start at zero.
Measurement log — every subscribers count we have recorded, most recent 20 of 60
Measured (UTC)
Subscribers
Change
7 Nov 2026, 13:17
34,083
+5
6 Nov 2026, 10:06
34,078
-12
5 Nov 2026, 07:08
34,090
-1
4 Nov 2026, 07:59
34,091
-20
3 Nov 2026, 09:41
34,111
-1
2 Nov 2026, 06:56
34,112
-2
1 Nov 2026, 09:54
34,114
+17
30 Oct 2026, 11:00
34,097
-1
29 Oct 2026, 08:07
34,098
+7
28 Oct 2026, 07:19
34,091
+2
27 Oct 2026, 06:20
34,089
+1
26 Oct 2026, 03:57
34,088
-6
25 Oct 2026, 04:27
34,094
+47
24 Oct 2026, 03:46
34,047
-4
22 Oct 2026, 06:31
34,051
+2
20 Oct 2026, 21:06
34,049
+1
19 Oct 2026, 21:20
34,048
-5
18 Oct 2026, 19:37
34,053
-4
17 Oct 2026, 17:10
34,057
-5
16 Oct 2026, 18:21
34,062
first reading
Engagement
51 posts held, back to 18 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 173 pages of Telegram’s post history, 20 posts per page.
ERR · 30 days
12.5%
avg views ÷ 34,083 subscribers
Avg views / post
4,250
8 posts measured
Reaction rate
0.233%
reactions ÷ views · ER floor
Posts in window
8
of 51 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 3 November 2026
Posts held
51 (18 June 2026 – 3 November 2026)
Views total
33,960
Reactions total
79
Forwards / comments
not exposed by the public surface — not measured, not estimated
Readings taken
7 Nov 2026, 06:11 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
946 reactions across 49 posts, in 25 distinct kinds. The most used accounts for 55.6% of them.
Every reaction kind recorded on the sample, most used first
Reaction
Count
Share
Share, drawn
❤
526
55.6%
👍
72
7.61%
👏
56
5.92%
💘
52
5.50%
❤🔥
36
3.81%
🔥
36
3.81%
💯
27
2.85%
🏆
24
2.54%
😍
24
2.54%
🆒
17
1.80%
💋
13
1.37%
✍
12
1.27%
😁
10
1.06%
🤩
8
0.846%
😘
7
0.74%
⚡
6
0.634%
🥰
5
0.529%
💊
4
0.423%
💅
3
0.317%
🙈
3
0.317%
5 further kinds
5
0.529%
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 51 of the 51 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 989 reactions in total: the kind of figure the paragraph above means by “a reaction total printed elsewhere on the page”.
Measured over the 51 most recent posts we hold, published 18 June 2026 to 3 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.
Recent posts
Telegram’s own ‘edited’ marker: 0 of 8 posts held from the last 30 days (0%) 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).
68-year-old man presents with chest pain, ECG showed ST elevation in leads II, III and aVF, BP: 85/60 mmHg and his lungs are clear, what is the most appropriate next step?
IV Furosemide5%
IV normal saline bolus59%
IV Nitroglycerin28%
IV beta blocker8%
Shares as published. No per-option vote count is published by Telegram, so none is shown.
53-year-old man with CKD presents with muscle weakness, ECG shows tall peaked T waves, serum potassium: 6.8 mmol/L, what is the most appropriate initial management?
IV calcium gluconate88%
IV insulin with glucose9%
Oral sodium bicarbonate2%
Nebulized Salbutamol2%
Shares as published, totalling 101%. No per-option vote count is published by Telegram, so none is shown.
Patient admitted 5 days ago with NSTEMI, received unfractionated Heparin, labs upon admission were normal but today platelet: 65 with normal coagulation profile, most likely cause of thrombocytopenia?
Immune thrombocytopenia2%
Heparin induced thrombocytopenia90%
Thrombotic thrombocytopenic purpura4%
Disseminated intravascular coagulopathy4%
Shares as published. No per-option vote count is published by Telegram, so none is shown.
43-year-old-woman has fever, night sweats and unintentional weight loss, has bilateral cervical lymph nodes and splenomegaly, most appropriate next step in management?
FNA of the lymph node36%
Excisional biopsy of the lymph node50%
Bone marrow biopsy12%
Splenectomy2%
Shares as published. No per-option vote count is published by Telegram, so none is shown.
60-year-old man with advanced bronchogenic carcinoma presents with malignant right pleural effusion, he undergoes several therapeutic pleural taps, next best option in management?
Diuretics18%
Ultrafiltration8%
Chemical pleurodesis65%
Low salt human albumin9%
Shares as published. No per-option vote count is published by Telegram, so none is shown.
66-year-old man presents with SOB, he smokes 20 cigarettes/day but is otherwise well, spirometry shows a restrictive pattern, what is the most likely diagnosis?
Pulmonary fibrosis66%
Bronchiectasis27%
Heart failure3%
Asthma4%
Shares as published. No per-option vote count is published by Telegram, so none is shown.
45-year-old man presents with sudden onset of unilateral facial weakness 1 hour ago, which of the following is most likely to shorten his symptoms duration?
Anti-viral therapy8%
Thrombolytic therapy33%
Corticosteroid therapy52%
Hyperbaric oxygen therapy8%
Shares as published, totalling 101%. No per-option vote count is published by Telegram, so none is shown.
38-year-old woman with pleurisy requires a thoracentesis, the needle should be placed on the midaxillary line of the affected side, which rib level should the needle penetrate through?
At the 4th10%
At the 5th33%
Between the 6th and 7th28%
Between the 8th and 10th29%
Shares as published. No per-option vote count is published by Telegram, so none is shown.
22-year-old man whose asthma is uncontrolled on beta agonist therapy is commenced on a steroid inhaler, which of the following is the most likely adverse effect?
Dysphonia49%
Dental abscess26%
Peptic ulceration14%
Thrombocytopenia10%
Shares as published, totalling 99%. No per-option vote count is published by Telegram, so none is shown.
للي حابين يراجعوا كيفية التعامل مع الحالات الشائعة اللي حتنشاف طول سنين البورد وللي حابب يسوي استعادة للمعلومات قبل مايبدأ
للسنة الثانية على التوالي راح اقدم جزء الباطنة العامة في برنامج التحضير للإقامة للأطباء المقيمين والمُنظم من قبل CH Academy
فكرة البرنامج هي رفع لجودة التدريب بالتهيئة المسبقة وشرح تفاصيل كل بورد وكيف نفكر في الحالات اللي تتواجه فيه من مرحلة توقع التشخيص إلى مرحلة العلاج
للتسجيل:-
https://chac…
❤17👏4👍3💘1🥰1😍1
Signed Elaf Faisal
Showing the 12 most recent of 51 posts we hold for @Elaf_Faisal. 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.
Posts recorded as deleted after publishing
We recorded 9 posts on @Elaf_Faisal 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
7 August 2026
Most recent seen missing
20 October 2026
Median time before seen missing
3 days
Seen missing in the last 30 days
1
Polls
The 6 most recent of 39 polls we hold for this entry, as Telegram rendered them when we read the post. A poll’s figures keep moving after that, so each one is dated.
68-year-old man presents with chest pain, ECG showed ST elevation in leads II, III and aVF, BP: 85/60 mmHg and his lungs are clear, what is the most appropriate next step?
IV Furosemide5%
IV normal saline bolus59%
IV Nitroglycerin28%
IV beta blocker8%
Shares as published. No per-option vote count is published by Telegram, so none is shown.
53-year-old man with CKD presents with muscle weakness, ECG shows tall peaked T waves, serum potassium: 6.8 mmol/L, what is the most appropriate initial management?
IV calcium gluconate88%
IV insulin with glucose9%
Oral sodium bicarbonate2%
Nebulized Salbutamol2%
Shares as published, totalling 101%. No per-option vote count is published by Telegram, so none is shown.
Patient admitted 5 days ago with NSTEMI, received unfractionated Heparin, labs upon admission were normal but today platelet: 65 with normal coagulation profile, most likely cause of thrombocytopenia?
Immune thrombocytopenia2%
Heparin induced thrombocytopenia90%
Thrombotic thrombocytopenic purpura4%
Disseminated intravascular coagulopathy4%
Shares as published. No per-option vote count is published by Telegram, so none is shown.
43-year-old-woman has fever, night sweats and unintentional weight loss, has bilateral cervical lymph nodes and splenomegaly, most appropriate next step in management?
FNA of the lymph node36%
Excisional biopsy of the lymph node50%
Bone marrow biopsy12%
Splenectomy2%
Shares as published. No per-option vote count is published by Telegram, so none is shown.
60-year-old man with advanced bronchogenic carcinoma presents with malignant right pleural effusion, he undergoes several therapeutic pleural taps, next best option in management?
Diuretics18%
Ultrafiltration8%
Chemical pleurodesis65%
Low salt human albumin9%
Shares as published. No per-option vote count is published by Telegram, so none is shown.
66-year-old man presents with SOB, he smokes 20 cigarettes/day but is otherwise well, spirometry shows a restrictive pattern, what is the most likely diagnosis?
Pulmonary fibrosis66%
Bronchiectasis27%
Heart failure3%
Asthma4%
Shares as published. No per-option vote count is published by Telegram, so none is shown.
Percentages only — there are no per-option vote counts here, because Telegram publishes none. The public post preview gives each option’s share and a single voter total, and nothing else. Multiplying one by the other would produce a per-option tally that looks measured and is not: the shares are rounded to whole numbers before we ever see them. We print what was published and leave the column that does not exist empty.
The shares need not add up to 100. Rounding alone puts many polls at 99 or 101. A poll that allows more than one answer per voter runs well past 100 by design, and several here do. The bars are drawn against a fixed 100% track at each option’s own percentage rather than normalised to the total, so a poll that exceeds it shows that it does instead of being quietly rescaled.
Read from the 51 most recent posts we hold, published 18 June 2026 to 3 November 2026. Telegram labels each poll by kind — an anonymous poll, a quiz, a closed set of final results — and that label is reproduced rather than paraphrased.
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 2 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 3 September 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.
SMLE TOP10🔥Daily Recalls @Saudi_SMLE_TOP10 · 38,461 Telegram ranks this channel #1 of 84 here — alongside 83 others — read 30 August 2026
Silent🇸🇦 🇸🇦 @silent_2026_2027 · 59,505 Telegram ranks this channel #1 of 83 here — alongside 82 others — read 22 August 2026
SMLE Brain @smlebrain · 18,574 Telegram ranks this channel #2 of 83 here — alongside 82 others — read 4 October 2026
FAIR ⛈ SMLE @dec2020q · 25,926 Telegram ranks this channel #2 of 83 here — alongside 82 others — read 13 September 2026
Review team | Internal medicine @SMLE_medicine · 32,994 Telegram ranks this channel #2 of 83 here — alongside 82 others — read 4 September 2026
Wafa OBGYN @WafaOBGYN · 34,808 Telegram ranks this channel #2 of 83 here — alongside 82 others — read 2 September 2026
Family Physician @FamilyPhysician_1 · 28,425 Telegram ranks this channel #5 of 75 here — alongside 74 others — read 10 September 2026
Fair Q & A✨ @fairdaily · 31,005 Telegram ranks this channel #8 of 81 here — alongside 80 others — read 9 September 2026
مؤتمر صحي 🩺 @medical_conference · 30,014 Telegram ranks this channel #12 of 80 here — alongside 79 others — read 10 September 2026
Local Material Ahmed Adlan @Prof_adlan_local · 19,581 Telegram ranks this channel #13 of 82 here — alongside 81 others — read 1 October 2026
SMLE - B @smlemay · 29,746 Telegram ranks this channel #22 of 81 here — alongside 80 others — read 7 September 2026
Medicine collection 🤍 @medicincollecation · 20,024 Telegram ranks this channel #24 of 88 here — alongside 87 others — read 1 October 2026
OnlineMedED Videos | USMLE Step 2 CK | 1 @USMLEOnlineMedED · 30,342 Telegram ranks this channel #44 of 79 here — alongside 78 others — read 7 September 2026
وظائف طبية medical jobs الفضل للتوظيف الطبي @alfadheldoctor · 43,700 Telegram ranks this channel #46 of 89 here — alongside 88 others — read 28 August 2026
وظائف صحية و طبية 🩺🇸🇦 @ksamedicaljobs · 75,098 Telegram ranks this channel #58 of 85 here — alongside 84 others — read 19 August 2026
Internal Medicine | MW @Medical_Patna · 47,545 Telegram ranks this channel #70 of 91 here — alongside 90 others — read 28 August 2026
This channel appears in 16 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 7 November 2026 — this
entry's latest reading, not the date you are reading this.
“Elaf Faisal - Internal Medicine” (@Elaf_Faisal), 34,083 subscribers as measured 7 November 2026. Telegram Register, tgregister.com/channel/Elaf_Faisal.
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.