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AI’s Context Dependence, Keep Benching, and TARTAN-HF By Viktor Zarev, Virginia Hunt
August 24, 2026
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Together with
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“If you’re a physician sitting across from a patient and you hear this: “My LLM suspects I have XYZ diagnosis based on these symptoms, labs, and so on…” What is your reaction?”
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Christina Farr
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A recent JAMA study suggested AI will replace doctors by 2035, but its authors might want to consider the individuality of every patient and every physician on the planet before making such claims. Today’s top story is a reminder why.
Thanks for reading,
Vik
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With all the talk of AI outperforming and replacing doctors, a new JACC study reminds us – AI diagnostic algorithms don’t perform great when applied to populations different from the ones they’re trained on.
- The algorithm in question is Pathway Labs’ EchoNext, an AI-ECG model trained on multicenter hospital data for detecting structural heart disease (SHD).
- EchoNext launched in June to mixed reception. The New York Times wrote a positive piece about the problem it solves, while some cardiologists called it unnecessary.
What better way to address the critics than with real world data? EchoNext was applied to patients from PREVUE-VALVE, a community-based study of adults aged 65-85 who underwent in-home ECG and echo.
But the details of those participants’ disease matters and they looked fundamentally different from EchoNext’s training data.
- SHD prevalence in the real-world community participants was just 8% versus 43% in the hospital training data.
- The community-based patients’ SHD also presented as less severe.
- Moderate tricuspid regurgitation was more common in these participants than the usual systolic heart failure from the hospital patient group.
With those differences in mind, it’s no wonder EchoNext showed a drop in diagnostic performance among community-based patients.
- Model discrimination fell to an AUC of 71% compared to 83% in the hospital.
- Adjusting for differences in prevalence and case mix narrowed but didn’t close that gap.
- But, AUC did rise to 79% in participants with an abnormal ECG.
- It also reached 76% among patients with worse health status.
In the context of EchoNext’s potential applications, these results are still decent (though an AUC > 80% is preferred for clinical reliability).
There’s a lesson to be learned here, and it goes beyond this one model.
- AI algorithms can only be as good as the data they’re trained on, especially since they lack the intuition of human doctors.
The Takeaway
Diagnostic AI is an eventuality in medicine, but that doesn’t mean that it’ll be perfectly reliable for every patient or population. Rather, physicians encountering and eventually using tools like EchoNext will still need to rely on their gut and experience, no matter AI’s utility.
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- NOACs for AFib and AD: Non-vitamin K oral anticoagulants deter dementia in AFib patients, and an EHJ study revealed they may boost brain health for AFib patients with Alzheimer’s disease. Among 7.3k patients, NOAC users had 0.23- and 0.21-point improvements on the 30-point MMSE tests compared to non-users and warfarin users, respectively. When NOACs went head-to-head with warfarin, NOAC use yielded ~20 percentage point decreases in stroke risk and major bleeding, alongside small reductions in mortality and fracture.
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- Bempedoic Acid’s Benefits Continue: No statins, no problem. Bempedoic acid showed it not only offers cardioprotective benefits for statin-intolerant patients with PAD, it also protects patients’ limbs. Among 1.6k patients, bempedoic acid reduced total major adverse limb events by 45% and resulted in 29% fewer occurrences of CV-related deaths or MALE. Interestingly, bempedoic acid treatment also showed big benefits for patients without PAD, lowering their risk of CV-related deaths or MALE by 18%.
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- Heart Failure Cost Savings: Hello Heart announced a study showing that its AI-driven heart health program was associated with lower costs and hospital use among HF patients. Comparing 292 participants against matched controls, researchers found that those enrolled in the CV self-management program saw a $7,000 reduction in total medical spend per participant on average. This came alongside 47 fewer inpatient admissions and 297 fewer inpatient days per 100 participants. That’s notable since the less HF patients hospitalized, the lower the strain on health systems.
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- Federal Funding for Stroke Robots: The HHS’ ARPA-H awarded Siemens Healthineers up to $31.1M over five years to develop autonomous remote endovascular robotics. While it sounds like sci-fi, the idea is to let robots perform mechanical thrombectomy for acute ischemic stroke without direct human input. Siemens also committed to $5.4M in cost sharing, bringing the project’s total investment to $36.5M. Stryker is a sub-awardee on the contract, building on the two companies’ stroke care partnership that began a year ago.
- Clash of the HCM Titans: Cytokinetics is suing Bristol Myers Squibb to defend patents covering its newly launched heart drug Myqorzo. The suit alleges that BMS obtained a patent that applies to a method of treating HCM that includes the active ingredient in Cytokinetics’ Myqorzo. It is curious how BMS obtained such a patent considering that Cytokinetics says the company had “zero involvement” in Myqorzo’s development. The patent litigation will certainly slow Cytokinetics’ attempts to secure market share with its HCM drug, despite Myqorzo’s potentially superior efficacy.
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Heart Failure Places Enormous Strain on our Healthcare Systems and Patients
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