Photo, posted without a caption

Channel
医疗咨询、
@zhongyizhiliao6668
On this record: Growth · Engagement · What this channel posts · Reactions · Posts · Citations · Handles named that no longer answer · Cite this entry
32subscribers
-5 since we began measuring on 7 August 2026
Risers and fallers across the register · movement among entries of Under 1,000.
Register entry
| Telegram ID | -1002103292369 |
|---|---|
| Type | Channel |
| Username | @zhongyizhiliao6668 |
| Created | Between 1 November 2023 and 31 May 2024 — estimated from Telegram’s id allocation, not measured. How this range is calculated. |
| First recorded | 12 September 2026 |
| Last confirmed live | 15 September 2026 |
| Measurements held | 5 |
| Confirmed unchanged | 1 time, most recently 15 September 2026 |
| On Telegram | t.me/zhongyizhiliao6668 |
Growth
| Measured (UTC) | Subscribers | Change |
|---|---|---|
| 15 Sept 2026, 06:21 | 32 | -2 |
| 12 Sept 2026, 08:24 | 34 | no change |
| 30 Aug 2026, 16:36 | 34 | -2 |
| 23 Aug 2026, 11:38 | 36 | -1 |
| 7 Aug 2026, 11:57 | 37 | first reading |
Engagement
20 posts held, back to 7 June 2024 — the 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.
Nothing published in the last 30 days. ERR and ER are rolling 30-day measures, so there is nothing to compute — we hold 20 posts for this entry, the most recent from 27 August 2026. An engagement rate over an empty window would be a number about nothing.
What this channel posts
- Video runtime
- 1m 16s
- Average length
- 1m 16s
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
4 reactions across 4 posts, in 1 kind.
| Reaction | Count | Share | Share, drawn |
|---|---|---|---|
| 👍 | 4 | 100.0% |
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 4 of the 20 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 4 reactions in total: the kind of figure the paragraph above means by “a reaction total printed elsewhere on the page”.
Measured over the 20 most recent posts we hold, published 7 June 2024 to 27 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
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以上图片是2026经过年审的营业执照
Photo, posted without a caption
Channel name was changed to «医疗咨询、»
https://t.me/Lin_bao71588 https://t.me/zhongyizhiliao6668 @fh686899 @hifaxj 菲华门诊部专业: 我们致力于保护和弘扬传统医疗的古代智慧。我们的传统医疗,护理提供全面的健康服务方法:将古老的治疗方法与现代科学融为一体。我们的核心重点是整合医学是一种革命性的医疗保健方法。它结合了传统西医和整体治疗传统的智慧。通过融合两种治疗的优点。它使患者获得了最佳的健康。 Specialty of Feihua Clinic: We are committed to protecting and promoting the ancient wisdom of traditional medicine. Our traditional medical care provides a comprehensive health service method. Integrate …
https://t.me/Lin_bao71588 预约林医生: @fh686899 @hifaxj 菲华门诊部服务项目: 内科:伤风感冒,胃肠病, 外科:痔疮,包皮过长,包茎病, 妇科:超声波检查,药流,人流,乳腺小叶增生,乳房肿瘤,卵巢囊肿,妇科疑难杂症。 其他:针灸、中医推拿、艾灸。火疗、按摩、特定电磁波照射治疗、拔火罐、药物香薰治疗。 疑难杂症有:鼻炎,肝病,尿毒症,三高症,糖尿病,各种肿瘤,淋病,梅毒,尿道炎。各种皮肤病。 Feihua Medical CliniC Service items: Internal medicine: colds, gastroenteritis, common diseases. Surgery: Hemorrhoids, too long wrapping, peeling phimosis cortex. Debridement…
我们关心您的健康,如果您对自己的健康有任何担忧,请在购买适合您的药物之前立即咨询医生。
医疗咨询、 pinned Deleted message
https://t.me/Lin_71588 菲华门诊部的中医采用以下治疗方法: Chinese medicine in Feihua Clinic adopts the following treatment methods: 一:汗:用大量排汗的方法。 Sweat: by sweating a lot: 二:吐:把吃进去的的食物往外吐出来。 Spit out the food you have eaten. 三:下:把残留在胃肠里食品,往大便,小便向外排泄。 Discharge the food left in the stomach and intestines to stool and urine to clean up the toxins in the gastrointestinal tract. 四:和:中和用药,就是用相反相乘的药结合治疗,达到调整人体阴阳平衡的目的。 Harmony: it is a neut…
👍1
https://t.me/Lin_71588 https://t.me/Zhongyizhiliao6668 你来门诊部看。或者科普一下,你细看一下,男性:阴茎勃起时,海棉体龟头不能自然露出.称为阴茎包皮过长,会使尿后污渍存留,不方便清洗,易传染给对方,自己易得包皮炎,对方有艾滋病,会传染给你,
菲华门诊部的中医采用以下治疗方法: Chinese medicine in Feihua Clinic adopts the following treatment methods: 一:汗:用大量排汗的方法。 Sweat: by sweating a lot: 二:吐:把吃进去的的食物往外吐出来。 Spit out the food you have eaten. 三:下:把残留在胃肠里食品,往大便,小便向外排泄。 Discharge the food left in the stomach and intestines to stool and urine to clean up the toxins in the gastrointestinal tract. 四:和:中和用药,就是用相反相乘的药结合治疗,达到调整人体阴阳平衡的目的。 Harmony: it is a neutralizing drug, that is,…
Showing the 12 most recent of 20 posts we hold for @zhongyizhiliao6668. 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.
Mentions
Names
Channels on the register whose handles appear in this channel's posts.
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.
Handles this channel named that no longer answer
- Dead references
- 2
- handles named in this channel’s posts, vacant today
- Evidenced gone
- 0
- we ourselves saw one of these resolve, at some point
- Never seen alive
- 2
- vacant every time we have ever looked
@zhongyizhiliao6668 named 2 handles that resolve to nothing today. That is a fact about the reference, not necessarily a fact about the handle’s history — see the two groups below.
Most of these may never have existed as a live channel at all. A handle a channel names can be a typo, an aspirational name nobody registered, or a channel that was already gone before this one ever mentioned it. Unless a row below is marked evidenced, all we know is that it references a handle that is not a live channel today — not that anything “died”. How this is measured.
Never seen alive
References a handle that is not a live channel — we have no record it ever was one.
named in 7 posts, 13 September 2026 – 13 September 2026
named in 2 posts, 13 September 2026 – 13 September 2026
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 15 September 2026 — this entry's latest reading, not the date you are reading this.
“医疗咨询、” (@zhongyizhiliao6668), 32 subscribers as measured 15 September 2026. Telegram Register, tgregister.com/channel/zhongyizhiliao6668.
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.