New Report: Long COVID Diagnosis Shouldn't Depend on Positive Test Results

Aurora, Ill., Illinois United States of America
Long COVID can impact people across all demographics and is associated with a wide range of new or worsening health conditions that can last for months or years
Nearly 18 million adults and nearly 1 million children in the US have had long COVID at some point
New report recommends that long COVID diagnosis should not depend on positive test results
People who were hospitalized from COVID-19 are two to three times as likely to develop long-term symptoms
Report notes that many individuals with long COVID were never tested or test results not reported to healthcare systems
Symptoms include brain fog, chronic fatigue, decreased physical and cognitive function
New Report: Long COVID Diagnosis Shouldn't Depend on Positive Test Results

A new report from the National Academies of Sciences, Engineering and Medicine concludes that people do not need to have tested positive for COVID-19 to be considered for a diagnosis of long COVID. The report, which aims to summarize what is known about the condition, states that many individuals who were infected never received formal documentation of their illness due to limited testing availability or self-reported results not being reported to healthcare systems. The report also noted that sole reliance on a documented history of SARS-CoV-2 infection when diagnosing long COVID will miss individuals who have not been tested or whose test results were never reported. According to the report, nearly 18 million adults and nearly 1 million children in the United States have had long COVID at some point, with about 7% of adults currently affected. The condition can impact people across all demographics and is associated with a wide range of new or worsening health conditions that can last for months or years. Symptoms include brain fog, chronic fatigue, and decreased physical and cognitive function. People who were sick enough to be hospitalized from the coronavirus are two to three times as likely to develop long-term symptoms.



Confidence

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No Doubts Found At Time Of Publication

Sources

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  • Unique Points
    • Nearly 18 million adults and nearly 1 million children in the United States have had long COVID at some point, with about 7% of adults currently affected.
    • Women are about twice as likely to develop long COVID.
    • Long COVID symptoms can include brain fog, chronic fatigue, and decreased physical and cognitive function for six months to two years or longer.
    • People who were sick enough to be hospitalized from the coronavirus are two to three times as likely to develop long-term symptoms.
  • Accuracy
    • Nearly 18 million adults and nearly 1 million children in the United States have had long COVID at some point
    • There is no standardized way to diagnose long COVID
    • Long COVID symptoms can include brain fog, chronic fatigue, and decreased physical and cognitive function for six months to two years or longer
  • Deception (100%)
    None Found At Time Of Publication
  • Fallacies (100%)
    None Found At Time Of Publication
  • Bias (100%)
    None Found At Time Of Publication
  • Site Conflicts Of Interest (100%)
    None Found At Time Of Publication
  • Author Conflicts Of Interest (100%)
    None Found At Time Of Publication

94%

  • Unique Points
    • Doctors should not require a positive coronavirus test for a long Covid diagnosis.
  • Accuracy
    • As of January 2024, nearly 7% of adults in the US had long Covid.
    • There is no standardized way to diagnose long Covid and no definitive treatments to cure it.
  • Deception (100%)
    None Found At Time Of Publication
  • Fallacies (95%)
    The article by Pam Belluck contains some instances of appeals to authority and dichotomous depictions, but overall the article is well-written and provides valuable information about long Covid without resorting to fallacious reasoning. The author cites data from reputable sources such as the National Academies of Sciences, Engineering and Medicine to support her claims about the prevalence and impact of long Covid. She also acknowledges that there is no standardized way to diagnose the condition and no definitive treatments for it, which is an accurate reflection of the current state of research on long Covid. However, she does make some dichotomous depictions by stating that 'there is still no standardized way to diagnose the condition' and 'doctors should not require patients to have a positive coronavirus test to be diagnosed with long Covid'. This creates a false dichotomy between the two approaches, implying that one is right and the other is wrong when in reality both approaches may be valid depending on the individual case. The author also uses some appeals to authority by quoting the National Academies of Sciences, Engineering and Medicine as an expert source on long Covid. While this is a valid use of appeals to authority, it should be noted that such appeals should not be relied upon exclusively and other forms of evidence should also be considered.
    • ]The National Academies said the condition could involve up to 200 symptoms, make it difficult for people to work and last for months or years.[
    • Here are some of the National Academies’ findings:
  • Bias (100%)
    None Found At Time Of Publication
  • Site Conflicts Of Interest (100%)
    None Found At Time Of Publication
  • Author Conflicts Of Interest (100%)
    None Found At Time Of Publication

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  • Unique Points
    • New report concludes that people do not need to have tested positive for COVID-19 to be considered for a diagnosis of long COVID.
    • Among its conclusions, the report states that many who were infected never received formal documentation of their illness due to limited testing availability or self-reported results not being reported to healthcare systems.
    • The report concluded that sole reliance on a documented history of SARS-CoV-2 infection when diagnosing long COVID will miss individuals who have not been tested or whose test results were never reported to healthcare systems.
  • Accuracy
    No Contradictions at Time Of Publication
  • Deception (100%)
    None Found At Time Of Publication
  • Fallacies (100%)
    None Found At Time Of Publication
  • Bias (100%)
    None Found At Time Of Publication
  • Site Conflicts Of Interest (100%)
    None Found At Time Of Publication
  • Author Conflicts Of Interest (100%)
    None Found At Time Of Publication