Sequential battery of COVID-19 testing to maximize negative predictive value before surgeries.

Area of Science:

• Infectious Diseases
• Virology
• Medical Diagnostics

Background:

• Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) is a highly contagious novel virus.
• Understanding viral dynamics and immune responses is crucial for effective management.
• The diagnostic accuracy of available SARS-CoV-2 testing methods requires further evaluation.

Purpose of the Study:

• To review published data on SARS-CoV-2 testing methods.
• To assess how test yield is affected by specimen type and time since illness onset.
• To propose an optimized testing strategy to enhance diagnostic accuracy.

Main Methods:

• Systematic review of published literature on SARS-CoV-2 diagnostic tests.
• Analysis of test performance based on specimen type and temporal aspects of infection.
• Development of a sequential testing algorithm.

Main Results:

• The yield of COVID-19 tests is significantly influenced by the type of specimen collected.
• Test sensitivity and specificity change over the course of the illness.
• A multi-modal testing approach demonstrates potential for improved diagnostic yield.

Conclusions:

• Diagnostic accuracy for SARS-CoV-2 is variable and dependent on testing methodology and timing.
• A sequential testing strategy, incorporating epidemiologic surveys, RT-PCR, serology, and chest CT, may enhance the negative predictive value.
• This approach could facilitate surgical procedures by improving patient assessment and safety.