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 10 September 2026 and assigned it the closest of 31 fixed categories, at 97% 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
30 measurements spanning 41 days, net +108. 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 16,951–17,091 and does not start at zero.
Measurement log — every subscribers count we have recorded, most recent 20 of 30
Measured (UTC)
Subscribers
Change
18 Sept 2026, 01:58
17,075
+1
15 Sept 2026, 22:00
17,074
+8
14 Sept 2026, 07:41
17,066
+8
12 Sept 2026, 19:15
17,058
+7
10 Sept 2026, 17:40
17,051
+17
7 Sept 2026, 17:20
17,034
+13
4 Sept 2026, 16:57
17,021
+1
3 Sept 2026, 02:28
17,020
+3
2 Sept 2026, 02:45
17,017
+2
1 Sept 2026, 03:56
17,015
-8
30 Aug 2026, 07:57
17,023
+4
29 Aug 2026, 07:34
17,019
+1
28 Aug 2026, 04:34
17,018
+1
27 Aug 2026, 06:47
17,017
+5
26 Aug 2026, 05:58
17,012
+3
25 Aug 2026, 04:37
17,009
-1
24 Aug 2026, 02:59
17,010
-3
22 Aug 2026, 13:16
17,013
+10
21 Aug 2026, 06:27
17,003
+1
20 Aug 2026, 07:11
17,002
first reading
Engagement
60 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 52 pages of Telegram’s post history, 20 posts per page.
ERR · 30 days
7.27%
avg views ÷ 17,075 subscribers
Avg views / post
1,240
19 posts measured
Reaction rate
0.193%
reactions ÷ views · ER floor
Posts in window
19
of 60 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. It is computed over the 15 of 19 measured posts that carry a reaction reading, and over those same posts' views.
What these figures were computed from
Window
Rolling 30 days · latest post in window 31 August 2026
Posts held
60 (28 July 2026 – 31 August 2026)
Views total
23,585
Reactions total
36
Forwards / comments
not exposed by the public surface — not measured, not estimated
Readings taken
3 Sept 2026, 09:32 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
3m 34s
Average length
1m 47s
Measured directly from 2 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
109 reactions across 35 posts, in 2 distinct kinds. The most used accounts for 89.0% of them.
Every reaction kind recorded on the sample, most used first
Reaction
Count
Share
Share, drawn
❤
97
89.0%
👍
12
11.0%
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 39 of the 60 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 109 reactions in total: the kind of figure the paragraph above means by “a reaction total printed elsewhere on the page”.
Measured over the 60 most recent posts we hold, published 28 July 2026 to 31 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.
The #BLUEProtocol is a rapid bedside #lung ultrasound technique for patients with acute respiratory failure. Using 6 standardized scanning points, this protocol helps identify common causes of acute dyspnea, such as #pneumonia, pulmonary edema, and pneumothorax, in less than 5 minutes.
📖 Read the full article to learn more: ja.ma/3S2Jq6G
A patient with severe respiratory distress may have a very high peak inspiratory flow requirement.
Even when the Venturi mask delivers the correct oxygen concentration, the total flow generated by the device may not always exceed the patient's inspiratory demand.
When this happens, additional room air may be entrained around the mask, potentially reducing the effective FiO₂.
Key Point
With a Venturi mask, always …
Choosing the Right Oxygen Delivery Device in the ED & ICU 🫁
Matching FiO₂ and Flow to the Patient’s Inspiratory Demand
Selecting an oxygen-delivery device is not simply about choosing a target FiO₂. In critically ill patients, especially those with tachypnea and high inspiratory demand, the total flow delivered by the device must also be considered.
A useful bedside principle is:
«If the oxygen-delivery system ca…
Choosing the Right Oxygen Delivery Device in the ED & ICU 🫁
🫁 Assess → Select → Monitor → Reassess → Escalate when necessary.
#respiratorytherapist #mechanicalventilation #be_anRT
Chronic rhinosinusitis (CRS) is characterized by persistent inflammation involving the nasal and sinus system, with symptoms lasting 12 weeks or longer. Helping your patients recognize the distinction between CRS with and without nasal polyps can help inform evaluation and appropriate disease management.
For healthcare providers, increasing awareness of CRS without nasal polyps can also help patients recognize when …
COPD: Causes, Signs & Risk Factors
COPD, or chronic obstructive pulmonary disease, is a long-term lung condition that causes persistent airflow limitation. It mainly includes chronic bronchitis and emphysema and usually develops gradually over years.
🟣 Common Causes
➟ Cigarette smoking is the most important cause
➟ Long-term exposure to second-hand smoke
➟ Indoor air pollution from biomass fuels used for cooking…
📚 Four Essential Textbooks for Respiratory Care Students & Professionals
For anyone studying or practicing Respiratory Care, these textbooks are highly valuable additions to your professional library. Together, they cover the major foundations of our field—from anatomy and physiology to clinical assessment, equipment, and neonatal/pediatric care.
🔹 Wilkins’ Clinical Assessment in Respiratory Care, 10th Edition (202…
🫁 CAPNOGRAPHY: ETCO₂
More than just a number—it’s a window into ventilation, perfusion, and metabolism.
📊 Normal ETCO₂: 35–45 mmHg
⬆️ High ETCO₂
Think hypoventilation
• ↓ Respiratory rate
• ↓ Tidal volume
• CO₂ retention
• Rebreathing
⬇️ Low ETCO₂
Think hyperventilation or reduced perfusion
• ↑ Respiratory rate
• ↓ Cardiac output
• Pulmonary embolism
• Severe hypotension
• Cardiac arrest
💡 TMC TIP:
A sudden drop…
❤1
Showing the 12 most recent of 60 posts we hold for @Respiratory_Care_Global. 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.
Polls
The poll we hold for this entry, as Telegram rendered it when we read the post. A poll’s figures keep moving after that, so each one is dated.
1. During pre-study physiologic calibration, the patient is instructed to look left, right, up, and down. The primary purpose is to:
A. Establish EEG sensitivity16%
B. Verify EOG signal response and polarity58%
C. Determine electrode impedance11%
D. Identify REM sleep14%
Shares as published, totalling 99%. 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 60 most recent posts we hold, published 28 July 2026 to 31 August 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
Republishes
Channels on the register whose posts this channel has forwarded.
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.
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.
Boards and Beyond 2024 @Boards_Beyond_videos · 41,035 Telegram ranks this channel #3 of 76 here — alongside 75 others — read 30 August 2026
ICU and pulmonary medicine @ahmedyasminc1 · 25,867 Telegram ranks this channel #15 of 75 here — alongside 74 others — read 13 September 2026
THE WHITE ARMY @whitearmyofmedicos · 103,492 Telegram ranks this channel #17 of 60 here — alongside 59 others — read 26 August 2026
Hakimed: Medical Resources @HakimApps_Guideline · 32,777 Telegram ranks this channel #19 of 80 here — alongside 79 others — read 5 September 2026
PLAB, MRCP, MRCS, NBME @Plab_MRcp · 69,759 Telegram ranks this channel #19 of 53 here — alongside 52 others — read 26 August 2026
Internal Medicine Videos & books @medicinevideoss · 102,991 Telegram ranks this channel #21 of 75 here — alongside 74 others — read 26 August 2026
NEJM (The New England Journal of Medicine) @The_NEJM · 27,342 Telegram ranks this channel #22 of 79 here — alongside 78 others — read 11 September 2026
UPDATES IN MEDICINE @Updates_in_Medicine · 47,787 Telegram ranks this channel #22 of 74 here — alongside 73 others — read 26 August 2026
Medical Books @MedicalBooksStoreA · 42,123 Telegram ranks this channel #23 of 67 here — alongside 66 others — read 29 August 2026
Artículos médicos Twitter @articulosmedicosdelMedtwitter · 51,771 Telegram ranks this channel #30 of 77 here — alongside 76 others — read 24 August 2026
Al-Azhar Assiut Medical School @AlAzharAssiutMedicalSchool · 26,268 Telegram ranks this channel #38 of 73 here — alongside 72 others — read 13 September 2026
Polite Doctor🩺 @skills_first · 42,535 Telegram ranks this channel #38 of 73 here — alongside 72 others — read 29 August 2026
Medicina Interna & Medicina Crítica & Emergencias.Artículos actualizados. @medicinaIntern · 41,093 Telegram ranks this channel #44 of 71 here — alongside 70 others — read 30 August 2026
Internal Medicine @inter_first · 29,634 Telegram ranks this channel #45 of 72 here — alongside 71 others — read 8 September 2026
Medical Mnemonics @medical_mnemonics · 63,572 Telegram ranks this channel #45 of 70 here — alongside 69 others — read 26 August 2026
Urgencias Criticas @urgenciascriticas · 24,062 Telegram ranks this channel #47 of 73 here — alongside 72 others — read 17 September 2026
Internal Medicine - Medicina Interna @loacro01 · 30,709 Telegram ranks this channel #47 of 72 here — alongside 71 others — read 7 September 2026
Medical Guidelines 2025_2026 @Mmmmmm221234 · 35,955 Telegram ranks this channel #49 of 66 here — alongside 65 others — read 2 September 2026
Clinical Notes @Clinical_Notes · 39,371 Telegram ranks this channel #49 of 79 here — alongside 78 others — read 30 August 2026
Clinical Practice guidelines @ClinicalPharmGuideline · 60,754 Telegram ranks this channel #50 of 78 here — alongside 77 others — read 22 August 2026
internal medicine @easymedicine7 · 29,375 Telegram ranks this channel #52 of 73 here — alongside 72 others — read 8 September 2026
doctor's notebook @doctorsnotebooks · 24,746 Telegram ranks this channel #58 of 75 here — alongside 74 others — read 16 September 2026
📚Medicine Books📚 @medallbooks · 45,555 Telegram ranks this channel #59 of 62 here — alongside 61 others — read 28 August 2026
MBFD2018 @mbfd2018 · 78,426 Telegram ranks this channel #63 of 64 here — alongside 63 others — read 21 August 2026
This channel appears in 26 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 18 September 2026 — this
entry's latest reading, not the date you are reading this.
“Respiratory Care Profession” (@Respiratory_Care_Global), 17,075 subscribers as measured 18 September 2026. Telegram Register, tgregister.com/channel/Respiratory_Care_Global.
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.