Use of predictive tools in the management of COVID-19 patients: a key role of clinical laboratories

Abstract Objectives Coronavirus disease 2019 (COVID-19) is widely spreading and represents a critical threat to global health. In the fight against this pandemic, provincial hospitals urgently need rapid diagnostic of COVID-19 infected patients to avoid collapsing of emergency units. However, the high demand of patients with severe acute respiratory symptoms limits the fast delivery of results by the gold standard method reverse transcription-polymerase chain reaction real time (rRT-PCR) for the identification of COVID-19 positive pneumonia. The principal aim is to find other useful laboratory indicators to assist rRT-PCR tests and to help controlling of this outbreak. Methods Blood, coagulation and inflammatory parameters were collected from a total of 309 patients classified as negative (128) and positive (181) rRT-PCR test groups. Patients were classified as positive by molecular diagnostic test. Results Leukocyte count (WBC), neutrophils count, lymphocytes count and lactate dehydrogenase (LDH) were statistically different between both groups of patients. The use of LDH/WBC ratio increases the diagnostic performance with the best area under the curve (0.783), sensibility (82%) and the best percentage (80.5%) of correctly identified COVID-19 positive patients. Conclusions The combination of predictive LDH/WBC ratio with clinical illness features could help in medical management of patients and improve the technical resources of hospitals, especially in a critical scenario with a large shortage of medical equipment and lack of reagents for performing rRT-PCR.