Journal Article

·2022 OPEN ACCESS

Evaluation of SARS-CoV-2 patients with annual RT-PCR analysis results

Yakup Artik , Selen Zeliha Mart Kömürcü , Nevra Pelin Cesur YTU , Cemal Kazezoğlu , Yasemin Tuba Sutasir

Journal of Clinical and Experimental Investigations

Abstract

Background: Nowadays, people have faced with a pandemic called COVID-19. The reliable detection of the virus is important to prevent transmission of the virus. RT-PCR is a gold standard method for the diagnosis of the disease used at all over the world. The highest number of sample size (1,461,258 patient sample) and differing results are reported with our study regarding the PCR positivity rates. Method/Study Design: The study was aimed to evaluate the positivity and negativity of the patients with RT-PCR from all the samples studied between March 25, 2020 and March 25, 2021, when the pandemic was declared and started to be seen in Turkey, and to investigate its contribution to the total test capacity of our country. Results/Conclusions: 1,461,258 patient is observed, and this frequency male is 58% and female is 42% of the population. The maximum number of admissions is noticed during the Autumn-2020 involved age ranged from 25 to 35. 14.6% positive result is got while the 85.4% negative result is observed. When the age distribution of COVID-19 (+) patients is evaluated, COVID-19 (+) rate is highest in the 6-15 age range, followed by the 66-75 age range and the highest COVID-19 (+) rate are November and October, respectively. Additionally, the highest COVID-19 (+) rate is in Autumn. According to the test results, it was determined that 7.5% of the male participants were COVID-19 (+) and 7.1% of the female participants were COVID-19 (+).

Keywords

Medicine Coronavirus disease 2019 (COVID-19) Pandemic Gold standard (test) Population Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) Demography Internal medicine Disease Environmental health Infectious disease (medical specialty)

Subject Areas

SARS-CoV-2 and COVID-19 Research ·Infectious Diseases ·Health Sciences
COVID-19 diagnosis using AI ·Radiology, Nuclear Medicine and Imaging ·Health Sciences
SARS-CoV-2 detection and testing ·Infectious Diseases ·Health Sciences

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