The present study aimed to determine PCR-Thoracic CT compliance in Covid-19 diagnosis, and to create a decision tree to make PCR negative identification based on the clinical, laboratory and radiological data of people who admitted to hospital with Covid-19 diagnosis or suspicion. The present study was a cross-sectional retrospective study, and was conducted between 12 March and 30 April 2020 at the University of Health Sciences Kanuni Sultan Suleyman Training and Research Hospital. The Study Group consisted 532 patients who admitted to the Covid-19 Clinic of the hospital and who were admitted to hospital with Covid-19 diagnosis or suspicion and not transferred to Intensive Care Units. The sensitivity of PCR test was 0.384, and the specificity was found as 0.585. The positive predictive rate of the same test was calculated as 0.893; negative predictive rate was 0.095; and the overall predictive rate of the test was 0.404. The overall predictive rate of the decision tree was found as 90%. Statistically significant differences were detected between the groups in terms of fibrinogen, LYM, Albumin and age parameters (p<0.05). The overall predictive rate of the decision tree was as 90%. Statistically significant differences were detected between the groups in terms of fibrinogen, LYM, Albumin and age parameters (p<0.05). The biochemical markers mentioned in the decision tree caught Thoracic CT positivity in PCR-negative patients with an accuracy rate of 90%. Computed Tomography is presented as a guiding method for the diagnosis patients with biochemical parameters in RT-PCR-negative individuals in decision tree.

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