Improving CT accuracy in the diagnosis of COVID-19 in a hospital setting

Autor: Julia Kremmin, Alexandra Niehues, Lisa C. Adams, Marcus R. Makowski, Hans Martin Thieß, Stefan M. Niehues, Janis L Vahldiek, Christoph Erxleben, Keno K. Bressem, Antonia Petersen, Jacob Albrecht
Jazyk: angličtina
Rok vydání: 2021
Předmět:
medicine.medical_specialty
Respiratory rate
Coronavirus disease 2019 (COVID-19)
Hospital setting
PPV
Positive Predictive Value
Subgroup analysis
Pretest probability
IQR
Interquartile Range
Sensitivity and Specificity
030218 nuclear medicine & medical imaging
03 medical and health sciences
0302 clinical medicine
Text mining
Medicine
Humans
Radiology
Nuclear Medicine and imaging
NPV
Negative Predictive Value
Cardiothoracic Imaging
AUC
Area Under the Curve
Computed tomography
Retrospective Studies
business.industry
SARS-CoV-2
Confounding
ROC
Receiver Operating Characteristic
RT-PCR
Reverse Transcription-Polymerase Chain Reaction
COVID-19
Retrospective cohort study
CT
Computed Tomography
CI
Confidence Interval
Hospitals
Pre- and post-test probability
SARS-CoV-2
Severe Acute Respiratory Syndrome Coronavirus 2
Radiology Nuclear Medicine and imaging
030220 oncology & carcinogenesis
COVID-19
Coronavirus Disease 2019
Prediction of COVID-19
Radiography
Thoracic
Radiology
business
Tomography
X-Ray Computed
Vital parameters
Zdroj: Clinical Imaging
ISSN: 1873-4499
0899-7071
Popis: Objective This study aimed to improve the accuracy of CT for detection of COVID-19-associated pneumonia and to identify patient subgroups who might benefit most from CT imaging. Methods A total of 269 patients who underwent CT for suspected COVID-19 were included in this retrospective analysis. COVID-19 was confirmed by reverse-transcription-polymerase-chain-reaction. Basic demographics (age and sex) and initial vital parameters (O2-saturation, respiratory rate, and body temperature) were recorded. Generalized mixed models were used to calculate the accuracy of vital parameters for detection of COVID-19 and to evaluate the diagnostic accuracy of CT. A clinical score based on vital parameters, age, and sex was established to estimate the pretest probability of COVID-19 and used to define low, intermediate, and high risk groups. A p-value of
Highlights • A simple score to estimate the pre-test probability of COVID-19 can be calculated using vital parameters, basic vital parameters. • Accuracy of CT for the detection of COVID-19 might be increased by selecting patients with a high-pretest probability. • In patients with mild symptoms, CT examinations are unlikel unlikely to be effective with a very low positive predictive value.
Databáze: OpenAIRE
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