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Quademic 2025: Hospitals in the United States are dealing with a surge in patients admission, the reason is the quademic it is dealing with at this moment. This has led to an influx of patients. It is all caused by seasonal infections, including common flu, Covid-19, and respiratory syncytial virus (RSV) that dominate the winter season in the US. This year, norovirus also joined the list, which has further increased the load on the healthcare.
The healthcare company founded in academics M Health Fairview, confirmed that their hospitals are overflowing due to the quademic.
The hospitals of M Health Fairview's volume is up by 30% and as a results, patients are being treated in the hallways and in alternative care areas. There is also a longer wait time and shortages for resources that are required to treat these emergencies. This has also impacted other life-threatening emergencies like heart attacks and strokes, as the healthcare resources and caregivers are occupied with the surge in seasonal cases.
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Common cold and flu: The common cold and influenza (flu) are perhaps the most well-known illnesses that peak during the fall. As temperatures drop and humidity levels fluctuate, viruses that cause colds and the flu become more active. The flu, in particular, can be more severe than a common cold, leading to complications such as pneumonia, especially in vulnerable populations like the elderly and those with pre-existing health conditions. Symptoms include a runny nose, sore throat, coughing, fever, and body aches.
Covid-19: As per the World Health Organization, Coronavirus disease or COVID-19 is an infectious disease caused by the SARS-CoV-2 virus. Most people infected with this virus will experience mild to moderate respiratory illness and recover without requiring special treatment, However, there could be some cases of seriously ill patients who may require medical attention. It is also because of the other existing medical conditions like cardiovascular diseases, diabetes, chronic respiratory diseases, cancers, or older age.
The best way to protect against this virus is by following social isolation form those who are infected, using mask to prevent droplets from infecting others when you cough or sneeze and to wash your hands for 20 seconds frequently.
RSV or Respiratory Syncytial Virus: As per the Centers of Diseases Control and Prevention (CDC), RSV is a common respiratory virus that infects nose, throat and lungs. Though symptoms are similar to the viruses like flu or COVID-19, the disease in itself is different. It also peaks during the winter season, especially between December and January.
However, the main difference between RSV and other respiratory illness, above mentioned is that RSV can cause pneumonia or bronchiolitis, especially for those who are over the age of 50 or with an existing heart or lung disease.
Norovirus: It is a number 1 cause of foodborne illness in the US and this happens when virus gets into the food and then it accidentally enters your mouth. These particles are from faeces or vomit from infected people, or can be transmitted via contaminated food and water. It could also spread by touching unclean surfaces like door handles or cutlery.
For most people, having norovirus is unpleasant, but mild and recovery could be made in 1 to 2 days. However, it could be more serious for babies, older people and anyone with any existing health condition.
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Alcohol-attributable cancer deaths in the US doubled between 1990 and 2023, according to a study published in The Lancet Regional Health – Americas.
Using more than three decades of Global Burden of Disease data, researchers found that annual alcohol-attributable cancer deaths rose from 11,361 in 1990 to 23,126 in 2023.
Men and adults aged 55 and older experienced the greatest burden, but increases were seen across most cancer types, age groups and regions.
Among older men, liver cancer accounted for the highest alcohol-attributable mortality rates, followed by esophageal and colorectal cancers. Among women, breast cancer represented the leading source of alcohol-attributable cancer mortality.
The study also identified concerning patterns among younger adults. For men aged 20 to 54, colorectal cancer was the leading alcohol-attributable cause of cancer death. Among women in the same age group, breast cancer ranked first, followed by colorectal cancer.
“Notably, among adults aged 20 to 54, colorectal cancer was the leading cause of alcohol-attributable cancer mortality in men and the second leading cause in women, surpassing liver cancer in both groups,” Jani said.
While it is commonly known that alcohol damages the liver, the new study highlights that its impact extends beyond liver cancer, with growing burdens from colorectal, breast, esophageal, pancreatic and other cancers.
Alcohol has long been recognized as a Group 1 carcinogen by the International Agency for Research on Cancer, in the same category as tobacco smoke and asbestos. Scientific evidence links alcohol consumption to cancers of the breast, liver, esophagus, colorectum and several head and neck sites.
“The most surprising finding was the breadth of alcohol’s potential impact across cancer types,” said Chinmay Jani, chief fellow in hematology and oncology at Sylvester Comprehensive Cancer Center, part of the University of Miami Miller School of Medicine.
“Although its relationship with liver cancer is widely recognized, its contribution to cancers such as colorectal, esophageal, breast, pancreatic and prostate cancer is less well understood by the public.”
Gilberto Lopes, chief of the Division of Medical Oncology at Sylvester, said the findings reinforce the importance of giving people clear information about lifestyle factors that influence cancer risk.
“What this study makes clear is that alcohol-related cancer risk is not limited to one disease or one group of people,” Lopes said. “As physicians and cancer researchers, we have an opportunity to help patients understand that alcohol is a modifiable risk factor and that even small, informed changes can be part of a broader strategy to reduce cancer risk in our community.”
Despite increasing scientific evidence, public awareness of the alcohol-cancer connection remains relatively low compared with awareness of other risk factors such as tobacco use.
“The most important takeaway is greater awareness that alcohol may affect cancer risk beyond the liver,” Jani said.
“These findings highlight alcohol as a potentially modifiable risk factor, and while the lowest safe dose is not yet known, this study suggests that reducing consumption to the lowest amount feasible for each individual may help lessen its impact on cancer risk and overall health.”
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While GLP-1 drugs such as Ozempic, Wegovy and Zepbound are helping with weight loss and diabetes management, men already at risk of androgenetic alopecia may face a 7% higher risk of hair loss with higher GLP-1 activity, according to a new study.
Hair thinning has been reported by both men and women using GLP-1 drugs, with researchers largely attributing the shedding to rapid weight loss associated with the medications.
However, researchers at NYU Langone Health have now identified a potential genetic link between GLP-1 activity and androgenetic alopecia, an inherited form of hair loss affecting the top and front of the scalp.
"Our study provides the first genetic link between GLP-1 use and an increased risk of male-pattern hair loss from androgenetic alopecia, an association long suspected but until now not shown scientifically," said Lynn Petukhova, assistant professor in the Department of Dermatology and the Department of Population Health at NYU Grossman School of Medicine.
Researchers used large, publicly available genetic databases, including:
The researchers compared GLP1R-related genetic data with markers associated with androgenetic alopecia. They found that genetic variants linked to naturally higher levels of GLP-1 receptor proteins were more common in men with androgenetic alopecia.
The team also adjusted the analysis for hypertension, which may affect blood flow to the scalp and hair follicle growth; and accounted for insulin resistance and lower testosterone levels.
After these adjustments, the 7% higher risk remained.
Published online in the Journal of Investigative Dermatology, the findings suggest that GLP-1 activity and male-pattern hair loss may share a biological link.
The findings could eventually help identify people who may be more vulnerable to hair loss before they are prescribed GLP-1 medications.
"Our findings suggest that, if future experiments prove successful, some men, and possibly women too, could be screened and benchmarked for their risk of hair loss before being prescribed GLP-1 medications," Petukhova said.
The researchers also suggested that some GLP-1 users could potentially receive combination treatments to prevent hair loss, such as minoxidil or another drug.
However, more research is needed to understand how GLP-1 activity may affect hair follicle growth. Petukhova also plans to investigate whether the genetic link seen in men applies to women.
Hair shedding has been reported among GLP-1 users and has been linked by researchers to rapid weight loss.
In many cases, hair growth resumes several months after weight stabilizes.
The new findings add a potential genetic explanation to these reports, but further research is needed to establish the underlying biological mechanism.
What Is Androgenetic alopecia?
Androgenetic alopecia is a common form of hair loss that becomes more likely with age. It can begin as early as the teenage years and affects both men and women, with hair loss in women most commonly observed after menopause.
Surveys suggest that 12% of Americans have used GLP-1 drugs specifically for weight loss, including one-fifth of women aged 50 to 64. Since Ozempic was approved by the US Food and Drug Administration in 2020, prescriptions for the medication have more than tripled.
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Researchers from the Indian Institute of Technology Madras (IIT Madras) and Christian Medical College (CMC), Vellore, have developed three artificial intelligence (AI)-based tools designed to help detect and assess kidney diseases earlier.
The technologies could help doctors identify kidney conditions more quickly, analyse medical images more consistently and assess the extent of kidney tumours in greater detail.
The team developed three complementary technologies:
Together, the tools have been designed to support clinicians in detecting kidney disease and assessing its severity.
Kidney diseases can remain asymptomatic during their early stages and may go undetected until significant damage has occurred.
The researchers say their AI-based tools could assist physicians by providing rapid and consistent analysis, potentially supporting earlier diagnosis and more informed treatment decisions.
“The team aimed to develop intelligent systems that would help clinicians make quicker and more informed decisions. We used machine learning along with clinical knowledge to develop tools that would assist in the earlier detection of kidney diseases and give more detailed information specific to the patient,” said Prof. G.L. Samuel, Department of Mechanical Engineering, IIT Madras, in a statement.
The CT image classifier was trained using more than 12,000 images and can distinguish between healthy kidneys, cysts, stones and tumours.
The researchers also developed a 3D imaging framework using open-source software to measure tumour burden.
According to the team, the approach offers an inexpensive and repeatable way to assess the extent of a tumour, which could provide additional information for treatment planning.
The CKD prediction model was implemented as a user-friendly prototype interface with the aim of facilitating future clinical translation. The team also worked on improving the model's accuracy and interpretability for doctors.
“Early detection is of paramount importance when dealing with kidney diseases; these AI tools can help detect at-risk patients early and plan their treatment more effectively. The patient-specific imaging framework is of significant promise as it goes beyond the standard measurements to give a more comprehensive picture of the extent of the disease,” said Jennifer Delighta, Research Scholar, IIT Madras.
The research could also contribute to the development of a kidney Digital Twin — a technology that combines AI-assisted image analysis with patient-specific 3D anatomical models.
Such virtual models could eventually help researchers and clinicians monitor disease progression, forecast changes and support more personalized treatment planning.
However, the technologies are still being developed. The researchers plan to test the models using additional patient datasets to validate their performance and establish partnerships with healthcare institutions for potential real-world deployment.
The team is also exploring the long-term integration of these AI technologies with minimally invasive wearable sensing systems and Digital Twin platforms for personalised kidney health monitoring.
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