Accuracy of the Verbal Autopsy questionnaire in the diagnosis of COVID-19 deaths in a Brazilian capital.
Marcos Adriano Garcia CamposÉzio Arthur Monteiro CutrimÉrico Murilo Monteiro CutrimJoão Victor Pimentel de OliveiraEduardo José Silva Gomes de OliveiraDaniel de Brito PontesJosé Albuquerque de Figueiredo NetoGyl Eanes Barros SilvaPublished in: Revista do Instituto de Medicina Tropical de Sao Paulo (2024)
The Verbal Autopsy (VA) is a questionnaire about the circumstances surrounding a death. It was widely used in Brazil to assist in postmortem diagnoses and investigate excess mortality during the Coronavirus Disease 2019 (COVID-19) pandemic. This study aimed to determine the accuracy of investigating acute respiratory distress syndrome (ARDS) using VA. This is a cross-sectional study with prospective data collected from January 2020 to August 2021 at the Death Verification Service of Sao Luis city, Brazil. VA was performed for suspected COVID-19 deaths, and one day of the week was randomly chosen to collect samples from patients without suspected COVID-19. Two swabs were collected after death and subjected to reverse transcription-polymerase chain reaction (RT-PCR) for SARS-CoV-2 detection. Of the 250 cases included, the VA questionnaire identified COVID-19-related ARDS in 67.2% (52.98% were positive for COVID-19). The sensitivity of the VA questionnaire was 0.53 (0.45-0.61), the specificity was 0.75 (0.64-0.84), the positive predictive value was 0.81 (0.72-0.88), and the negative predictive value was 0.44 (0.36-0.53). The VA had a lower-than-expected accuracy for detecting COVID-19 deaths; however, because it is an easily accessible and cost-effective tool, it can be combined with more accurate methods to improve its performance.
Keyphrases
- coronavirus disease
- sars cov
- acute respiratory distress syndrome
- respiratory syndrome coronavirus
- extracorporeal membrane oxygenation
- cross sectional
- mechanical ventilation
- mental health
- patient reported
- pulmonary embolism
- randomized controlled trial
- risk factors
- newly diagnosed
- cardiovascular disease
- high resolution
- mass spectrometry
- clinical trial
- intensive care unit
- big data
- prognostic factors
- deep learning
- study protocol
- machine learning
- cardiovascular events
- loop mediated isothermal amplification