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Author Spotlight: Advancements in Multiplex Detection of Respiratory Viruses
Published on: November 10, 2023
Combination of rRT-PCR and Clinical Features to Predict Coronavirus Disease 2019 for Nosocomial Infection Control
Fumihiro Yamaguchi1, Ayako Suzuki2, Miyuki Hashiguchi3
1Department of Respiratory Medicine, Showa University Fujigaoka Hospital, Yokohama, Japan.
Insights
Clinical factors like age, BMI, and inflammatory markers can help predict COVID-19 in patients with similar symptoms. Two SARS-CoV-2 tests are recommended for accurate diagnosis.
Area of Science:
- Infectious Diseases
- Clinical Medicine
- Epidemiology
Background:
- The COVID-19 pandemic necessitated effective screening for SARS-CoV-2.
- Nosocomial infection control requires early identification of COVID-19 patients.
Purpose of the Study:
- To identify clinical variables that can predict COVID-19.
- To differentiate COVID-19 from other conditions presenting with similar symptoms.
Main Methods:
- A cross-sectional study of 1087 patients in an isolation ward.
- Utilized multivariate logistic regression to analyze clinical factors.
- Employed nucleic acid testing and clinical conferences for diagnosis.
Main Results:
- 32.4% of patients were diagnosed with COVID-19.
- Bacterial infections were the primary cause of non-COVID-19 cases.
- COVID-19 prediction was associated with age, sex, BMI, LDH, CRP, and malignancy.
Conclusions:
- Specific clinical factors aid in predicting COVID-19 among symptomatic individuals.
- Recommends at least two real-time RT-PCR tests for SARS-CoV-2 to exclude the diagnosis.
Background:
Coronavirus disease 2019 (COVID-19), caused by severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2), immediately became a pandemic. Therefore, nosocomial infection control is necessary to screen for patients with possible COVID-19.
Objective:
This study aimed to investigate commonly measured clinical variables to predict COVID-19.
Methods:
This cross-sectional study enrolled 1087 patients in the isolation ward of a university hospital. Conferences were organized to differentiate COVID-19 from non-COVID-19 cases, and multiple nucleic acid tests were mandatory when COVID-19 could not be excluded. Multivariate logistic regression models were employed to determine the clinical factors associated with COVID-19 at the time of hospitalization.
Results:
Overall, 352 (32.4%) patients were diagnosed with COVID-19. The majority of the non-COVID-19 cases were predominantly caused by bacterial infections. Multivariate analysis indicated that COVID-19 was significantly associated with age, sex, body mass index, lactate dehydrogenase, C-reactive protein, and malignancy.
Conclusion:
Some clinical factors are useful to predict patients with COVID-19 among those with symptoms similar to COVID-19. This study suggests that at least two real-time reverse-transcription polymerase chain reactions of SARS-CoV-2 are recommended to exclude COVID-19.
