Experiencing daytime sleepiness is something that is usually perceived as a minor inconvenience, but for older adults, it could be an early warning sign of Dementia. This neurodegenerative disease leads to the progressive decline of brain cells. This eventually

affects memory, cognition, and personality, making everyday tasks more difficult. As one of the fastest-growing neurological disorders across the world, dementia poses a significant health threat to ageing populations.

Is Dementia Linked To Poor Sleep?

For this study, researchers followed 445 older adults (average age 76) over three years, aiming to determine whether poor sleep could increase the risk of mild cognitive impairment (MCI), which often leads to dementia. At the start, none of the participants had MCI, but by the end of the study, 36 individuals had developed the condition.

The researchers discovered that participants with poor sleep were more likely to develop MCI compared to those who slept well. However, when depression symptoms were taken into account, the link between poor sleep and MCI became less pronounced, suggesting that while sleep issues are a concern, mental health also plays a key role in dementia risk.

To assess sleep quality, the Pittsburgh Sleep Quality Index (PSQI) was used, evaluating factors such as sleep duration, disturbances, and daytime alertness. Among these, "daytime dysfunction"—defined as excessive sleepiness and low energy during the day—was most strongly associated with an increased risk of MCI. Those experiencing daytime dysfunction were more than three times as likely to develop MCI as those who didn’t report such symptoms.

There are many types of dementia:

Dementia is not a specific disease. According to the Centers for Disease Control and Prevention (CDC), it is an overall term that describes a decline in mental ability that interferes with daily life. People with dementia often have symptoms like trouble remembering, thinking, or making everyday decisions. These symptoms tend to get worse over time.

Alzheimer’s disease is the most common type of dementia, and it mostly affects the elderly. Each form of dementia has a different cause. Though dementia mostly affects older adults, it is not a part of normal ageing. An estimated 6.7 million older adults have Alzheimer's disease in the United States. That number is expected to double by 2060, as per data from the CDC.

In 2022, 3.8% of men and 4.2% women in US were diagnosed with dementia. The percentage of people increase with age from 1.7% for those aged 65-74 to 13.1% for those aged 85 and older. Alzheimer's accounts for 60 to 80% of all dementia cases and it is most prevalent in California, Florida, and Texas, as these states have the highest number of people.

Myocardial infarction (MI) is one of the most common cardiovascular disorders, with an estimated prevalence of 3.8% in individuals aged less than 60 years and 9.5% in those aged over 60 years. MI remains a leading cause of death and is a significant public health concern worldwide.

But a heart attack isn't one single disease with one single mechanism. Being able to classify the type of myocardial infarction quickly can improve diagnosis and treatment.

In view of this, four major cardiac societies—the European Society of Cardiology (ESC), the American College of Cardiology (ACC), the American Heart Association (AHA) and the World Heart Federation (WHF)—have jointly launched the Fifth Universal Definition of Myocardial Infarction.

The Fifth Universal Definition of Myocardial Infarction replaces numerical labels with three clinically meaningful categories.

The new approach aims to help healthcare professionals make more consistent diagnoses and enable patients to understand their condition better.

The new definition also aligns with the International Classification of Diseases (ICD) coding, which captures statistics on the extent, causes and consequences of different diseases.

“People may think of an MI as a heart attack caused by a blocked coronary artery but there are many different causes of MI,” explained ESC Chair, Professor Nicholas Mills from the University of Edinburgh, UK.

“The previous universal definition used a numerical system to categorize the different types of MI but this was not always easy to apply in clinical practice, leading to inconsistencies in diagnosis and treatment. The ESC, ACC, AHA and WHF have worked together to devise an updated and simplified classification system for MI, which aims to address these limitations.”

What Does the Fifth UDMI Mean?

The Fifth Universal Definition of Myocardial Infarction updates the classification to better reflect underlying pathophysiology, align with the clinical evaluation of patients, and incorporate objective diagnostic criteria.

Notably, it could facilitate wider study of less common mechanisms of primary MI, such as spontaneous coronary artery dissection (SCAD), a condition occurring predominantly in women that is currently underdiagnosed.

What Are the 3 New Heart Attack Categories?

The new system considers the underlying cause of MI and aligns the diagnosis with established approaches to clinical evaluation. It recognises that MI occurs in three clinical settings: primary MI, secondary MI and procedure-related MI.

In this updated approach to MI classification, all MIs fit into one of these three clinical categories, and the new document outlines the diagnostic tests and investigations required for each.

1. Primary MI

Primary MI arises spontaneously due to an acute problem in a coronary artery. It is most commonly caused by a rupture of an atherosclerotic plaque, but there are other causes, such as a tear in the coronary wall (spontaneous coronary artery dissection [SCAD]), spasm or a clot.

2. Secondary MI

Secondary MI arises from an imbalance in oxygen supply and demand in the heart caused by another condition, such as very high or very low blood pressure or a very fast heartbeat.

3. Procedure-Related MI

The third setting—procedure-related MI—is one that occurs within 30 days of a cardiac procedure, such as coronary stenting, or a heart operation, such as coronary artery bypass surgery.

“Clinicians often do not use the previous numerical terminology—e.g. type 2 or type 4c—in patient discussions as it is rather complex. With the new approach, we can now talk with patients about the cause of their MI so that they can understand their condition and recognize why the next steps, such as further tests and treatments, are needed,” said ACC/AHA Chair, Professor Kristin Newby from Duke University Medical Center, Durham, US.

A new artificial intelligence tool could turn a routine heart test into an effective early warning system for serious cardiac emergencies. Doctors have developed an AI tool for analysing an electrocardiogram (ECG). It could study ECG in less than two seconds and identify signs of heart valve disease that may not be visible to the trained human eye.

Developed by researchers at Imperial College London, the AI tool was trained on millions of ECGs and presented at the European Society of Cardiology Congress 2026 in Munich.

In a human trial involving around 67,000 US patients, it was able to detect signs of heart valve disease with up to an astonishing 90% accuracy and heart failure with up to 81% accuracy.

How Can An ECG Reveal A Valve Problem?

A standard ECG records the heart's electrical activity. Traditionally, it has been used to identify heart problems like irregular heart rhythms, but these electrical patterns, according to researchers, can contain signs about the heart's overall structure and function.

The AI looks for patterns across the ECG that may be too complex or subtle for a clinician to recognise visually.

That means the machine isn't simply reading the obvious peaks and dips on an ECG. It is looking for hidden patterns buried within the electrical signal.

Researchers say this could allow routine ECGs, which are already performed millions of times, to flag people who may have an underlying structural heart problem.

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AI Tool Delivered Accurate Results Within Two Seconds

The results are particularly striking for heart valve disease as the AI tool achieved accuracy of up to 90% in identifying cases.

Heart valve disease occurs when one or more of the heart's valves become narrowed or fail to close properly. This can disrupt the normal flow of blood through the heart.

Some people may have few or no symptoms initially. As the disease progresses, however, it can cause breathlessness, fatigue, chest discomfort, dizziness and swelling, and severe disease can eventually lead to heart failure.

A patient suspected of a heart emergency often requires an ECG, an ultrasound scan that allows doctors to see the heart's chambers and valves. Waiting times for such tests can be long, meaning some patients may remain undiagnosed. The AI could therefore work as a effective tool, identifying people who should be prioritised for echocardiogram.

The AI can analyse an ECG in under two seconds, compared to the much longer process of patients being referred for additional cardiac tests.

Dr Ahmed El-Medany, the British Heart Foundation clinical research fellow who led the Imperial College London analysis, described the tool as a "superhuman AI". The phrase has become shorthand for the project. He also said the next challenge is designing portable AI-based ECG readers.

Dr Sonya Babu-Narayan, consultant cardiologist and BHF clinical director, said she found it exciting to see AI deliver results from an ECG in "what feels like the blink of an eye."

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The technology is being developed as an extra layer of screening. A positive AI result would not mean that someone definitely has heart valve disease. Instead, it could signal that the patient needs a more definitive investigation, such as an echocardiogram.

Heart disease can remain hidden for years before symptoms become obvious. A routine ECG is already a familiar, relatively quick and inexpensive test. If AI can study additional data from that same test, it could help doctors in identifying people who otherwise might not have been investigated and treated further.

US President Donald Trump has announced drug pricing deals with nine more drug makers, including international pharmaceutical companies and smaller biotech firms, as part of his push to make healthcare more affordable.

Currently, US consumers pay nearly three times more for prescription medicines than people in other developed nations. Trump has been pressuring drug makers to bring the prices closer to those paid in other countries.

The latest deals, the White House said in a statement, bring the administration’s total to 26 drug makers. According to Trump, these represent 90% of the domestic pharmaceutical market, while the remaining 10% is “also coming in” and “have no choice.”

Which Companies Signed the Deals?

The latest agreements build on the administration’s broader “most favored nation” (MFN) drug pricing policy.

The White House said the nine companies are:

• Alcon
• Astellas Pharma
• BeOne Medicines
• BridgeBio
• CSL
• Kyowa Kirin
• Sun Pharma
• Teva Pharmaceuticals
• UCB

What Do the Deals Mean?

The White House said the agreements will lower prices on medicines used to treat costly chronic and rare diseases, including hemophilia, Parkinson’s disease, macular degeneration, glaucoma, liver disease, skin conditions and various cancers.

The deals give every state Medicaid program access to MFN prices on products from the nine companies, generating billions of dollars in savings.

The agreements also guarantee MFN pricing for all new innovative medicines the companies bring to market, which the administration says will prevent foreign price controls from benefiting from US pharmaceutical innovation.

$19.6 Billion US Manufacturing Investment

The nine companies have committed to investing at least $19.6 billion collectively in US manufacturing in the near term, according to the White House.

Astellas, Sun Pharma, Teva and UCB also agreed to donate active pharmaceutical ingredients to the federal government’s strategic reserve, known as SAPIR, aimed at reducing reliance on foreign supplies and preparing for emergencies.

Previous Drug Pricing Deals

Over the past year, the administration reached deals with 17 other drug makers, including Pfizer, Eli Lilly and Novo Nordisk.

Novo Nordisk and Eli Lilly reportedly agreed to price cuts in exchange for making their medicines more widely available through Medicare.

Trump also signed an executive order in May 2025 to revive the MFN policy, calling for prices to be increased outside the US and to “end global freeloading.”

The biggest savings from earlier drug pricing deals have come from weight-loss medicines.

Novo Nordisk and Eli Lilly reportedly agreed to price cuts in exchange for making their medicines more widely available through Medicare.

Will Americans Pay Less?

It remains unclear how many medicines are covered by the new deals or how large the discounts will be, making the potential savings for patients and the government difficult to determine.

The White House did not release details of the agreements, while some companies described certain terms as private. The administration and several companies said the deals will also bring future savings on innovative medicines and expand US manufacturing.

Beyond weight-loss drugs, consumer watchdog Public Citizen has questioned how much price relief Americans are actually receiving from the administration’s agreements, Reuters reported.

Medicaid already receives steep discounts from drug makers under existing law, while most Medicaid beneficiaries pay little out of pocket for prescriptions.