Chest CT for triage during COVID-19 on the emergency department: myth or truth?

Abstract

We aimed to investigate the diagnostic performance of chest CT compared with first RT-PCR results in adult patients suspected of COVID-19 infection in an ED setting. We also constructed a predictive machine learning model based on chest CT and additional data to improve the diagnostic accuracy of chest CT. Methods This study's cohort consisted of 319 patients who underwent chest CT and RT-PCR testing at the ED. Patient characteristics, demographics, symptoms, vital signs, laboratory tests, and chest CT results (CO-RADS) were collected. With first RT-PCR as reference standard, the diagnostic performance of chest CT using the CO-RADS score was assessed. Additionally, a predictive machine learning model was constructed using logistic regression.

Optimization of Patient Management During the COVID-19 Pandemic: Chest CT Scan and PCR as Gatekeepers of the Radiation Therapy Workflow

“…However, this study highlighted the low specificity of chest CT [37% (95% CI: 26%, 50%)] with poor positive predictive value (PPV) for populations with low expected prevalence of COVID-19, limiting its routine use for mass screening and diagnosis in the overall population, especially since CT scans also expose people to ionizing radiation. Therefore, the general consensus is to not recommend chest CT for diagnosing COVID-19 and to reserve CT for patients with worsening symptoms (21,22). However, several authors have suggested that imaging could help patient triage in a resource-constrained environment, especially when the pre-test probability of COVID-19 is high (21,22).…”

“…Therefore, the general consensus is to not recommend chest CT for diagnosing COVID-19 and to reserve CT for patients with worsening symptoms (21,22). However, several authors have suggested that imaging could help patient triage in a resource-constrained environment, especially when the pre-test probability of COVID-19 is high (21,22). Nevertheless, with a high negative predictive value (NPV) estimated between 90.6% and 99.8%, chest CT imaging could still be very valuable in specific situations, such as in screening patients undergoing radiotherapy.…”

Machine learning is the key to diagnose COVID-19: a proof-of-concept study

“…that used data from a large sample, but did not include imaging data 58 . Another study integrated RT-PCR, chest-CT and clinico-biological data, like in the present work, but the study population was smaller, and the performance was slightly lower 59 . In our study, the AUC values for chest-CT and RT-PCR increased from 0.778 to 0.892 and from 0.852 to 0.930 with the contribution of machine learning.…”

Coronavirus disease (COVID-19) cases analysis using machine-learning applications

“…Hereafter, the results suggested artificial intelligence be applied for accurate risk estimation of COVID-19 patients, to enhance patient triage (Assaf 2020). In a study conducted by (Hermans et al 2020) in the Netherlands, their article used 319 patients as the dataset and they selected supervised learning as their method, while the logistic regression was the selected algorithm. In this article, they depended on the patient's chest CT scan scores, and the RT-PCR test the results demonstrated that Chest CT, using the CO-RADS scoring system, is a specific useful method that can lead to accurate diagnosis of COVID-19, particularly if RT-PCR tests are uncommon during an epidemic.…”