The Association for Diagnostics & Laboratory Medicine (ADLM, formerly AACC) has issued a new guidance document that provides expert recommendations on fundamental areas of clinical testing for respiratory viral infections.
Read the guidance document here: https://www.myadlm.org/science-and-research/academy-guidance/laboratory-diagnosis-of-respiratory-viruses
Respiratory tract infections caused by viral pathogens are among the most common reasons for healthcare visits, and the rapid and accurate diagnosis of these infections is crucial for ensuring optimal patient outcomes. Thanks to the innovative work of laboratory medicine experts, testing has advanced greatly in this area in recent years, particularly in response to the needs of the COVID-19 pandemic. As a result, a wider variety of sample types can now be used to test for respiratory viruses, and a wider variety of testing modalities are available, too. However, this has also led to a need for more education on the most effective ways to use these new testing options.
A multidisciplinary group of clinical microbiologists and infectious disease clinicians formed by the Academy of Diagnostics & Laboratory Medicine has developed guidance on this subject that is endorsed by the Pan American Society for Clinical Virology. Based on the latest research on COVID-19 and other respiratory viruses, the document recommends using nasopharyngeal samples to test for upper respiratory tract infections and it also recommends the use of nucleic acid amplification testing when possible. The document advises that viral load test results should be interpreted in the context of clinical symptoms. Furthermore, the guidance document discusses the role of diagnostic stewardship in respiratory virus testing, which can help generate accurate and clinically relevant results while conserving laboratory resources.
Additionally, the authors of the guidance document propose an algorithm that can help laboratories efficiently decide on the most appropriate tests for a given case of respiratory virus infection. The algorithm considers if patients are symptomatic, immunocompromised, and if a positive result would change disease management.
