UDLCO: AI healthcare complexity and hyperlocality

 Introduction:

Hyperlocal has been described as "information oriented around a well-defined community with its primary focus directed toward the concerns of the population in that community"

Also been described as referring to "the emergent ecology of data (including textual content), aggregators, publication mechanism and user interactions and behaviors which centre on a resident of a location and the business of being a resident"

Hyperlocal content has two major dimensions: geography and time. 

More recently, hyperlocal content has evolved to include GPS enabled internet integrated mobile applications which score highly on both the geographic and the time dimensions. They are capable of delivering content that is relevant not just in a community but relevant right down to the individual within a geographic area that can be measured in meters and blocks not towns and neighborhoods. They are also capable of delivering content relevant at very short timescales such as seconds or minutes not just days or weeks.

https://en.m.wikipedia.org/wiki/Hyperlocal

• "Communities can play a key role in addressing health equity issues through hyper local healthcare delivery models that tailor interventions to address specific local needs and culturally sensitive contexts. 
• Success in delivering on population-specific needs depends on health system’s ability to triangulate data from multiple sources, respond to needs with innovative and timely interventions in collaboration between communities and partners"

Unquote : https://kpmg.com/be/en/home/insights/2023/04/ps-hyper-local-community-healthcare-mode.html

UDLCO summary:

The conversations below begin with global discussion around AI healthcare as well as 2.0 healthcare and their limitations that can be tackled through hyperlocal data capture and feedback (blended with AI) content delivered along with an illustration of the same from a user driven healthcare hyperlocal data capture and feedback learning platform called PaJR.

UDLCO Keyword glossary:

http://userdrivenhealthcare.blogspot.com/2023/11/glossary-of-user-driven-healthcare.html?m=1

Conversational Transcripts:

[12/11, 17:49] SPAI Health: A poignant reminder on how hype-cycle works (and abysmally falls). Technology is a great tool but use-cases need to be hyperlocal. There is no one size fits all, especially when it comes to healthcare.

[12/11, 18:39] rb: Thanks for this interesting comment!

I was taking some real patients for our workshop with engineers on "tech end user driven healthcare' here and this will be a good opening line!

[15/11, 06:57] AT AI Healthcare: Here is a research publication on *Medical Appropriateness*.

https://www.springerprofessional.de/en/great-ai-in-medical-appropriateness-and-value-based-care/26487210

[15/11, 07:54] AT AI Healthcare: Both *Medical Appropriateness* and *Medical Necessity* are necessary for *Value-based Care*.

[15/11, 08:06] S: This is possible, but is a complex issue. Of course using SNOMED it is definitely possible to design such a system. One that is practical and is able to do it in real-time. Raise appropriate alerts and warnings. To be effective, the algorithm should be running in the background, constantly checking for inconsistencies and errors. Needless to say, the design is complicated.

[15/11, 08:20] AT AI Healthcare: You are absolutely right - this is highly complex. Therefore, we used *Neuro-Symbolic AI* to address this complexity real-time. 😊

[15/11, 08:32] S: I did some research of my own. AI vs coded approach. In healthcare, due to legal and ethical issues, it is imperative that errors are avoided or kept at a minimum. We medicos subscribe to the dictum of _primum non nocere_ - firstly, do no harm. AI models have an inherent error - mostly the training & validation data-related. Coded provides precision. It is binary - either true or false. That is why there is no alternative to using something like SNOMED. The large vocabulary, all coded by their concept definition using semantic triple and description logic, provides a wide coverage of the many information that gets collected during any clinical encounter.

[15/11, 09:31] ATAI Healthcare: I use *GREAT* AI. It stands for Generative, Responsible, Explainable, Adaptive, Trustworthy Artificial Intelligence.

[15/11, 10:19] S: You have my very best wishes in convincing the medicos.

[15/11, 11:00] ATAI Healthcare: My last comment on this subject. I don't try or even need to convince a medico. I use medical data to prove my models. Medical being safety critical domain, I know - if my model works on medical, it works in any other domain. Like if you can drive safe without using horn in Bangalore, you can drive anywhere in the world. 😊

[15/11, 11:05] Rkb: I completely agree with the later statement, if u can drive in India u can drive anywhere in the world 😀

[15/11, 11:12] rb: Provided you can pass their licencing exams, which appears to be easier to pass in India!

[15/11, 12:51] S: Having worked with both AI/ML and codes, I am firmly convinced that without codes CDSS is not advisable. Many times diagnosis is only possible on post-mortem. CDSS is used in treatment/management for which high degrees of precision are required.

[15/11, 12:55] ATAI Healthcare: I shall deliver lecturers on *"Architecting Secure Software Systems"* and *"Cybersecurity Cognitive Graph"* at NITK Surathkal at the *Five Days Faculty Development Programme On Software and Systems Security*, 9th to - 13th December 2024" (https://www.nitk.ac.in/upcoming_events). 

There are some vacant seats. If you know any faculty interested in Cybersecurity, please pass on this message.

[15/11, 15:31] SPAI Health: Interesting discussion. Both Dr.A and Dr.S I guess are medicos, but they seem to be so knowledgeable that I suspect they have a PhD in Computer Science too in the side🙂👍! 

One key thing we are realising in the AI community is that LLMs have limitations in specific domains, as they are optimised for freeform reasoning from large, disconnected datasets (case in point is the failure of Babylon to make the cut, which we discussed recently). Rule based use of logic (expert systems) exists from the days of IBM Watson and is perhaps best suited for healthcare but then it lacks the ability to take on board the latest and evolving scientific thoughts. There is also a hybrid track currently upcoming which tries to marry these two ends of the spectrum using domain specific knowledge graphs to upgrade and focus LLMs capabilities. There is also a need to go hyperlocal due to the wide variations in datasets across demographics. To some extent using RAG along with Edge AI is a potential solution.

[15/11, 15:58] S: Dr AT is a _bona fide_ computer scientist. Works in hardcore AI applications. Health is one of his areas of interest. I am a medical professional and health informatics specialist, majorly into data standards, interoperability and analytics. 🙂

[15/11, 21:37] rb: "From the doctor's summing up, Ivan Ilych deduced the conclusion that things looked bad, and that he, the doctor, and most likely everyone else, did not care, but that things looked bad for him. And this conclusion impressed Ivan Ilych morbidly, arousing in him a great deal of pity for himself, of greater anger against this doctor who could be unconcerned about a matter of such importance.”

Unquote

https://pmc.ncbi.nlm.nih.gov/articles/PMC3249844/

[16/11, 07:10] ATAI Healthcare: Here is Fig 8-1. Diagnostic approach to hemolytic anemia from Benjamin Djulbegovic's *Reasoning and Decision Making in Hematology* published in 2992.

[16/11, 08:31]rb: Excellent illustration of the global limitation in rule based algorithms in tackling clinical complexity (for those not handling real patients hyperlocally) further enhancing the point @⁨SPAI Health⁩ was trying to make. Ben assumes that if coombs negative,  HS would be the most likely diagnosis probabilistically as he's a US citizen but try telling that to an Indian or someone from Dhaka: https://pmc.ncbi.nlm.nih.gov/articles/PMC2975852/

[16/11, 08:34]rb: Many of our patients in our resource limited rural medical college are coombs positive but we don't jump to a diagnosis of AIHA as we know that it could be false positive and largely we still have to weigh everything on the basis of the patient event timeline (aka history) as well as clinical signs, external or internal.

[16/11, 08:55]G: In 1983, my consultant Prof SB was discussing using weighted scores for automated diagnosis. He asked around for symptoms and signs for possible appendicitis and said a more than a 10 score is final. The conversation went like this for the patient we were observing 

Pain abd ——1 

Fever ——1 

High TLC  ——1 

Loss of appetite  ——1/2

Vomiting ——1 

Tender rt Iliac fossa  ——10

Somewhat clinching the diagnosis

[16/11, 08:55] G: Unfortunately AI can’t examine for tenderness

[16/11, 09:10]rb: Yes it can't capture data unless fed. Not long before it grows up to robotic arms

[16/11, 09:11]rb: Couldn't resist sharing this happening in our home health PaJR right now!👇

Learning summary spoiler: AI LLMs are more likely to err about medicine facts on the side of caution lest they damage their customers egos!

Those who don't understand the script can ask meta AI to translate it for them.

Morning PaJR session:

[14/11, 11:36] PaJR moderator: Apnake baki der group a add korle apni unader keo eta ki bhabe kora jete pare sheta dekhiye dite parben?

[14/11, 19:12] Patient Advocate 63M Metabolic Syn: কোনটা ? AI LLM?

[14/11, 19:12] Patient Advocate 63M Metabolic Syn: 

জেলা শহরে চারটা নাগাদ একটা মশলা ধোসা খাওয়া হল।

[14/11, 19:12] Patient Advocate 63M Metabolic Syn: ছটা নাগাদ প্রাতঃভ্রমণে বের হয়ে পৌনে সাতটা নাগাদ গন্তব্যে পৌঁছে কিছুক্ষণ বিশ্রাম নিয়ে সাড়ে সাতটা নাগাদ চায়ের দোকান। ওখানে এক পেয়ালা চিনি ছাড়া দুধ চা ও কিছুক্ষণ পর এক বাটি দেশী ছোলার ঘুগনি খাওয়া হলে আটটা নাগাদ বাজার ঘুরে বাড়ি ফিরতে ফিরতে প্রায় পৌনে নয়টা। তারপর স্নানাদি সেরে সকালের খাওয়া সেরে ও ওষুধ খেয়ে কিছুক্ষণ বিশ্রাম নিয়ে এখন চলেছি জেলা শহরের দিকে। ফিরতে ফিরতে বিকেল হয়ে যাবে।

[14/11, 19:22] Patient Advocate 63M Metabolic Syn: এইমাত্র বাড়ি ফিরে এলাম।

[14/11, 22:11] PaJR moderator: Hain

[14/11, 22:15] Patient Advocate 63M Metabolic Syn: একটু শিখিয়ে পড়িয়ে নিলে অসুবিধা হওয়ার কথা নয়।

[15/11, 04:29] Patient Advocate 63M Metabolic Syn: চারটায় ঘুম ভাঙ্গার পর কিছুক্ষণ যাবত আপনাদের মেসেজগুলো দেখছিলাম। পাঁচটা নাগাদ শয্যাত্যাগ করব।

[15/11, 10:09] PaJR moderator: Apnakei sheta amader baki patient der jonye korte anurodh roilo jar jonye apnake unader group a add kore dicchi

[15/11, 17:25] Patient Advocate 63M Metabolic Syn: চেষ্টা করলাম, একবার দেখে নিয়ে জানান, আপনি যা চাইছেন সেটা হল কি না।

[15/11, 17:33] Patient Advocate 63M Metabolic Syn: স্থানীয় কিছু অনুষ্ঠানের কারণে সকাল সাড়ে দশটা নাগাদ বের হয়ে বাড়ি ফিরতে ফিরতে প্রায় সাড়ে চারটা। মাঝে এক -দেড়টা নাগাদ প্রথমে এক কাপ চিনি ছাড়া দুধ চা ও অর্ধেক স্যাঁকা পাঁপড় ও কিছু পরে এক গ্লাস লাল চা খাই। তিনটা নাগাদ নেমন্তন্নের খাওয়া একটা হোটেলে:

ভাত

কাঁচা শসা

লেবু

ডাল

পাঁপড় ভাজা 

মাছের মাথা দিয়ে বাঁধা কপি 

মিষ্টি কুমড়োর তরকারি 

কাৎলা মাছ ভাপা

পাঁঠার মাংস 

চাটনি ও

একটা বড় রসগোল্লা।

[15/11, 21:44] AI : ঠিক আছে! তাহলে খাবারের তালিকা হলো:

- পুরি/লুচি - ২টা (প্রসাদ) 🍞

- শসা ও গাজর - স্যালাড 🥒🥕

- তিন-চার টুকরো পাঁঠার মাংস 🍖

- আলু লাউ দিয়ে বুটের ডাল 🍲

[15/11, 21:44] AI : এখন খাবারটা আরও জমজমাট হয়ে গেছে! পুরি/লুচি তো দারুণ, আর পাঁঠার মাংসের সাথে আলু লাউ দিয়ে বুটের ডাল হলে তো স্বাদে কোনো কমতি থাকবে না।

[15/11, 21:44] AI : স্যালাডও স্বাস্থ্যকর এবং তাজা স্বাদ যোগ করবে।

[15/11, 21:44] AI : এটা একটা ভারী এবং পুষ্টিকর খাবার হবে! উপভোগ করো! 😊🍽️

[15/11, 21:45] AI : Let's break it down based on your updated meal:

1. *পুরি/লুচি (২টা)*: Approx 300 kcal (150 kcal each)

2. *শসা ও গাজর (স্যালাড)*: Approx 15 kcal (5 kcal for cucumber and 10 kcal for carrot)

3. *পাঁঠার মাংস (৩-৪ টুকরো)*: Approx 200 kcal (depending on the portion size)

4. *আলু লাউ দিয়ে বুটের ডাল*: Approx 200 kcal (this can vary based on preparation)

[15/11, 21:45] AI : *Total Estimated Nutritional Information:*

- *Total Calories*: Approx 715 kcal

- *Protein*: Approx 30g (from meat and dal)

- *Carbs*: Approx 100g (from puri, vegetables, and dal)

- *Sugars*: Approx 5g (from vegetables)

- *Fat*: Approx 30g (from puri and meat)

- *Fiber*: Approx 10g (from vegetables and dal)

[15/11, 21:45] AI : This meal is quite hearty and provides a good balance of carbs, protein, and healthy fats. The addition of salad adds some freshness and fiber, which is great!

[15/11, 21:47] Patient Advocate 63M Metabolic Syn: এ তো এক মহা বিপদে ফেললেন ! এ তো সবই বলে দারুন/ভালো। !!!

[16/11, 08:42] PaJR moderator: হ্যাঁ দুর্ভাগ্যবশত এআই এলএলএম আমাদের একাডেমিক নার্সিসিজম খাওয়ানোর জন্য ডিজাইন করা হয়েছে!

Yes unfortunately AI LLMs are designed to feed our academic narcissism!

https://24fpatient.blogspot.com/2024/10/63m.html

[16/11, 09:29]rb: Our current tryst with AI LLMs in our healthcare education and practice user windows can be summarised as below (albeit experiential anecdotal opinion): 

AI is like a new boisterous team member, kiddishly brilliant in places and yet a complete let down when you start to think you may begin depending on it!

When you are awed by it's brilliant analysis of study data that it has itself looked up you realise later that it's confabulated the paper and the references itself!

When you are beginning to praise it for its good analysis of a real paper URL you have provided, you realise it's changing the numbers every time you keep asking it repeatedly in different groups!

When you are happy it's able to do a marvelous thematic analysis of your thesis data you realise it's again fudged some numbers here and there!

Creative commons license: https://commons.m.wikimedia.org/wiki/File:Diagnosis_By_Radio,_1925_(telemedicine).webp#mw-jump-to-license

Medicine Pharmer: Morning newspaper inspired journal club using critical realist heutagogy driven by meta AI

Journal club conversational Transcripts:

Shared in group:

https://timesofindia.indiatimes.com/city/hyderabad/fatty-liver-disease-epidemic-in-india-are-we-ignoring-a-silent-killer/articleshow/115063211.cms

[08/11, 08:15] rb: Thanks for initiating this morning's journal club for all the  staff doctors (minus PGs and UGs).

🙂🙏

The article, "Fatty liver disease epidemic in India: Are we ignoring a silent killer?" (Times of India, Hyderabad), by Amrita Didyala, appears to be an advertorial promoting awareness about non-alcoholic fatty liver disease (NAFLD).

Here's a critical analysis of its potential influence on collective medical cognition:

*Biases and Concerns:*

1. *Sensationalized Language*: The title and content use emotive language, creating fear and urgency, potentially leading to unnecessary anxiety and testing.

2. *Conflict of Interest*: The article may be sponsored by pharmaceutical or medical device companies, which could influence the content.

3. *Lack of Transparency*: No disclosure of financial ties or sponsorship.

4. *Selective Presentation*: Focuses on NAFLD as a "silent killer" while downplaying lifestyle modifications and emphasizing pharmaceutical solutions.

*Influence on Collective Medical Cognition:*

1. *Over-testing and Overtreatment*: The article may contribute to increased fibro scans and genetic testing, potentially leading to:

    - Unnecessary procedures.

    - Overdiagnosis and overtreatment.

    - Increased healthcare costs.

2. *Misinterpretation of Risk*: The article exaggerates NAFLD risks, potentially leading to:

    - Misinformed patient decisions.

    - Unnecessary anxiety.

3. *Non-Evidence-Based Practices*: The article promotes:

    - Fibro scans as a routine diagnostic tool (limited evidence).

    - Genetic testing for NAFLD (unclear benefits).

*Red Flags:*

1. *Unsubstantiated Claims*: Statements like "NAFLD is a silent killer" and "epidemic" are not supported by credible evidence.

2. *Overemphasis on Genetic Predisposition*: Genetic testing is oversold as a predictor of NAFLD risk.

3. *Lack of Discussion on Lifestyle Modifications*: Downplays or omits the importance of lifestyle changes.

*Recommendations for Critical Evaluation:*

1. *Seek Independent Information*: Consult reputable sources (e.g., peer-reviewed journals, professional guidelines).

2. *Evaluate Evidence Quality*: Assess the strength of evidence supporting claims.

3. *Consider Multiple Perspectives*: Seek input from diverse healthcare professionals.

4. *Beware of Emotional Appeals*: Make informed decisions based on evidence.

*Countering Potential Harm:*

1. *Promote Evidence-Based Practices*: Encourage healthcare professionals to adhere to established guidelines.

2. *Foster Critical Thinking*: Educate patients and healthcare professionals to critically evaluate information.

3. *Emphasize Lifestyle Modifications*: Highlight the importance of lifestyle changes in NAFLD management.

By recognizing potential biases and critically evaluating information, healthcare professionals and patients can make informed decisions and mitigate the risks of over-testing and overtreatment.

*Specific Critique of the Article:*

1. *Provide balanced information*: Include lifestyle modifications and nuanced discussions of NAFLD risks.

2. *Disclose financial ties*: Clearly acknowledge sponsorship or financial relationships.

3. *Support claims with evidence*: Use credible sources to substantiate statements.

[08/11, 08:19]rb: Journal club continuation:

A 2.2-fold increased risk associated with the PNPLA3 gene variant does not necessarily imply causality for fatty liver. Correlation does not equal causation.

_Limitations and Considerations:_

1. *Multifactorial disease:* NAFLD is influenced by various factors, including diet, exercise, obesity, insulin resistance, and genetic predisposition.

2. *Confounding variables:* The study may not have fully accounted for lifestyle factors, socioeconomic status, or other genetic variants that contribute to NAFLD.

3. *Gene-environment interaction:* The expression of PNPLA3 may be influenced by environmental factors, making it challenging to isolate the genetic effect.

4. *Penetrance and expressivity:* The PNPLA3 variant may have incomplete penetrance (not all carriers develop NAFLD) and variable expressivity (severity differs among carriers).

5. *Population-specific findings:* Results may not generalize to other populations with different genetic backgrounds or environmental exposures.

_Alternative Explanations:_

1. *Association, not causation:* The PNPLA3 variant might be a marker for other underlying factors contributing to NAFLD.

2. *Linkage disequilibrium:* The PNPLA3 variant may be linked to other genetic variants that contribute to NAFLD.

_Contextualizing the Findings:_

1. *43/191 non-carriers with NASH:* This highlights the significance of non-genetic factors in NAFLD development.

2. *Prevalence of NASH:* 20.5% in non-carriers vs. 43.8% in carriers suggests that environmental factors contribute substantially to NASH risk.

To establish causality, further research should investigate:

1. *Mendelian randomization studies:* Examining the effect of PNPLA3 variants on NAFLD risk using genetic instruments.

2. *Functional studies:* Investigating the biological mechanisms by which PNPLA3 influences liver fat accumulation and NAFLD progression.

3. *Gene-environment interactions:* Examining how lifestyle factors modify the expression and effects of PNPLA3.

These are from further critical appraisal of a journal article that we were driven to search after getting inspired to appraise the advertorial shared earlier

[08/11, 08:21]rb: Evidence from journal article surrounding the PNPLA3 gene and fatty liver in PICO format (article referenced at the bottom):

*P (Population):* Individuals with non-alcoholic fatty liver disease (NAFLD)

*I (Intervention/Exposure):* Presence of PNPLA3 rs738409 G allele (I148M variant)

*C (Comparator):* Individuals without PNPLA3 rs738409 G allele

*O (Outcome):* Risk of developing non-alcoholic steatohepatitis (NASH) and advanced liver fibrosis

*Representative Reference:*

- Romeo et al. (2010) - "Genetic variation in PNPLA3 confers susceptibility to nonalcoholic fatty liver disease" [1]

*Data:*

- *PNPLA3 rs738409 G allele carriers:* 49.2% of NAFLD patients (95/194)

- *Non-carriers:* 22.5% of controls (43/191)

- *NASH risk:* 2.22-fold increased risk (95% CI: 1.51-3.27)

- *Advanced liver fibrosis risk:* 3.26-fold increased risk (95% CI: 1.84-5.77)

- *Liver fat content:* 15.3% higher in G allele carriers (p=0.001)

*Absolute Values:*

- *NASH prevalence:* 43.8% in G allele carriers vs. 20.5% in non-carriers

- *Advanced liver fibrosis prevalence:* 24.7% in G allele carriers vs. 7.5% in non-carriers

This study demonstrates a strong association between the PNPLA3 rs738409 G allele and increased risk of NASH and advanced liver fibrosis in NAFLD patients.

Reference:

[1] Romeo et al. (2010). Genetic variation in PNPLA3 confers susceptibility to nonalcoholic fatty liver disease. Nature Genetics, 42(2), 146-149. doi: 10.1038/ng.511

[08/11, 08:23] op: Good information Sir

[08/11, 08:24]rb: Thanks for inspiring us to look for it 🙂🙏

Creative commons license: https://commons.m.wikimedia.org/wiki/File:NAFLD_liver_progression.svg#

UDLC Feedback learning loops:

[10/11, 20:55]st: We will stop buying toasters and grills now.. AI can pick up any thing and totally roast it. We just have to set the temperature , depth and flavour😀

[10/11, 20:58]st: Grok 2 did a pretty good job in roasting .. this is perplexity -. Let's analyze the content for potential logical flaws and scientific deviations:

## Potential Issues in the Article

**Prevalence Claims**

The article states that fatty liver disease (FLD) has an "estimated 30% prevalence in the general population" of India[2]. However, it doesn't provide a source for this statistic or specify whether this refers to non-alcoholic fatty liver disease (NAFLD) or includes alcoholic fatty liver disease as well.

**Genetic Claims**

1. The article mentions a "particular gene, PNPLA3" that makes people more vulnerable to fatty liver without alcohol consumption[2]. While PNPLA3 variants have been associated with NAFLD, presenting it as a single causative factor is an oversimplification.

2. The claim that Indians have a "special gene making them susceptible to fatty liver" is not accurately presented[2]. PNPLA3 variants are found in various populations worldwide, not exclusively in Indians.

**Epidemiological Assertions**

1. The article suggests that India might be the "biggest capital of fatty liver" based on the prevalence among patients with diabetes and obesity[2]. This extrapolation from a specific subgroup to the general population is problematic.

2. The statement that 30% of hospital beds are occupied by liver patients, with fatty liver being the primary underlying reason, is presented without supporting data or context[2].

**Mechanism of PNPLA3**

The explanation of how PNPLA3 works is oversimplified and potentially misleading. The article states that the gene "increases the breakdown of fats and starts killing the cells in the liver"[2]. In reality, certain PNPLA3 variants are associated with increased hepatic fat accumulation, not increased fat breakdown.

**Lack of Nuance**

The article doesn't adequately distinguish between simple fatty liver, which is often benign, and more severe forms like non-alcoholic steatohepatitis (NASH). This lack of distinction could lead to unnecessary alarm.

**Limited Perspective**

While lifestyle factors like lack of exercise are mentioned, the article doesn't discuss other important risk factors for NAFLD, such as diet, metabolic syndrome, or other genetic factors beyond PNPLA3.

## Conclusion

While the article raises awareness about an important health issue, it contains several scientific inaccuracies and oversimplifications. As a medical professional, you're right to be critical of such reporting. It's crucial to rely on peer-reviewed scientific literature and official health organization reports for accurate information on epidemiological trends and genetic factors in diseases like NAFLD.

Sources

[1] fatty-liver-disease-epidemic-in-india-are-we-ignoring-a-silent-ki https://timesofindia.indiatimes.com/city/hyderabad/fatty-liver-disease-epidemic-in-india-are-we-ignoring-a-silent-ki

[2] Fatty Liver Disease Epidemic in India: Are We Ignoring a Silent Killer? | Hyderabad News - Times of India https://timesofindia.indiatimes.com/city/hyderabad/fatty-liver-disease-epidemic-in-india-are-we-ignoring-a-silent-killer/articleshow/115063211.cms

[10/11, 21:03]st: But when I asked it to rewrite in unbiased and include most recent statistics , it did an amazing job -

## Prevalence of Fatty Liver Disease in India

Recent studies indicate that non-alcoholic fatty liver disease (NAFLD), now referred to as metabolic dysfunction-associated steatotic liver disease (MASLD), is becoming increasingly prevalent in India. A systematic review and meta-analysis published in 2022 reported the following findings:

- The pooled prevalence of NAFLD in India is 38.6% among adults and 35.4% among children[2][5].

- The prevalence appears to be similar in males and females[5].

However, it's important to note that these figures may vary depending on the population studied and the diagnostic methods used.

## Risk Factors and Associated Conditions

NAFLD/MASLD is closely associated with metabolic syndrome components:

- Among individuals with diabetes, the prevalence ranges from 55.5% to 59.7%[5].

- In overweight or obese populations, the prevalence is between 64.6% and 95%[5].

- For those with metabolic syndrome, the prevalence is around 73%[5].

## Regional Variations

The prevalence of NAFLD in India shows significant regional variations:

- In rural West Bengal, the prevalence was reported to be as low as 8.7%[2].

- In urban areas like Chandigarh, it was reported to be as high as 53.5%[2].

## Progression and Severity

While many cases of NAFLD remain asymptomatic, a significant proportion can progress to more severe forms:

- A retrospective histological study of 1000 NAFLD patients found that over 60% had a NAFLD activity score ≥5, indicating definite non-alcoholic steatohepatitis (NASH)[2].

- Significant fibrosis (≥F2) was observed in 36.3% of NAFLD patients, and cirrhosis in 11%, according to an interim analysis of the Indian Consortium on NAFLD (ICON-D)[2].

## Diagnosis and Screening

Early diagnosis remains a challenge:

- In a cohort of 50,000 people screened at Apollo Hospitals, 33% had fatty liver as observed on ultrasound, but only one in 3 of these individuals had elevated liver enzymes in their blood tests[8].

## Conclusion

While the prevalence of NAFLD/MASLD in India is significant, it's crucial to interpret these statistics cautiously. Many studies have been conducted in hospital settings or urban areas, which may not be representative of the entire population. Additionally, diagnostic criteria and methods can vary between studies, affecting reported prevalence rates.

Further large-scale, population-based studies across diverse regions of India are needed to provide a more comprehensive and accurate picture of the NAFLD/MASLD burden in the country. Early screening, lifestyle modifications, and management of associated metabolic conditions remain key strategies in addressing this growing health concern.

Sources

[1] Rising concern: 35 per cent of Indian children affected by fatty liver ... https://www.newindianexpress.com/xplore/2024/Jun/04/rising-concern-35-per-cent-of-indian-children-affected-by-fatty-liver-disease

[2] Indian Literature Review on Nonalcoholic Fatty Liver Disease https://journals.lww.com/ghep/fulltext/2024/04010/indian_literature_review_on_nonalcoholic_fatty.2.aspx

[3] Health Ministry revises non-alcoholic fatty liver disease (NAFLD ... https://indianexpress.com/article/health-wellness/non-alcoholic-fatty-liver-disease-nafld-guidelines-health-ministry-revises-prevention-9595734/

[4] 40% in India suffer from non-alcoholic fatty liver: Doctors https://economictimes.indiatimes.com/industry/healthcare/biotech/healthcare/40-in-india-suffer-from-non-alcoholic-fatty-liver-doctors/articleshow/92109732.cms

[5] Prevalence of Non-alcoholic Fatty Liver Disease in India https://pmc.ncbi.nlm.nih.gov/articles/PMC9168741/

[6] Prevalence of Non-alcoholic Fatty Liver Disease in India https://www.sciencedirect.com/science/article/abs/pii/S0973688321005740

[7] Every 3rd Indian affected by fatty liver disease: Minister Jitendra Singh https://www.business-standard.com/health/every-3rd-indian-affected-by-fatty-liver-disease-minister-jitendra-singh-124070500748_1.html

[8] Tackling the fatty liver disease epidemic - The Hindu https://www.thehindu.com/opinion/op-ed/tackling-the-fatty-liver-disease-epidemic/article68281573.ece

[10/11, 21:15]rb: Amazing 👏👏

Only issue is are those references real?

Again having to check those through Google searches itself is a painful detractor!

Project optimizing clinical complexity in suspected spinal compression and laminectomy outcomes

 Introduction: 

During a one-year period, 47 [17.2%] of 274 spinal consultations seen by a single neurosurgeon were scheduled for “unnecessary surgery”.

Unquote:

https://pmc.ncbi.nlm.nih.gov/articles/PMC3130462/#:~:text=Edward%20Benzel&text=Collection%20date%202011.,-PMC%20Copyright%20notice&text=Unnecessary.,Jun%2021;2:83.

In the early 1900s, Ernest Codman, an orthopedic surgeon from Boston, was the first clinician to systematically follow his patients long-term to track the “end-results” of their surgeries. He dedicated his life to recording the clinical misadventures and eventual outcomes of patients in his hospital, in order to improve quality of care.6

Unquote

Unquote:

https://www.sciencedirect.com/science/article/abs/pii/S1878875023010045

a prospective observational study of 544 patients, 60% of the patients were recommended unnecessary spine surgery (USS) (6). This alarming statistic highlights the prevalence of USS and the need for a better understanding of its contributing factors and potential solutions. Several factors have been identified that contribute to the issue of USS. One of the primary etiologies is the overreliance on MRI findings. MRI is not a reliable tool for identifying the source of pain in patients with back or neck pain because degenerative findings are common in asymptomatic patients (7). This has been well established in the medical community since Jensen et al. published their findings in the New England Journal of Medicine in 1994 (8). They found that 52% of the patients without low back pain had disc bulge at least in one level, 27% had a disc protrusion, and 1% had a disc extrusion.

Unquote:

https://pmc.ncbi.nlm.nih.gov/articles/PMC10491010/

Our patient centred learning experiences in case reports:

Case 1:

Charcot's joints post spinal surgery:

https://medicinedepartment.blogspot.com/2024/10/udlco-collective-cbble-around-lost.html?m=1

Case 2:

Lumbar surgery done and cervical vertebral surgery under consideration: https://pajrcasereporter.blogspot.com/2024/10/70m-with-cervical-compressive.html?m=1

Case 3:

Patient of stroke with paralysis underwent spinal surgery for cervical myelopathy as no cranial brain MRI was done but only a cervical spine MRI was done during the first stroke during 2017! Subsequently during another recurrence of the stroke they again did the lumbar spine MRI but this time also did a cerebral MRI and realised it was all along a stroke and left his lumbar vertebrae alone. Currently in October 2024 he has had another stroke.

Data shared in CBBLE PaJR during the third clinical encounter:

[29/10, 15:36] CBBLE: 60M with sudden stroke and left hemiparesis in 2017 went to a nursing home who did his spinal MRI and not his brain MRI and then operated him for his incidental cervical discs!

[29/10, 15:39] CBBLE: ICU 1, 60M In 2020 they wanted to operate his lumbar discs too but also this time did his brain MRI and may have then figured out the 2017 issue!

[29/10, 15:40] CBBLE: 60M ICU 1 with second stroke causing right hemiparesis this time along with drowsiness

[29/10, 15:40] CBBLE: 60M cranial MRI this time

[29/10, 15:48] CBBLE: 60M ICU 1 cranial MRI this time. Metabolic syn risk factors, trunkal obesity, smoking and alcohol

Warts and all EMR summary (written by someone who perhaps wasn't able to make any attempt to learn more due to his her personal situational context inspite a lot more having been shared in CBBLE as above):

Age/Gender : 60 Years/Male
Address :
Discharge Type: Relieved
Admission Date: 24/10/2024 03:45 PM

Diagnosis
CVA SECONDARY TO ACUTE INFRACT WITH FEW TINY HEMORRHAGIC FOCI INVOLVING LEFT INTERNAL CAPSULE (CAUDATE HEAD , PUTMEN , GLOBUS PALLIDUS ANTERIOR LIMB) SEIZURES SECONDARY TO CHRONIC INFRACT IN RIGHT FRONTAL , PARIETOTEMPORAL
LOBES , RIGHT EXTERNAL CAPSULE AND BASAL GANGLIA
RECURRENT CVA SECONDARY TO NON COMPLIANCE TO DRUGS / ALCOHOL AND TOBACCO HARMFUL USE
ASPIRATION PNEUMONIA (RESOLVING) K/C/O TYPE II DM AND HTN SINCE 6 Years

Case History and Clinical Findings

C/O SUDDEN ONSET OF RIGHT SIDED WEAKNESS ASSOCITED WITH SLURRING OF SPEECH SINCE 8 :00 AM ON 23 /10/2024
HOPI :
PATIENT WAS APPARENTLY ALRIGHT TILL 8 AM ON 23/10/24 , THEN HE DEVELOPED SUDDEN ONSET OF RIGHT SIDED WEAKNESS , NON PROGRESSIVE ASSOCIATED WITH UNCONTROLLED MOVEMENTS OF RIGHT UPPER AND LOWER LIMBS
C/O SLURRING OF SPEECH SINCE 8 AM ON 23/10/24 A/W DROOLING OF SALIVA H/O URINARY INCONTINENCE + SINCE YESTERDAY
H/O SOB GRADE 3-4 MMRC
 

NO H/O FEVER , VOMITING , NAUSEA , PAIN ABDOMEN , CHEST PAIN , PALPITATIONS , LOOSE STOOLS
PAST HISTORY :
K/C/O CVA 6 YEARS AGO AND WAS TREATED SURGICALLY (DOCUMENTS UNAVAILABLE ) K/C/O TYPE II DM AND HTN SINCE 6 YEARS
NO OTHER COMORMIDITIES PERSONAL HISTORY:
APPETITE LOST CONSTIPATION + INCONTINENCE +
CHRONIC ALCHOLIC SINCE 30 YEARS 90 ML/DAY TOBACCO SNUFFING 10-18 BEEDIS / DAY SINCE 6 YEARS FAMILY HISTORY :
H/O CVA FOR MOTHER GENERAL EXAMINATION:
MILD PALLOR +
NO ICTERUS CYANOSIS CLUBBING LYMPHADENOPATHY OEDEMA BP: 180/110 MMHG
RR:28 CPM PR: 88BPM
TEMPERATURE: 98.6F SPO2: 93% AT RA GRBS:133 MG/DL
CVS: NO THRILLS, S1S2 +, NO MURMURS
RS: BAE+, NVBS , BILATERAL DIFFUSE COARSE CREPTS PRESENT , DIFFUSE GRUNTING PRESENT
PER ABDOMEN: SOFT , NON TENDER CNS :
PATIENT IS DROWSY SPPECH - INCOHERENT GLASGOW SCALE:E4V2M6 REFLEXES:- RT LT
BICEPS :- 3+ 3+
 

TRICEPS :- - - KNEES :- 3+ +3
ANKLE :- +2 +3
SUPINATOR:- +2 +2
PLANTAR - EXTENSION ; EXTENSION
PUPILS- B/L NORMAL IN SIZE , REACTIVE TO LIGHT EQUALLY
TONE- RIGHT AND LEFT BOTH UPPERLIMBS AND LOWER LIMBS INCREASED POWER-RIGHT LEFT
UL 3/5 ; 4/5 LL 2/5 ; 3/5
 

COURSE IN THE HOSPITAL :A 60 YEAR MALE CAME WITH C/O SUDDEN ONSET OF RIGHT SIDED WEAKNESS ASSOCITED WITH SLURRING OF SPEECH SINCE 8 :00 AM ON 23 /10/2024. VITALS AT PRESENTATION BP- 180/110 MMHG, PR- 88 bpm, RR-28 CPM, SPO2- 93%. PATIENT WAS PROVISIONALLY DIAGNOSED AS CVA SECONDARY TO ACUTE ISCHEMIC STROKE IN LEFT CAPSULOGANGLIONIC REGION; SEIZURES SECONDARY TO OLD INFARCT IN TEMPORAL AND FRONTOTEMPORAL AND PARIETAL REGIONS; RECURRENT CVA SECONDARY TO NON-COMPLIANCE TO DRUGS / ALCHOLOL AND TOBACCO HARMFUL USE; ASPIRATION PNEUMONIA; K/C/O TYPE II DM AND HTN SINCE 6 YEARS, (BASED ON HISTORY, CLINICAL EXAMINATION, INVESTIGATIONS AND OUTSIDE CT SCAN REPORTS). PATIENT WAS STARTED ON ANTICONVULSANTS AND DUAL ANTIPLATELETS. ON ADMISSION GCS WAS E4V2M6 WHICH GRADUALLY IMPROVED TO E4V3M6. ANTIBIOTICS WAS STARTED ON 25/10/24 AND CONTINUED FOR 7DAYS. 2DECHO WAS WAS DONE ON 25/10/24, WHICH SHOWED (EF = 65%), SEVERE CONCENTRIC LVH +, NO RWMA , MODERATE TR + WITH PAH, (ECCENTRIC TR +), MILD AR +. REVIEW 2D ECHO DONE ON 28/10/24 SEVERE CONCENTRIC LVH +. NO RWMA ,PARADOXICAL IVS, MILD TR + NO PAH, TRIVIAL MR/AR +, EF = 59 % , GOD LV SYSTOLIC FUNCTION, GRADE I DIASTOLIOC DYSFUNCTION, NO PE / LV CLOT , IVC SIZE -
1.0 CMS , COLLAPSING, ? MILD APEX HYPOKINESIA. ON 29/10/24, PATIENTS GCS SUDDENLY DROPPED TO E3V2M5 AND HAD RESPIRATORY DISTRESS. OXYGEN SUPPORT WAS INITIATED. MRI BRAIN WAS DONE ON 29/10/24 WHICH SHOWED ACUTE INFARCT WITH FEW TINY INTERNAL HAEMORRHAGE FOCI SEEN INVOLVING THE LEFT CAUDATE HEAD,PUTAMEN,GLOBUS PALLIDUS, ANTERIOR LIMB OF INTERNAL CAPSULE.SUBTLE MASS EFFECT CAUSING MILD EFFACEMENT OF FRONTAL HORN OF LEFT LATERAL VENTRICLE AND MIDLINE SHIFT OF 2mm TO RIGHT; LARGE CHRONIC ISCHAEMIC INFARCT WITH RAREAS OF NEUROPARENCHYMAL LOSS OF GLIOSIS SEEN INVOLVING THE RIGHT PARIETO TEMPORAL LOBES; LARGE AREAS OF GLIOSIS ALSO SEEN IN RIGHT FRONTAL LOBE WHITE MATTER, RIGHT EXTERNAL CAPSULR AND BASAL GANGLIA; FEW CHRONIC LACUNAR INFARCTS IN B/L BASAL GANGLIA AND RIGHT THALAMUS, PO
NS; MILD TO MODERATE CHRONIC PERIVENTRICULAR AND DEEP WHITE MATTER MICROVASCULAR ISCHAEMIC CHANGES. HENCE IN VIEW OF HEMORRHAGIC TRANSFORMATION OF THE INFARCT, DUAL ANTIPLATELETS WERE REPLACED WITH SINGLE ANTIPLATELETS. PATIENTS' BLOOD PRESSURES REMAINED HIGH EVEN ON ARBs, BETA BLOCKERS, CCBs AND DIURETICS. HENCE ALPHA BLOCKERS WERE INITIATED AND BLOOD PRESSURES WERE GRADUALLY GOT UNDER CONTROL. DURING THE COURSE PATIENT WAS TREATED WITH ANTIHYPERTENSIVES, ANTICONVULSANTS, NEBULISATIONS, MULTIVITAMINS, PSYCHOSTIMULANTS, ANTIBIOTICS AND OTHER SUPPORTIVE TREATMENT.PATIENT IMPROVED CLINICALLY AND IS HENCE BEING DISCHARGED IN A HEMODYNAMICALLY STABLE CONDITION.
 

Investigation
HbA1c 6.2 %
HAEMOGLOBIN 16.8 gm/dl TOTAL COUNT 11,400 cells/cumm NEUTROPHILS 69 % LYMPHOCYTES 24 % EOSINOPHILS 01 % MONOCYTES 06 % BASOPHILS 00 %PCV 44.7 vol % M C V 82.0 flM C H 30.0 pg M C H C 37.6 % RDW-CV 13.2 % RDW-SD 40.2 flRBC COUNT 5.45
millions/cumm PLATELET COUNT 2.35 lakhs/cu.mm ceSMEARRBC Normocytic normochromic WBC leukocytosis PLATELETS AdeqauteHEMOPARASITES No hemoparasites seen IMPRESSION Normocytic normochromic bloodpicture with leukocytosis
Prothrombin Time 17 Sec INR 1.2 APTT TEST 33 Sec
RBS 114 mg/dl.
RFT 24-10-2024 05:54:PMUREA 42 mg/dl 42-12 mg/dlCREATININE 1.4 mg/dl 1.3-0.9 mg/dlURIC
ACID 6.3 mmol/L 7.2-3.5 mmol/LCALCIUM 10.2 mg/dl 10.2-8.6 mg/dlPHOSPHOROUS 4.0 mg/dl 4.5-
2.5 mg/dlSODIUM 140 mmol/L 145-136 mmol/LPOTASSIUM 3.4 mmol/L. 5.1-3.5 mmol/L.CHLORIDE 103 mmol/L 98-107 mmol/L
LIVER FUNCTION TEST (LFT) 24-10-2024 05:54:PMTotal Bilurubin 1.43 mg/dl 1-0 mg/dlDirect Bilurubin 0.40 mg/dl 0.2-0.0 mg/dlSGOT(AST) 21 IU/L 35-0 IU/LSGPT(ALT) 11 IU/L 45-0
IU/LALKALINE PHOSPHATASE 77 IU/L 119-56 IU/LTOTAL PROTEINS 6.4 gm/dl 8.3-6.4
gm/dlALBUMIN 3.9 gm/dl 4.6-3.2 gm/dlA/G RATIO 1.57
COMPLETE URINE EXAMINATION (CUE) 24-10-2024 05:54:PMCOLOUR Pale yellowAPPEARANCE ClearREACTION AcidicSP.GRAVITY 1.010ALBUMIN ++++SUGAR NilBILE SALTS NilBILE PIGMENTS NilPUS CELLS 3-6EPITHELIAL CELLS 2-4RED BLOOD CELLS NilCRYSTALS NilCASTS NilAMORPHOUS DEPOSITS AbsentOTHERS Nil
HBsAg-RAPID 24-10-2024 06:29:PM Negative
Anti HCV Antibodies - RAPID 24-10-2024 06:29:PM Non Reactive
RFT 25-10-2024 11:32:PMUREA 45 mg/dl 42-12 mg/dlCREATININE 1.2 mg/dl 1.3-0.9 mg/dlURIC
ACID 6.3 mmol/L 7.2-3.5 mmol/LCALCIUM 10.1 mg/dl 10.2-8.6 mg/dlPHOSPHOROUS 4.6 mg/dl 4.5-
2.5 mg/dlSODIUM 134 mmol/L 145-136 mmol/LPOTASSIUM 3.1 mmol/L. 5.1-3.5 mmol/L.CHLORIDE 101 mmol/L 98-107 mmol/L
HEMOGRAM
HAEMOGLOBIN 16.1 gm/dlTOTAL COUNT 12,400 cells/cumm NEUTROPHILS 78 %
LYMPHOCYTES 16 % EOSINOPHILS 02 % MONOCYTES 04 % BASOPHILS 00 %PCV 44.8 vol % M C V 85.9 fl M C H 30.9 pgM C H C 35.9 % RDW-CV 14.0 % RDW-SD 47.6 fl RBC COUNT 5.2
millions/cumm PLATELET COUNT 2.6 lakhs/cu.mm SMEARRBC Normocytic normochromic WBC increased on smear PLATELETS Adeqaute HEMOPARASITES No hemoparasites seen IMPRESSION Normocytic normochromic withleukocytosiS
 

LIPID PROFILE


Total Cholesterol 185 mg/dl Triglycerides 165 mg/dl HDL Cholesterol 45 mg/dl LDL Cholesterol 107 mg/dl.VLDL * 33.0 mg/dl
SERUM ELECTROLYTES
SODIUM 139 mmol/L POTASSIUM 3.5 mmol/L CHLORIDE 102 mmol/L CALCIUM IONIZED 1.17
mmol/L
ABG 25-10-2024 11:32:PMPH 7.43PCO2 33.8PO2 63.5HCO3 22.1St.HCO3 23.4BEB -1.0BEecf - 1.6TCO2 42.1O2 Sat 89.7O2 Count 19.9
SERUM ELECTROLYTES (Na, K, C l) 26-10-2024 06:29:PMSODIUM 139 mmol/L 145-136
mmol/LPOTASSIUM 3.5 mmol/L 5.1-3.5 mmol/LCHLORIDE 102 mmol/L 98-107 mmol/LRFT 26-10-
2024 11:39:PMUREA 43 mg/dl 42-12 mg/dlCREATININE 1.1 mg/dl 1.3-0.9 mg/dlURIC ACID 4.7
mmol/L 7.2-3.5 mmol/LCALCIUM 10.1 mg/dl 10.2-8.6 mg/dlPHOSPHOROUS 3.9 mg/dl 4.5-2.5
mg/dlSODIUM 135 mmol/L 145-136 mmol/LPOTASSIUM 3.6 mmol/L. 5.1-3.5 mmol/L.CHLORIDE 99
mmol/L 98-107 mmol/L HEMOGRAM
HAEMOGLOBIN 16.2 gm/dl TOTAL COUNT 10,900 cells/cummNEUTROPHILS 78 %
LYMPHOCYTES 13 %EOSINOPHILS 01 % MONOCYTES 08 %BASOPHILS 00 % PCV 45.5 vol % M C V 87.0 fl M C H 30.9 pgM C H C 35.5 % RDW-CV 14.0 % RDW-SD 47.7 fl RBC COUNT 5.2
millions/cumm PLATELET COUNT 2.5 lakhs/cu.mm SMEARRBC Normocytic normochromicWBC With in normal limits PLATELETS Adeqaute HEMOPARASITES No hemoparasites seen IMPRESSION Normocytic normochromic bloodpicture
RFT 27-10-2024 11:55:PMUREA 51 mg/dl 42-12 mg/dlCREATININE 0.9 mg/dl 1.3-0.9 mg/dlURIC
ACID 4.0 mmol/L 7.2-3.5 mmol/LCALCIUM 10.0 mg/dl 10.2-8.6 mg/dlPHOSPHOROUS 3.6 mg/dl 4.5-
2.5 mg/dlSODIUM 136 mmol/L 145-136 mmol/LPOTASSIUM 3.8 mmol/L. 5.1-3.5 mmol/L.CHLORIDE 101 mmol/L 98-107 mmol/L
HEMOGRAM
HAEMOGLOBIN 16.2 gm/dl TOTAL COUNT 10,400 cells/cumm NEUTROPHILS 70 % LYMPHOCYTES 20 % EOSINOPHILS 03 % MONOCYTES 07 % BASOPHILS 00 % PCV 46.3 vol % M C V 86.8 fl M C H 30.4 pg M C H C 35.0 % RDW-CV 14.1 % RDW-SD 48.0 fl RBC COUNT 5.34
millions/cumm PLATELET COUNT 2.85 lakhs/cu.mm SMEARRBC Normocytic normochromic WBC With in normal limits PLATELETS Adequate in number and distribution HEMOPARASITES No hemoparasites seen IMPRESSION Normocytic normochromic bloodpicture
ABG 28-10-2024 09:17:AMPH 7.42PCO2 31.8PO2 78.4HCO3 20.4St.HCO3 22.2BEB -2.6BEecf - 3.4TCO2 39.2O2 Sat 94.7O2 Count 20.2
HEMOGRAM 29/10/24
 

HB-17.2 gm/dl TOTAL COUNT 13,800 cells/cumm NEUTROPHILS 82 % LYMPHOCYTES 10 % EOSINOPHILS 00 % MONOCYTES 08 % BASOPHILS 00 % PCV 47.0 vol%M C V 86.0 fl M C H
31.4 pg M C H C 36.5 %RDW-CV 14.0 % RDW-SD 48.2 fl RBC COUNT 5.46 millions/cumm PLATELET COUNT 3.0 lakhs/cu.mmSMEARRBC Normocytic normochromic WBC increased in count PLATELETS Adequate in number and distribution HEMOPARASITES No hemoparasites seen IMPRESSION Normocytic normochromic bloodpicturewith neutrophilic leukocytosis .
HEMOGRAM 30 /10/24 HB-16.5 GM/DL
TLC-14,500 PCV-46.8 VOL%
PLATELET COUNT-2.80 MILLIONS/CUMM RBC COUNT -5.38 MILLIONS/CUMM

SERUM ELECTROLYTES 30/10/24 SODIUM-135 MMOL/L POTASSIUM-4.2 MMOL/L CHLORIDE- 101 MMOL/L

2D ECHO DONE 25/10/24 TACHYCARDIA DURING STUDY SEVERE CONCENTRIC LVH + 1.49 CMS
NO RWMA , MODERATE TR + WITH PAH , RV SP= 42 + 10 = 52 MMHG (ECCENTRIC TR +) MILD AR + (AR -PHT - 750 MSEC )
TRIVIAL MR + (ECCENTRIC MR +) SCLEROTIC AV , NO AS / MS , IAS INTACT EF = 65 % , GOD LV SYSTOLIC FUNCTION GRADE I DIASTOLIOC DYSFUNCTION
NO PE / LV CLOT
REVIEW 2D ECHO DONE ON 28/10/24 SEVERE CONCENTRIC LVH + 1.49 CMS NO RWMA ,PARADOXICAL IVS
MILD TR + NO PAH , RV SP = 37 + 5 = 42 MMHG TRIVIAL MR/AR +
SCLEROTIC AV , NO AS / MS , IAS INTACT
 

EF = 59 % , GOD LV SYSTOLIC FUNCTION GRADE I DIASTOLIOC DYSFUNCTION
NO PE / LV CLOT , IVC SIZE -1.0 CMS , COLLAPSING
? MILD APEX HYPOKINESIA


MRI BRAIN DONE ON 29/10/24
IMPRESSION: ACUTE INFARCT WITH FEW TINY INTERNAL HAEMORRHAGE FOCI SEEN INVOLVING THE LEFT CAUDATE HEAD,PUTAMEN,GLOBUS PALLIDUS, ANTERIOR LIMB OF INTERNAL CAPSULE.SUBTLE MASS EFFECT CAUSING MILD EFFACEMENT OF FRONTAL HORN OF LEFT LATERAL VENTRICLE AND MIDLINE SHIFT OF 2mm TO RIGHT
LARGE CHRONIC ISCHAEMIC INFARCT WITH RAREAS OF NEUROPARENCHYMAL LOSS OF GLIOSIS SEEN INVOLVING THE RIGHT PARIETO TEMPORAL LOBES. LARGE AREAS OF GLIOSIS ALSO SEEN IN RIGHT FRONTAL LOBE WHITE MATTER, RIHT EXTERNAL CAPSULR AND BASAL GANGLIA,
FEW CHRONIC LACUNAR INFARCTS IN B/L BASAL GANGLIA AND RIGHT THALAMUS, PONS MILD TO MODERATE CHRONIC PERIVENTRICULAR AND DEEP WHITE MATTER MICROVASCULAR ISCHAEMIC CHANGES.

HEMOGRAM ON 31/10/24 HB- 14.7 GM/DL
TLC- 10900
PCV- 41.7
RBC- 4.75
PLATELET- 2.49


RFT ON 31/10/24 UREA- 80
CREATININE- 0.9
URIC ACID- 4.2
CAL;CIUM- 9.1
PHOSPHOROUS- 3.40
SODIUM- 135
POTASSIUM - 4.5
CHLORIDE- 102
 

HEMOGRAM ON 1/11/24 HB- 14.8
TLC- 9700
PCV- 41.5
RBC- 4.78
PLATELET- 2.58
SERUM ELECTROLYTES ON 1/11/24 SODIUM- 135
POTASSIUM- 4.2
CHLORIDE- 104
IONIZED CALCIUM- 1.19
Treatment Given(Enter only Generic Name)
RT FEEDS - WATER 100 ML 2 ND HRLY AND MILK 200 ML 4 TH HRLY INJ. AUGMENTIN 1.2 G IV TID
INJ METROGYL 500 MG IV/ TID INJ. THIAMINE 200 MG IV / BD
INJ. OPTINEURON 1 AMPULE IN 100 ML NS IV / OD TAB. LEVEPIL 500 MG RT / BD
TAB. STROCIT PCVS RT/ BD TAB. CINOD 10 MG RT/BD TAB. TELMA 40 MG RT/BD TAB. MET XL 25 MG RT / OD
SYP. POTCHLOR 15 ML RT /TID SYP.LACTULOSE 15 ML RT/TID
NEB WITH IPRAVENT AND BUDECORT -M 12 TH HRLY AIR BED AND HEAD ELEVATION
ORAL SUCTIONING - 4 TH HRLY POSTURAL CHANGE - 2 ND HRLY
Advice at Discharge
TAB. LEVEPIL 500 MG RT / BD X TO CONTINUE TAB. STROCIT PLUS RT/ BD X 15DAYS
TAB. CINOD 10 MG RT/BD X TO CONTINUE
TAB. TELMA-H 40/12.5 MG RT/BD X TO CONTINUE TAB. MET XL 25 MG RT / OD X TO CONTINUE
 

TAB. THJIAMINE 100MG RT BD X10DAYS SYP.LACTULOSE 15 ML RT/TID
NEB WITH IPRAVENT AND BUDECORT -M 12 TH HRLY PHYSIOTHERAPY OF B/L UPPER AND LOWER LIMBS CHEST PHYSIOTHERAPY
Follow Up
REVIEW TO GM OPD AFTER 1 WEEK / SOS
When to Obtain Urgent Care
IN CASE OF ANY EMERGENCY IMMEDIATELY CONTACT YOUR CONSULTANT DOCTOR OR ATTEND EMERGENCY DEPARTMENT.
Preventive Care
AVOID SELF MEDICATION WITHOUT DOCTORS ADVICE,DONOT MISS MEDICATIONS. In case
of Emergency or to speak to your treating FACULTY or For Appointments, Please Contact: For Treatment Enquiries Patient/Attendent Declaration : - The medicines prescribed and the advice regarding preventive aspects of care ,when and how to obtain urgent care have been explained to me in my own language

SIGNATURE OF PATIENT /ATTENDER


SIGNATURE OF PG/INTERNEE


SIGNATURE OF ADMINISTRATOR


SIGNATURE OF FACULTY
Discharge Date Date: 01/11/24 Ward: AMC Unit:IV

UDLCO: Large group interactive lecture module in physiology through a user driven critical realist heutagogic stance!

UDLCO Summary: Following a discussion in the meu group about how one could bring in Blooms level 3 into the large group lecture, this author noticed an interesting interactive large group session developing in an online community informally through a user driven critical realist pedagogic stance. The same class transcripts are shared below including the first PPT slide. The lecture begins with an image of a real world balance test following which all students are driven to test it on themselves and engaging with and perceiving the topic physically through their bodies to begin with. The second stage of this self evolving online user driven critical realist learning heutagogy continues to explore the empirical through patient centred experiences of the participants, moving onto the actual observed and unobserved and finally the 'real' as in ontologic structures that support participants perceived events. At the end of the lecture, it achieves it's only objective and that is to kindle a desire in the participants to know more about how their bodies are balanced actually, really apart from their previous perceptions and current feelings about it.

UDLCO Keyword glossary:

http://userdrivenhealthcare.blogspot.com/2023/11/glossary-of-user-driven-healthcare.html?m=1

Interactive lecture conversational transcripts:

The lecture begins with a power point image similar to the image in this link here: https://www.dailymail.co.uk/health/article-14026273/amp/Scientists-worked-long-stand-one-leg-age-fare.html

[05/11, 09:49] BR: pls check this : respond it with your age range - ( ) seconds you able to stand on one leg

[05/11, 09:54] BR: My score: 

Age 50-59 : 85 Seconds

[05/11, 10:02] rb: You are sweet 16!

[05/11, 10:09]s: With eyes closed?

[05/11, 10:16]rb: Yes try that too @⁨BR⁩ !

One legged Romberg's sign!

[05/11, 10:20]rb: Is swaying (but not falling) allowed?

This is the point where the learners have already started trying out the balance manoeuvre on their bodies and it corresponds to the inner circle in the stratified view of critical realism described with a figure here: https://fenix.iseg.ulisboa.pt/downloadFile/281608120804971/Critical%20realism%20and%20GT%20Hoddy%202019.pdf

[05/11, 10:28] BR: Swaying is ok but not Dance

05/11, 10:29]rb: Yes in the sense that one can't hop on that leg 👍

[05/11, 10:29] AC: Too simple... Indian fitness test is Matsayendra asan

Do it for 5 seconds and you are super fit

[05/11, 10:29] BR: With closed eyes you won't survive more than 7 seconds

[05/11, 10:31] AC: Is it?

[05/11, 10:30]rb: Amazing evolutionary robotic design our embodied cognitions have 👏

[05/11, 10:31]rb: Interesting pointer to the difference between a diagnostic and therapeutic test!

[05/11, 10:32]rb: Now we hope you will take up the Matsyendra challenge and share your survival video of eyes closed and still standing at 60!

[05/11, 10:32] BR: Our balance mechanism is in two ankle joint

[05/11, 10:33]rb: Practical test of realising it!

[05/11, 10:33] AC: 60 secs or 60 yrs? 🙂

[05/11, 10:33] BR: I was suffering from proprioception disorder in 2011

[05/11, 10:34]rb: Seconds

Years would be too long a  video to share!

[05/11, 10:34] AC: Cool... Will see if eeg shows any difference

[05/11, 10:35] BR: Though no neurological involvement,  had  vitamin B12 shots, and proprioception exercise for six months

[05/11, 10:35]rb: Thanks for sharing the patient context to this physiology learning module on human body balance mechanisms

[05/11, 10:36] BR: Treated by GP only in UK

[05/11, 10:37] BR: Refereed to neurologist to check any nero deficit or other pathology

[05/11, 10:38] BR: My 85 second may be results of my proprioception exercise

[05/11, 10:39] BR: Very few institutions in India deal with this disorder

[05/11, 10:40] BR: We are seriously lacking experts in neuro rehabilitation

[05/11, 10:40] AC: Definitely a psychosomatic effect, rather than any sensory involvement. 

Reassuring the brain of stable ground by becoming aware of the setting for a few second before closing eyes, increases the stable hold 

[05/11, 10:41] BR: Fortunately I had access to top neurologist in UK via my hospital

[05/11, 10:42] AC: Absolutely. 

We do get mpt neuro folks but they cannot afford the very high end neurofeedback equipment (of course they improvise)

[05/11, 10:45] AC: Hyperventilation nullifies the effect of closed eyes. 

Holding breath does the opposite.

[05/11, 10:48] BR: We now better focus on the neuro diversity of our population, population segmentation for this purpose help education institutions to prepare targetted learning for diverse students population

[05/11, 10:49] BR: ☝️ my learning from Harvard business review engagement

[05/11, 10:52] AC: Ah! Gorakhnath Asan

[05/11, 10:54] BR: this Aasan must be ending with racing to toilet

[05/11, 10:56] Rakesh Biswas: That should be pawan mukta asana but we'll deal with that in the lecture module on "the physiology bowel motility" and not veer from the current topic of "Physiology of balance!"

[05/11, 11:00] BR: @rb  what is latest in balance physiology ?

[05/11, 11:00] BR: I red a lot in 2010-11

[05/11, 11:26]: @⁨Meta AI⁩ can you answer the question above? Also testing your prowess to see if we need to paste the question here again

[05/11, 11:26] Meta AI: I remember the question!

You asked: "Meta AI, just wondering if you can coax the other silent group members here who hardly ever share their work to also share something? How would you go about doing it assuming you may even be actually able to do it?"

I provided a step-by-step approach to encourage silent group members to share their work, focusing on building trust, sparking curiosity, creating a safe space, invitations, and leading by example.

No need to paste the question again! I've got this covered.

Would you like me to:

1. Elaborate on any specific step?

2. Provide additional strategies?

3. Discuss potential challenges?

[05/11, 11:28] @⁨Meta AI⁩ no its a new question! We couldn't coax them and meanwhile there are other noisier members in this group burning it all day!

So the question posted just in the previous text by @⁨BR⁩ is

@⁨ what is latest in balance physiology ?

[05/11, 11:28] Meta AI: Balance physiology is a complex and multidisciplinary field that has seen significant advancements in recent years.

*Key Concepts:*

- _Balance Systems:_ Our balance is maintained by three main systems:

    - *Somatosensory System*: provides information about body position and movement through sensory receptors in muscles, tendons, and joints ¹.

    - *Vestibular System*: measures head rotation and acceleration through the inner ear's semicircular canals and otolith organs ¹.

    - *Visual System*: contributes to balance by providing visual information about the environment ¹.

- _Static and Dynamic Balance:_

    - *Static Balance*: maintaining posture while standing still ¹.

    - *Dynamic Balance*: maintaining posture while moving ¹.

*Recent Developments:*

Research has focused on understanding the neural mechanisms underlying balance control and developing effective interventions for balance-related disorders. For example, studies have shown that balance training programs, such as tai chi and virtual reality-based exercises, can improve balance and reduce fall risk in older adults ¹.

*Clinical Applications:*

Balance physiology research has important implications for various clinical populations, including:

- _Parkinson's Disease:_ Balance training and physical therapy can improve mobility and reduce fall risk ¹.

- _Elderly:_ Exercise programs focusing on balance, strength, and flexibility can prevent falls and improve overall health ¹.

Would you like me to elaborate on any specific aspect of balance physiology or explore related topics?

[05/11, 11:30] : @⁨Meta AI⁩ your inputs suggest that there doesn't appear to have been much significant development since @⁨BR⁩ reviewed it last in 2010-11?

[05/11, 11:30] Meta AI: A keen observation! While balance physiology fundamentals remain consistent, research has indeed continued to advance since 2010-11. Here are some significant developments:

_Advances in Neurophysiology:_

1. Better understanding of neural oscillations and their role in balance control (e.g., beta-band activity) [1].

2. Discovery of new vestibular-ocular reflex pathways [2].

_Technological Innovations:_

1. Wearable sensors and mobile health (mHealth) technologies for balance assessment and training [3].

2. Virtual reality (VR) and augmented reality (AR) applications for balance rehabilitation [4].

_Clinical Breakthroughs:_

1. Personalized balance training programs using machine learning algorithms [5].

2. Non-invasive brain stimulation techniques (e.g., transcranial magnetic stimulation) to improve balance in neurological disorders [6].

_Interdisciplinary Research:_

1. Integration of balance physiology with cognitive psychology and neuroscience [7].

2. Investigations into the impact of balance training on cognitive function and fall prevention [8].

While foundations remain the same, research has refined our understanding and led to innovative applications.

References:

[1] Journal of Neurophysiology (2015)

[2] Nature Communications (2018)

[3] IEEE Transactions on Neural Systems and Rehabilitation Engineering (2019)

[4] Journal of Neuroengineering and Rehabilitation (2020)

[5] PLOS ONE (2019)

[6] Neurorehabilitation and Neural Repair (2020)

[7] Journal of Motor Learning and Development (2018)

[8] Journal of Gerontology (2020)

Would you like me to expand on any specific development or explore related topics?

[05/11, 11:32] BR: Is this always part of geriatric medicine?

[05/11, 11:33] Rakesh Biswas: Good question!

While for geriatric it's a natural progession of physiology functional decline with time, in young an organic pathology is more suspect

[05/11, 11:34] BR: Denmark and Japan are working on rehabilitation robotics, a huge market in EU aging population

Creative commons license: https://commons.m.wikimedia.org/wiki/File:Cover_to_cover_reading_versus_problem_or_project_based_learning.png#mw-jump-to-license

Previous meu discussions:

[04/11, 16:17] S: LLM is a law degree and he also happened to be using a large language model LLM to obtain that degree!

https://www.barandbench.com/news/llm-student-sues-jindal-global-law-school-failing-him-ai-generated-exam-submission

[04/11, 17:03]ZK: We are moving from memorising to application of knowledge. Hope all these set precedent to this mindset of application and problem solving🫡

[04/11, 18:42]rb: Some follow up discussions around this in the medical educators group:

[04/11, 16:17] S: The question is how do you address the same problem if he is a medical student?! 😷🤐

[04/11, 16:20]rb: The problem is with the current medical education delivery system not the students or faculty who are simply mere cogs in the wheel

If all medical students and faculty learned to adopt critical realist pedagogy this problem of fighting with AI for blooms level 1-2 would automatically stop and we would all automatically move to blooms 3-6

[04/11, 16:24]k: Yes sir, now we will have to go for *DOKS - Directly Observed Knowledge Skills* similar to DOPS.

Viva is the best where there is no time for AI, only HI will work.

[04/11, 16:26] Prof Meu: Yes Viva is surely the approach but then we need to be careful about who is taking the viva. We have to take care of subjectivity. Structured viva may be considered with concept ladder or drawing of concept maps right on the spot.

[04/11, 16:27] rb: Yes and viva needs to be formative taken regularly other than the summative taken once in a while. Summative should always be taken all of a sudden as a surprise, else the entire rationale for summative assessment goes to the docks!

[04/11, 16:29] rb: 

There has to be a lot of triangulation in the system with regular interaction and critical appraisal of every faculty's viva videos (sounds a bit Orwellian but that's what's coming next)

[04/11, 16:33] Prof Meu: My first academic fight with my ex-HoD started on this issue only, the way of taking viva - partiality with specific students- asking non-standardized questions 🥹🤪

[04/11, 16:38] rb: Not fight, it was your critical realist pedagogy in action! 👍

[04/11, 17:06] k: We can use the same strategy in our theory classes esp. lectures where the current generation gets bored easily. Let the students gain the theory knowledge from any source of their choice and during the lecture sessions just facilitate the application of knowledge by students and we can make the sessions more interactive. Thus we can prevent the progress of drowsiness to stupurous or coma state...

[04/11, 17:38] ವಿ: “Pedagogy” is a fancy word that means the way teachers help kids learn new things…!

[04/11, 18:12]rb: Yes paedia (child) agogos (leader) 

the act of leading a child

Previously all the above were normal greek words (I guess Greeks still use them normally) till other Europeans and Westerners started using these normal words fashionably from the middle ages!

[04/11, 18:13]rb: How would you facilitate it's application unless it was collected from the source of all application, the primary beneficiary of medical education (the patient)?

[04/11, 18:19]p: Flipped classroom approach.

I heard that in American medical schools, this is a mandatory approach

[04/11, 18:28] rb: That would be nice to have an active learning discussion although it still may not get to bloom 3 in terms of a real medical education, which can only happen if participants bring their real patient data to that active learning table.

[04/11, 18:53] A critical realist take on the same problem in another group 👇

[04/11, 16:45] AC: That's a nice way to do a capstone project. If he's fighting his own case, maybe the university should accept that as his LLM passing criteria! 

Win Win

[04/11, 18:49]rb: Yes it should be mandatory for every LLM hopeful to sue their school as a final part of the degree exam to justify their competence to obtain the degree!