A trio of indicators that suggest a higher risk of death COVID-19 patients
In Wuhan, China, research shows 14-19% of infected patients became severely sick. Among those critically ill cases, the death rate was higher than 60%.
To identify commonalities between these severe cases, ther esearchers analysed blood samples taken repeatedly from 485 patients at Tongji Hospital in Wuhan, China, between Januar10 and February 18. They tested for myriad kidney, heart, and blood-clotting issues, noted whether those patients had survived or died, then used machine-learning algorithms to look for biological patterns.
The results found that the following indicators can predict whether a patient had a higher risk of death than other infected people:
1) High levels of the enzyme lactic dehydrogenase (LDH). This is associated with lung damage and the type of tissue breakdown that happens during pneumonia.
2) Lymphopenia, the terms for low levels of lymphocytes---white blood cells that defend the body against invading pathogens.
3) An increase in high-sensitivity C-reactive proteins, or hs-CRP for short. This indicates inflammation in the lungs.
Using those indicators, the computer model could predict what happened to the hospital patients 10 days in advance of their clinical outcomes.
The 3 key features, LDH, lymphocytes and hs-CRP, can be easily collected in any hospital, the researchers wrote in the study. In crowded hospitals, and with shortages of medical resources, this simple model can help to quickly prioritize patients, especially during a pandemic when limited healthcare resources have to be allocated.
A coronavirus ' risk score'.
Another study published this week took a similar approach, pinpointing 10 biomarkers that can help doctors assess individual patients' risk levels. That research, published in the Journal of the American Medical Association on Tuesday, suggested using these markers to determine the likelihood that a hospitalised cOVID-19 patient will become critically ill-- admitted to an intensive-care unit or put on a ventilator-- or die.
The researchers retrospectively examined medical records from 1,590 patients who were treated in 575 hospitals across China between November 21, 2019 and January 31.
Two of those biomarkers overlap with those suggested in the Nature study: high levels of LDH and a high neutrophil-to-lymphocyte ratio ( which is associated with lower levels of lymphocytes).
The other eight risk predictors include a history of cancer, high number of pre-existing medical conditions, older age, shortness of breath, coughing up blood, unconsciousness, abnormal chest x-rays, and high levels of bilirubin ( a substance in the blood that, in elevated amounts, indicates liver damage).
The researchers used those 10 indicators to develop an online coronavirus risk " calculator" that could help predict which hospitalised COVID-19 patients will become critically ill.
That prediction tool could enable doctors and healthcare workers optimise hospital resources, the study authors wrote.
If the patient's estimated risk for critical illness is low, the clinician may choose to monitor, whereas high-risk estimates might support aggressive treatment or admission to the ICU, they said.
To identify commonalities between these severe cases, ther esearchers analysed blood samples taken repeatedly from 485 patients at Tongji Hospital in Wuhan, China, between Januar10 and February 18. They tested for myriad kidney, heart, and blood-clotting issues, noted whether those patients had survived or died, then used machine-learning algorithms to look for biological patterns.
The results found that the following indicators can predict whether a patient had a higher risk of death than other infected people:
1) High levels of the enzyme lactic dehydrogenase (LDH). This is associated with lung damage and the type of tissue breakdown that happens during pneumonia.
2) Lymphopenia, the terms for low levels of lymphocytes---white blood cells that defend the body against invading pathogens.
3) An increase in high-sensitivity C-reactive proteins, or hs-CRP for short. This indicates inflammation in the lungs.
Using those indicators, the computer model could predict what happened to the hospital patients 10 days in advance of their clinical outcomes.
The 3 key features, LDH, lymphocytes and hs-CRP, can be easily collected in any hospital, the researchers wrote in the study. In crowded hospitals, and with shortages of medical resources, this simple model can help to quickly prioritize patients, especially during a pandemic when limited healthcare resources have to be allocated.
A coronavirus ' risk score'.
Another study published this week took a similar approach, pinpointing 10 biomarkers that can help doctors assess individual patients' risk levels. That research, published in the Journal of the American Medical Association on Tuesday, suggested using these markers to determine the likelihood that a hospitalised cOVID-19 patient will become critically ill-- admitted to an intensive-care unit or put on a ventilator-- or die.
The researchers retrospectively examined medical records from 1,590 patients who were treated in 575 hospitals across China between November 21, 2019 and January 31.
Two of those biomarkers overlap with those suggested in the Nature study: high levels of LDH and a high neutrophil-to-lymphocyte ratio ( which is associated with lower levels of lymphocytes).
The other eight risk predictors include a history of cancer, high number of pre-existing medical conditions, older age, shortness of breath, coughing up blood, unconsciousness, abnormal chest x-rays, and high levels of bilirubin ( a substance in the blood that, in elevated amounts, indicates liver damage).
The researchers used those 10 indicators to develop an online coronavirus risk " calculator" that could help predict which hospitalised COVID-19 patients will become critically ill.
That prediction tool could enable doctors and healthcare workers optimise hospital resources, the study authors wrote.
If the patient's estimated risk for critical illness is low, the clinician may choose to monitor, whereas high-risk estimates might support aggressive treatment or admission to the ICU, they said.
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