AI tool predicts which coronavirus patients get deadly 'wet lung'

Researchers in the US and China reported Monday they have developed an artificial intelligence tool that is able to accurately predict which newly infected patients with the novel coronavirus go on to develop severe lung disease.

Once deployed, the algorithm could assist doctors in making choices about where to prioritize care in resource-stretched health care systems, said Megan Coffee, a physician and professor at New York University's Grossman School of Medicine who co-authored a paper on the finding in the journal Computers, Materials & Continua.

The tool discovered several surprising indicators that were most strongly predictive of who went on to develop so-called acute respiratory disease syndrome (ARDS), a severe complication of the COVID-19 illness that fills the lungs with fluid and kills around 50 percent of coronavirus patients who get it.

The team applied a machine learning algorithm to data from 53 coronavirus patients across two hospitals in Wenzhou, China, finding that changes in three features -- levels of the liver enzyme alanine aminotransferase (ALT), reported body aches, and hemoglobin levels –- were most accurately predictive of subsequent, severe disease.

Using this information along with other factors, the tool was able to predict risk of ARDS with up to 80 percent accuracy.

By contrast, characteristics that were considered to be hallmarks of COVID-19, like a particular pattern in lung images called "ground glass opacity," fever, and strong immune responses, were not useful in predicting which of the patients with initially mild symptoms would get ARDS.

Neither age nor sex were useful predictors either, even though other studies have found men over 60 to be at higher risk.

"It's been fascinating because a lot of the data points that the machine used to help influence its decisions were different than what a clinician would normally look at," Coffee told AFP.

Using AI in medical settings isn't a brand new concept -- a tool already exists to help dermatologists predict which patients will go on to develop skin cancer, to give just one example.

What makes this different is that doctors are learning on the fly about COVID-19, and the tool can help steer them in the right direction, in addition to helping them decide which patients to focus on as hospitals become overwhelmed, said co-author Anasse Bari, a computer science professor at NYU.

The team is now looking to further refine the tool with data from New York and hope it is ready to deploy sometime in April. 

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Experimental AI Tool Predicts Which Patients with Pandemic Virus Will Develop Serious Respiratory Disease

An artificial intelligence tool accurately predicted which patients newly infected with the COVID-19 virus would go on to develop severe respiratory disease, a new study found.

The work was led by NYU Grossman School of Medicine and the Courant Institute of Mathematical Sciences at New York University, in partnership with Wenzhou Central Hospital and Cangnan People's Hospital, both in Wenzhou, China.

Named "SARS-CoV-2," the new virus causes the disease called "coronavirus disease 2019" or "COVID-19." As of March 30, the virus had infected 735,560 patients worldwide. According to the World Health Organization, the illness has caused more than 34,830 deaths to date, more often among older patients with underlying health conditions. The New York State Department of Health has reported more than 33,700 cases to date in New York City.

Published online March 30 in the journal Computers, Materials & Continua, the study also revealed the best indicators of future severity, and found that they were not as expected.

"While work remains to further validate our model, it holds promise as another tool to predict the patients most vulnerable to the virus, but only in support of physicians' hard-won clinical experience in treating viral infections," says corresponding study author Megan Coffee, MD, PhD, clinical assistant professor in the Division of Infectious Disease & Immunology within the Department of Medicine at NYU Grossman School of Medicine.

"Our goal was to design and deploy a decision-support tool using AI capabilities – mostly predictive analytics – to flag future clinical coronavirus severity," says co-author Anasse Bari, PhD, a clinical assistant professor in Computer Science at the Courant institute. "We hope that the tool, when fully developed, will be useful to physicians as they assess which moderately ill patients really need beds, and who can safely go home, with hospital resources stretched thin."

Surprise Predictors

For the study, demographic, laboratory, and radiological findings were collected from 53 patients as each tested positive in January 2020 for the SARS-CoV2 virus at the two Chinese hospitals. Symptoms were typically mild to begin with, including cough, fever, and stomach upset. In a minority of patients, however, severe symptoms developed with a week, including pneumonia.

The goal of the new study was to determine whether AI techniques could help to accurately predict which patients with the virus would go on to develop Acute Respiratory Distress Syndrome or ARDS, the fluid build-up in the lungs that can be fatal in the elderly.

For the new study, the researchers designed computer models that make decisions based on the data fed into them, with programs getting "smarter" the more data they consider. Specifically, the current study used decision trees that track series of decisions between options, and that model the potential consequences of choices at each step in a pathway.

The researchers were surprised to find that characteristics considered to be hallmarks of COVID-19, like certain patterns seen in lung images (e.g. ground glass opacities), fever, and strong immune responses, were not useful in predicting which of the many patients with initial, mild symptoms would go to develop severe lung disease. Neither were age and gender helpful in predicting serious disease, although past studies had found men over 60 to be at higher risk.

Instead, the new AI tool found that changes in three features – levels of the liver enzyme alanine aminotransferase (ALT), reported myalgia, and hemoglobin levels – were most accurately predictive of subsequent, severe disease. Together with other factors, the team reported being able to predict risk of ARDS with up to 80 percent accuracy.

ALT levels – which rise dramatically as diseases like hepatitis damage the liver – were only a bit higher in patients with COVID-19, researchers say, but still featured prominently in prediction of severity. In addition, deep muscle aches (myalgia) were also more commonplace, and have been linked by past research to higher general inflammation in the body.

Lastly, higher levels of hemoglobin, the iron-containing protein that enables blood cells to carry oxygen to bodily tissues, were also linked to later respiratory distress. Could this explained by other factors, like unreported smoking of tobacco, which has long been linked to increased hemoglobin levels? Of the 33 patients at Wenzhou Central Hospital interviewed on smoking status, the two who reported having smoked, also reported that they had quit.

Limitations of the study, say the authors, included the relatively small data set and the limited clinical severity of disease in the population studied. The latter may be due in part to an as yet unexplained dearth of elderly patients admitted into the hospitals during the study period. The average patient age was 43.  

"I will be paying more attention in my clinical practice to our data points, watching patients closer if they for instance complain of severe myalgia," adds Coffee. "It's exciting to be able to share data with the field in real time when it can be useful. In all past epidemics, journal papers only published well after the infections had waned."

Along with Coffee and Bari, authors of the study included first author Xiangao Jiang, along with Jianping Huang, Jichan Shi, Jianyi Dai, Jing Cai, Zhengxing Wu, and Guiqing He, in the Department of Infectious Diseases at Wenzhou Central Hospital. Also from Wenzhou Central Hospital was author Yitong Huang of Department of Gynaecology.

Also study authors were Junzhang Wang of the Courant Institute of Mathematical Sciences at New York University, Xinyue Jiang of Columbia University, and Tianxiao Zhang in Department of Infectious Diseases at Cangnan People's Hospital. Coffee is also adjunct faculty in the Department of Population and Family Health at the Mailman School of Public Health at Columbia.

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Anemia

Anemia is a condition that occurs when not enough oxygen-carrying red blood cells are being delivered to your body's cells and organs. People with anemia look worn out and have less energy for activities because their hearts are working harder to pump red blood cells around their bodies.
 Anemia is not a disease, so it's easily treatable. Sometimes it’s triggered by other diseases. If you suspect you might be anemic, it's really important to get in touch with a medical professional. A blood test easily confirms whether you have anemia or not.
 Anemia also occurs when your body doesn't produce enough red blood cells, or there isn't enough hemoglobin in your red blood cells. Hemoglobin is an important protein, which transports oxygen from the lungs to other cells in your body.
 Types of Anemia
 There are several different kinds of anemia. The most common one is iron deficiency anemia, i.e. you have low levels of iron or are unable to absorb iron easily. Other nutritional deficiencies cause anemia such as vitamin B12 deficiency anemia or folic acid deficiency anemia. In rare cases, anemia is caused by inherited blood diseases such as sickle cell anemia, Aplastic anemia, or Thalassemia.
 How to know if you're Anemic
 Anemia isn't initially obvious. When you have mild to moderate anemia, you will feel weak, be fatigued and experience shortness of breath. If the condition is not detected early, more symptoms might develop such as a racing heartbeat, dizziness, headaches, ringing in the ears and restless leg syndrome. Additionally your skin and fingernails will look pale, and you might have increased hair loss. As mentioned before, the best way to tell if you are anemic is by getting a blood test.

Signs and Symptoms:
  Mild Anemia:

• Weakness
• Fatigue
• Shortness of breath 

  Moderate to Severe Anemia:

• Rapid heartbeat
• Dizziness
• Headaches
• Ringing in the ears
• Restless leg syndrome
• Hair loss
• Pale skin 

  Additional Signs:

• Pale or brittle fingernails
• Cold hands and feet
• Low body temperature
• Sexual dysfunction
• Cuts take longer to heal
• Inability to concentrate 

Treatment & Home Remedies

 Iron Pills Since the most common cause of anemia is low levels of iron, your doctor can prescribe iron pills, or you can buy supplements over the counter at a pharmacy. If one ingests too much iron, it can be toxic, and it is recommended you consult your doctor regarding the correct dosage for your age and weight.

Bananas, Honey, Almonds and Onions
The good news is that not only are these foods delicious, but they are also known for stimulating hemoglobin production. Start your day off by combining bananas, honey and almonds in oatmeal or with muesli for a nutritious breakfast.

Avoid Iron-Blocking Foods
Certain foods need to be avoided close to meal times as they can prevent iron absorption.

• Red wine, black and green tea, grapes, all heavy in tannins
• Coffee, chocolate, and other caffeine laden foods
• Milk and calcium products
• Egg yolks, which contain the iron binding protein phosvitin
• Soy products

Vitamin C
This super vitamin helps iron absorption. Vitamin C is found in many of nature's colorful fruits and vegetables and is particularly rich in oranges, strawberries, pomegranates or dates.
 Iron-Rich Food Options
 Iron can also be obtained through your regular diet and making healthy food choices can only help. Here is a list of iron-rich foods, with choices for both meat lovers and vegetarians.

Meat-eaters' options

• Clams
• Oysters
• Fish
• Red meat
• Chicken liver

Vegetarian options

• Fortified dry cereal
• Beets, lentils, and beans
• Spinach, or other leafy green vegetables
• Black molasses
• Dried fruits such as raisins, currants, and prunes

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Regulate your body's iron content to ‘switch on’ cellular functions

If you thought that your hemoglobin levels measure your iron status, think again. While hemoglobin reflects whether an individual is anemic, it may not necessarily be an indicator of your body’s iron stores.

Non-anemic iron deficiency was suggested as a factor for diffuse hair loss in women in 1963.
Since then, numerous studies have evaluated the associations between iron deficiency and hair loss.
Iron is stored in the body as ferritin. During early stages of iron deficiency, a decreased ferritin level is a sign of decreased iron stores.

Ferritin accounts for 20 per cent of total iron in adults and it plays an important role both in  absorption and recycling of iron and is formed by intestinal mucosa, liver, spleen and bone marrow.
Ferritin levels are a good indication of iron storage levels. Low ferritin levels indicate depleted iron reserves, while high ferritin levels indicate inflammation and can be a risk factor for cardiovascular disease and diabetes.

Hair fall, hair thinning, hair loss (alopecia) and dull lifeless hair and lightening of dark hair can be linked to low ferritin levels.

Since iron is one of the key nutrients to ‘switch on’ cellular functions, low levels affect brain function as well. Iron deficiency is also known to depress the immune system, making the body more vulnerable to infection.

Also, thyroid, para-thyroid and adrenal gland function are influenced by an imbalance of iron.
Amenorrhea (loss of menstrual cycles) is also seen with low iron stores. A poorly understood behaviour seen among iron deficient people is pica — the craving and consumption of ice, chalk, starch, clay, soil and other non-food substances.

Most common causes of low ferritin levels include heavy menstrual bleeding, crash dieting, poor diets, parasitic infections, surgeries, severe illnesses, digestive tract bleeding, emotional stress, medications, certain health conditions like malabsorption and thyroid abnormalities or hormonal changes.

Excessive or prolonged intake of certain supplements including vitamins B12, D, E, zinc, calcium, copper, magnesium or chromium antagonise the absorption of iron and may contribute to iron deficiency.

While these nutrients are important, supplementation with ferritin should be done with care for efficient body functioning.

Boost your iron levels
Iron rich foods include:
Animal foods — meat, especially organ meat (liver), Poultry and fish
Green leafy vegetables — cauliflower greens, mustard greens, radish leaves
Seed: Amaranth, lotus stem, black gram, black sesame, seaweed, black beans, soybean,
Grains: Quinoa
Dry fruits — dates and sultanas.

Iron absorption by our bodies is dependent on whether it is heme iron (animal food) or non-heme iron (plant foods)


Heme iron diets, rich in animal foods, allow a higher absorption of iron (10%-20%) compared to vegetarian diets (2%-5%)

Iron is absorbed 2-3 times more efficient when taken with foods high in vitamin C, such as citrus fruits, sprouts, tomatoes

Iron uptake can be increased by cooking in cast iron vessels. 100 g of spaghetti sauce can absorb 87g of iron from pan

 THIS IS ONLY FOR INFORMATION, ALWAYS CONSULT YOU PHYSICIAN BEFORE HAVING ANY PARTICULAR FOOD/ MEDICATION/EXERCISE/OTHER REMEDIES.








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