Narasimha Rao retweeted
Replying to @harryfisherEMTP
Hi Harry.
I’m a Pediatrician who is nowhere related to the US healthcare system.
I’m based out of India.
Rest assured - I have zero conflict of interest.
I saw this tweet on my timeline and Whatever I’m going to say - it’s out of sheer goodwill. Nothing else.
I understand vaccine hesitancy.
That’s your wish and that has to be respected.
With regards to VIT K - the IM injection has near zero side effects and it protects the children against something called hemorrhagic disease of newborn.
I have seen one case in my residency (VIT K injection in India is near universal) and it’s one of the most horrific deaths I witnessed. The child had not recieved VIT K. The levels were low and death was 100% due to its deficiency and not getting the injection.
The side effects being mentioned in comments I.e. allergic reactions are known to occur in Adults (not seen in children) and IV route (not IM) and very very rare.
The other side effect I see mentioned (jaundice) - was know to occur in old formulations of VIT K - not current used ones.
It’s one of the safest things with only upside and zero downside.
Please get it.
I myself had a kid last year in November. He got the Vit K injection.
He is perfectly healthy.
I wish you and your family the best and Congratulations on becoming a father.
Narasimha Rao retweeted
As someone who did some web development before AI, I would STRONGLY caution medical folks who vibe code something to resist the temptation to try to turn their app into a paid service. If…
NEW READ FROM CNN
Development and Internal Validation of a Neonatal Outcomes Prediction Score and Model for Neonates at 22-29 Weeks’ Gestation on Postnatal Days 7, 14, and 28 - @Sciencedirect
doi.org/10.1016/j.jpeds.2026…
Outcome Probability Calculator: canadianneonatalnetwork.org/…
Narasimha Rao retweeted
I resigned from Anthropic today. I spent the last three years doing pretraining research at both OpenAI and Anthropic. Neither company is acting responsibly. They are racing straight to self-improving superintelligence and gambling with our lives. More thoughts below.
Narasimha Rao retweeted
👶💙 ¡Gran noticia para la #Neonatología y para nuestros recién nacidos más vulnerables!
🏥El Hospital Universitario 12 de Octubre está desarrollando mascarillas nasales personalizadas mediante tecnología 3D para bebés prematuros de muy bajo peso👏🏻👏🏻
🔗europapress.es/madrid/notici…
Narasimha Rao retweeted
This Friday, free registration! Thanks to
@Neofocus_UK and Dr. @JWLYong for the kind invitation!
Please register using this Zoom link . us06web.zoom.us/webinar/regi…
A certificate of attendance will be provided once feedback has been completed
❤️#POCUS in #NICU
Narasimha Rao retweeted
This is an attention grabber. Intact cord resuscitation (ICR) reduced absolute mortality rate by about 14% compared to 30-60sec DCC. But the details matter... @EBNEO @NeonatologyJC @NeoAnup @neosatyan link.springer.com/article/10…
Narasimha Rao retweeted
Check out this lineup for the Dr. Giesinger Clinical Cardiopulmonary Physiology for the Care of the Sick Newborn course!
Dates: Nov 2-5, 2026
Register today!
👉iowa-cardiopulmonary-physiol…
Narasimha Rao retweeted
AI alone will provide better medical care than physicians, or even physicians working with AI.
AI will likely be ready to be deployed for real-world cognitive medical tasks in some, maybe many, workflows by 2030. Now is the time for leadership to develop workflows and regulation.
Read more in @JAMA_current with @vkhosla, @nealkhosla, and @AbeBakerButler.
jamanetwork.com/journals/jam…
Narasimha Rao retweeted
Interested in learning Neonatal Lung Ultrasound?
Join us for a comprehensive Neonatal Lung Ultrasound Course & Hands-on Workshop in Birmingham on Monday, 19 October 2026.
Please register using the link below 👇
wmcn.event-booking.org.uk/ev…
Narasimha Rao retweeted
The #JAMA article on #QualityImprovement, one of the iconic Users Guides to the Medical literature, provides a framework for evaluating the validity and clinical impact of quality improvement (#QI) research.
pubmed.ncbi.nlm.nih.gov/2109…
Narasimha Rao retweeted
How do you manage hsPDA in extremely preterm infants?
Help shape the next international clinical trial by completing our 10-minute anonymous survey on managing infants ≤26+6 weeks' gestation who remain ventilated beyond 7 days.
📝 redcap.link/xbat6kgq
@CardioNeo @souvik_neo
Please share with colleagues!
or complete it here: wix.to/YqQ7YMQ
#Neonatology #PDA #NICU #Prematurity #ClinicalTrials #Research4Babies
@PASMeeting @EBNEO @NeoVent_Py @SMHcriticalcare @Penn_CRS @American_Heart @rescuresearch @WeAreCanadiEM @Rescudoc @JENS_Congress @UENPS_Congress
@MFNM_Congress @HotTopicsNeo @Nemours @NANTtweets @NewbornToolkit @NeoToday
@criticalevels @CritCareSociety @ERC_resus @IofPHC @CPSupportCanada @MostPremBabies @NeoTECaN @NeoHeartSociety @ResusCouncilUK @ARC_resus @CprRound
@CCCTG_ @CCIRNet @Ilcor_org @NZResusCouncil @CCCForum @AlbanianArc @HealthySim @SimulationBb @onesimeducation @SIHonline @NewbornBrains @HealthcareSSI @HeartandStroke
@Newborn_PHM @neonatalinsider @NeoProvence
Narasimha Rao retweeted
Opinion paper from Thomas Hegyi @RutgersU @RWJUH. Arguing for a fetoneonatology fellowship. A specialty to bridge the gap between MFM and neonatology, caring for the same patient - the baby - just at different times. My thoughts🧵@EBNEO @nicupodcast nature.com/articles/s41372-0…
Narasimha Rao retweeted
#138
A huge Swedish registry study on newborn vitamin K prophylaxis and infant bleeding,
In @JAMAPediatrics, Published Online: July 13, 2026.
Simatou et al, Karolinska Institutet. Grab your coffee, this one has 2 million babies in it.
#JournalClub #PedsID
jamanetwork.com/journals/jam…
Narasimha Rao retweeted
Curated list of research papers on agentic AI for healthcare
github.com/AgenticHealthAI/A…
Archimedes
In preterm neonates, does extending non-invasive respiratory support beyond ventilatory needs improve growth?
Several papers out there to help: 4 RCT, 3 cohorts
adc.bmj.com/content/early/20…
Narasimha Rao retweeted
CRP -a story we all live daily (but rarely understand)
Today I asked my student:
“What is CRP? What is its normal function?”
He said confidently: “Sir, it’s an acute-phase reactant. It increases in infection.”
Then I asked:
“What do you mean by acute-phase reactant?”
He paused… thinking… stuck.
And honestly-most of us would also pause if we had to explain it properly.
Because we order CRP every day to “see inflammation”…
…but many of us don’t know CRP’s real identity.
So let’s see. 👇
First: why the name C-reactive?
Because CRP was discovered as a serum factor that reacted with the “C-polysaccharide” of pneumococcus during acute infection.
Second: what is CRP, conceptually?
CRP is a pattern recognition receptor (PRR)—but unlike TLR/CLR (membrane) or RLR (cytosolic)…
👉 CRP is a soluble, secreted PRR that patrols from the bloodstream.
What does this “soluble PRR” recognize?
Signals of danger: microbes + damaged self.
CRP binds targets like phosphorylcholine on microbes and on apoptotic/necrotic membranes—basically, “this needs cleanup.”
Then CRP does the work:
🧹 Opsonization (tags for phagocytosis)
🧩 Classical complement activation (via C1q)
➡️ Better clearance of debris & immune complexes.
Now the clinical beauty: CRP kinetics.
CRP is made fast—rises by ~6 hours, peaks around ~48 hours after a stimulus.
The golden fact most people miss:
CRP has a constant half-life ~19 hours (in health and disease).
So the CRP value mainly reflects how much the liver is producing, i.e., inflammatory drive.
So when should you repeat CRP?
If you want the repeat to mean something, match biology:
✅ Repeat in 24–48 hours to judge trend/response (rise/peak/fall dynamics).
When is repeating too early?
<12 hours usually adds noise, not insight—CRP hasn’t had time to change meaningfully given its kinetics and half-life.
CRP isn’t just “an acute phase reactant.”
It’s a secreted PRR + complement-linking opsonin + a real-time reporter of inflammatory production.
We order it daily.
It’s worth knowing what it really does.
👉 #MedTwitter #RheumTwitter #Immunology #CRP #ClinicalPearls #MedEd @DrAkhilX @IhabFathiSulima @CelestinoGutirr @Urchilla01 @schowardjd
Narasimha Rao retweeted
Delighted on publication in Archives of diseases of Childhood on review of evidence for ‘Use of NIV to support growth in preterm neonates’ on last day of 2025! @ADC_BMJ @EBNEO
Thanks to my co-authors Johanna Baker & @polythenia for collaboration.
doi.org/10.1136/archdischild…
Narasimha Rao retweeted
Holy shit… University of Alberta just solved one of AI’s biggest healthcare problems 🤯
They built a framework called Reason2Decide that makes medical AI actually explain its decisions, not hallucinate rationales after the fact.
And It works with models 40x smaller than GPT-4.
Here’s why this matters for clinical AI 👇
Models are trained to explain “correct” answers.
But in real use, they must explain their OWN predictions, which can be wrong.
This mismatch is called exposure bias.
It’s why explanations often don’t match decisions.
Doctors notice. Trust breaks.
The solution is Reason2Decide.
A two-stage training framework:
Stage 1: Teach the model how to explain medical decisions.
Stage 2: Gradually shift from explaining gold-standard answers to explaining its own predictions.
The model learns to be honest, not just confident.
The clever mechanism is called Task-Level Scheduled Sampling.
During training:
• Start with 0% self-predictions
• Gradually ramp to 90%
• Never hit 100% to avoid error amplification
The model literally learns to explain itself.
he results on real clinical data are wild.
Clinical triage with 170k+ real nurse notes:
T5-Large + Reason2Decide
• 60.58 F1
• Beat all fine-tuning baselines
• Beat Qwen-3-32B with a model 40× smaller
On PubMedQA:
• 60.28 F1
• 96% accuracy
Prediction alone isn’t enough.
The explanations must actually align.
Reason2Decide scored highest on:
• BERTScore (semantic similarity)
• BLEU (surface quality)
• LLM-as-Judge correctness
When the model said “Go to ED now,” the rationale actually justified it.
Here’s the surprising part.
Stage 1 used only LLM-generated rationales.
No human-written explanations.
Result?
It still outperformed models trained on human rationales.
Synthetic explanations can replace expensive human annotations in medical AI.
Why this matters for healthcare AI:
Trust: Doctors can verify the reasoning.
Safety: Misaligned explanations get caught.
Cost: 40x smaller models are deployable in hospitals.
Scale: Works with synthetic training data.
Explainable AI that actually explains.
The limitation they openly admit: “All predictions and rationales are decision-support tools and require human verification.”
This is the right mindset.
Augment clinicians.
Don’t replace them.
What Reason2Decide proves:
• Small models can beat foundation models
• Explanations can match predictions
• Synthetic rationales can work
• Real clinical deployment is possible
Paper: “Reason2Decide: Rationale-Driven Multi-Task Learning”
Hasan et al., University of Alberta
Narasimha Rao retweeted
Everyone is missing what this study actually says to parents.
The graph shows two paths to the same destination. The yellow line (early specialization) gets there faster in the early years. The blue line (multi-disciplinary) gets there slower but breaks through to world-class.
The key insight: individuals who perform best at a young age are usually not the same people who later reach the world-class level.
This came from 34,839 top performers across four domains: Nobel laureates, Olympic medalists, elite chess players, and renowned classical composers.
The researchers found three consistent patterns.
First, the best kids and the best adults are mostly different people.
Second, future world-class performers showed gradual development and weren’t among the best in their age group.
Third, they didn’t specialize early but engaged in multiple disciplines.
The research team proposes three mechanisms that explain why breadth beats depth.
The search-and-match hypothesis suggests that exposure to multiple disciplines increases the likelihood of eventually finding the best personal fit.
The enhanced-learning-capital hypothesis proposes that learning in diverse areas strengthens overall learning capacity, making it easier to continue improving later at the highest level within a chosen field.
The limited-risks hypothesis argues that engaging in multiple disciplines reduces the chance of setbacks such as burnout, unhealthy work-rest imbalances, loss of motivation, or physical injury.
That third one matters enormously. Specialized athletes are 2.25 times more likely to get overuse injuries than multi-sport athletes. The American Academy of Pediatrics, AOSSM, and American Medical Society for Sports Medicine all recommend against early specialization before age 15 for most sports.
The lead researcher, Arne Güllich from RPTU University Kaiserslautern-Landau, puts it bluntly: “Don’t specialize in just one discipline too early. Encourage young people by providing opportunities to pursue different areas of interest, and support development in two or three disciplines.”
The two or three disciplines don’t need to be related. Language and mathematics. Philosophy and geography. The researchers cite Einstein pursuing physics and violin.
The connection between domains seems to build cognitive infrastructure that pure depth cannot replicate.
Here’s what makes this uncomfortable for parents. The early specialization path produces visible results faster. Your kid looks better at age 10. They make the travel team. They win the tournament. The graphs cross and diverge later, around peak performance age, when the multi-disciplinary kids start pulling ahead.
The entire youth talent ecosystem runs on selecting early performers and accelerating them. Travel leagues, elite academies, showcase tournaments. Every incentive pushes toward specialization.
But the research shows this system is optimizing for the wrong metric.
It produces great 14-year-olds, not great 24-year-olds.
The practical takeaway: let your kid play three sports until at least middle school.
Let them quit the piano and try drums. Let them be mediocre at several things instead of great at one thing. The data says this approach produces both more elite performers and fewer burnout casualties.
The hardest part is watching other kids pass yours on the yellow line while trusting the blue line catches up.





























