Predictors of SARS-CoV-2 Positivity Based on RT-PCR Swab Tests at a Drive-Through Outpatient Clinic for COVID-19 Screening in Japan

Ishii, Tadashi; Kushimoto, Shigeki; Katori, Yukio; Kure, Shigeo; Igarashi, Kaoru; Fujita, Motoo; Takayama, Shin; Abe, Michiaki; Tanaka, Junichi; Kikuchi, Akiko; Abe, Yoshiko; Imai, Hiroyuki; Inaba, Yohei; Iwamatsu-Kobayashi, Yoko; Nishioka, Takashi; Onodera, Ko; Akaishi, Tetsuya

doi:10.1620/tjem.253.101

Cited by 20 publications

(19 citation statements)

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“…7,8 The predictors of SARS-CoV-2 infection include contact history with confirmed cases, fever, respiratory symptoms, gustatory dysfunction, gastrointestinal symptoms, and neurological symptoms. [9][10][11][12] The results of laboratory examinations have also been studied to help construct a predictive model using artificial intelligence. 13 However, patients with early COVID-19 or certain groups of patients, such as pregnant women, may only experience mild symptoms or could even be asymptomatic.…”

Section: Introductionmentioning

confidence: 99%

COVID-19 Screening for Hospitalized Patients: The Role of Expanded Hospital Surveillance in a Low Prevalence Setting

Hsu¹,

Liu²,

Tseng³

et al. 2021

JMDH

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Purpose:The COVID-19 pandemic poses a serious threat to healthcare workers and hospitalized patients. Early detection of COVID-19 cases is essential to control the spread in healthcare facilities. However, real-world data on the screening criteria for hospitalized patients remain scarce. We aimed to explore whether patients with negative results of prehospital screening for COVID-19 should be rescreened after admission in a low-prevalence (less than 3% of the world average) setting. Patients and Methods:We retrospectively included patients in central Taiwan who were negative at the first screening but were newly diagnosed with pneumonia or had a body temperature above 38 degrees Celsius during their hospitalization. Each patient might be included as an eligible case several times, and the proportions of cases who were rescreened for COVID-19 and those diagnosed with COVID-19 were calculated. A logistic regression model was constructed to identify factors associated with rescreening. Reverse transcriptionpolymerase chain reaction tests were used to confirm the diagnosis of COVID-19. Results: A total of 3549 cases eligible for COVID-19 rescreening were included. There were 242 cases (6.8%) who received rescreening. In the multivariable analysis, cases aged 75 years or older, those with potential exposure to SARS-CoV-2, or patients visiting specific departments, such as the Cardiovascular Center and Department of Neurology, were more likely to be rescreened. None was diagnosed with COVID-19 after rescreening. There was no known cluster infection outbreak in the hospital or in the local community during the study period and in the following two months. Conclusion:In Taiwan, a country with a low COVID-19 prevalence, it was deemed safe to rescreen only high-risk hospitalized patients. This strategy was effective and reduced unnecessary costs.

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Section: Introductionmentioning

confidence: 99%

COVID-19 Screening for Hospitalized Patients: The Role of Expanded Hospital Surveillance in a Low Prevalence Setting

Hsu¹,

Liu²,

Tseng³

et al. 2021

JMDH

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“…Positivity for the N2 gene was confirmed by RT-PCR using the primers and the probe developed by the National Institute of Infectious Disease, Japan (NIID_2019-nCOV_ N_F2, R2, and P2) (Shirato et al 2020). The RT-PCR method was described in detail in our previous report (Ishii et al 2021). It has been known that the transmissibility of COVID-19 infection is different between symptomatic and asymptomatic COVID-19 patients (Chen et al 2020;Qiu et al 2021).…”

Section: Methodsmentioning

confidence: 99%

Impacts of Natural Environmental Factors and Prevalence of Airway Symptoms on the Local Spread of COVID-19: A Time-Series Analysis in Regional COVID-19 Epidemics

Ishii

Kushimoto

Katori

et al. 2021

Tohoku J. Exp. Med.

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Coronavirus disease 2019 , caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), is the world's largest public health concern in 2021. This study evaluated the associations of the prevalence of airway symptoms among the tested individuals and data regarding the natural environmental factors with the weekly number of newly diagnosed COVID-19 patients in Sendai City (N t ). For the derivatives of the screening test results, data from individuals with a contact history who underwent nasopharyngeal swab reverse transcription-polymerase chain reaction (RT-PCR) testing between July 2020 and April 2021 (6,156 participants, including 550 test-positive patients) were used. The value of N t correlated with the weekly RT-PCR test-positive rate after close contact, prevalence of cough symptoms in test-positive individuals or in test-negative individuals, lower air temperature, lower air humidity, and higher wind speed. The weekly test-positive rate correlated with lower air humidity and higher wind speed. In cross-correlation analyses, natural environmental factors correlated with the regional epidemic status on a scale of months, whereas the airway symptoms among non-COVID-19 population affected on a scale of weeks. When applying an autoregression model to the serial data of N t , large-scale movements of people were suggested to be another factor to influence the local epidemics on a scale of days. In conclusion, the prevalence of cough symptoms in the local population, lower air humidity or higher wind speed, and largescale movements of people in the locality would jointly influence the local epidemic status of COVID-19.

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“…In this study, a total of 1,744 consecutive SARS-CoV-2 RT-PCR-tested participants who were ≥3 years of age and who were comprehensively evaluated for self-reported suggestive symptoms at the testing site (i.e., fever, cough, dyspnea, fatigue, dysosmia, dysgeusia), were prospectively enrolled between November 2020 and January 2021. Prior to testing, the participants were assessed by the local government staff at public health centers (via a phone call) on the need for testing based on the history of contact (close/low-risk) with a COVID-19 patient or having at least one of the aforementioned suggestive symptoms ( 5 ). The following information was collected from all of the participants: age, sex, and contact level (close/low-risk/none) with COVID-19 patients.…”

Section: Methodsmentioning

confidence: 99%

“…Real-time RT-PCR for detecting the SARS-CoV-2 nucleocapsid protein set no.2 (N2) gene was performed as previously reported ( 5 ). The primer/probe set was designed by the National Institute of Infectious Diseases in Japan (forward primer, NIID_2019-nCOV_N_F2; reverse primer, NIID_2019-nCOV_N_R2; and TaqMan probe, NIID_2019-nCOV_N_P2) ( 6 ).…”

Section: Methodsmentioning

confidence: 99%

Discriminatory Value of Self-reported Olfactory Dysfunction in the Prediction of Coronavirus Disease 2019

et al. 2021

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Objective Coronavirus disease 2019 , which is caused by severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2), remains the world's largest public health concern in 2021. A history of close contact with infectious patients is a factor that predicts a positive SARS-CoV-2 test result. Meanwhile, the precise predictive value of symptoms suggestive of COVID-19 has not been fully elucidated. This study aimed to clarify the predictive and discriminatory value of each clinical symptom suggestive of COVID-19. Methods This study enrolled participants who were tested for SARS-CoV-2 by reverse transcription polymerase chain reaction using a nasopharyngeal swab between November 2020 and January 2021. All enrolled patients were evaluated for data regarding the presence and closeness of contact with infectious patients and comprehensive clinical features (i.e., fever, cough, dyspnea, fatigue, dysosmia, and dysgeusia). Results Among the 1,744 tested participants, 144 tested positive for SARS-CoV-2. In the test-positive group, self-reported cough, fatigue, dysosmia, and dysgeusia were significant predictors of COVID-19, independent from a history of close contact. In particular, the presence of dysosmia was the strongest predictor of COVID-19 in both univariate and multivariate analyses. Among the 42 patients with self-reported dysosmia, 25 (59.5%) were SARS-CoV-2 test-positive. Self-reported dysosmia was reported by 25 (17.4%) of the 144 patients who tested positive for SARS-CoV-2, and 15 (60.0%) of the 25 COVID-19 patients with dysosmia had accompanying dysgeusia. Conclusion The presence of dysosmia was reported by 10-25% of patients with COVID-19, and is a significant predictor of COVID-19 infection, independent from a history of close contact.

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Predictors of SARS-CoV-2 Positivity Based on RT-PCR Swab Tests at a Drive-Through Outpatient Clinic for COVID-19 Screening in Japan

Cited by 20 publications

References 1 publication

COVID-19 Screening for Hospitalized Patients: The Role of Expanded Hospital Surveillance in a Low Prevalence Setting

COVID-19 Screening for Hospitalized Patients: The Role of Expanded Hospital Surveillance in a Low Prevalence Setting

Impacts of Natural Environmental Factors and Prevalence of Airway Symptoms on the Local Spread of COVID-19: A Time-Series Analysis in Regional COVID-19 Epidemics

Discriminatory Value of Self-reported Olfactory Dysfunction in the Prediction of Coronavirus Disease 2019

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