Diagnosis of coronavirus disease 2019 and the potential role of deep learning: insights from the experience of Cairo University Hospitals

OBJECTIVES

Early detection of coronavirus disease 2019 (COVID-19) is crucial for patients and public health to ensure pandemic control. We aimed to correlate clinical and laboratory data of patients with COVID-19 and their polymerase chain reaction (PCR) results and to assess the accuracy of a deep learning model in diagnosing COVID-19.

METHODS

This was a retrospective study using an anonymized dataset of patients with suspected COVID-19. Only patients with a complete dataset were included (n = 440). A deep analytics framework and dual-modal approach for PCR-based classification was used, integrating symptoms and laboratory-based modalities.

RESULTS

Participants with loss of smell or taste were two times more likely to have positive PCR results (odds ratio [OR] 1.86). Participants with neutropenia, high serum ferritin, or monocytosis were three, four, and five times more likely to have positive PCR results (OR 2.69, 4.18, 5.42, respectively). The rate of accuracy achieved using the deep learning framework was 78%, with sensitivity of 83.9% and specificity of 71.4%.

CONCLUSION

Loss of smell or taste, neutropenia, monocytosis, and high serum ferritin should be routinely assessed with suspected COVID-19 infection. The use of deep learning for diagnosis is a promising tool that can be implemented in the primary care setting.

Gender Difference in Perceived Symptoms and Laboratory Investigations in Suspected and Confirmed COVID-19 Cases: A Retrospective Study

BACKGROUND

Evaluating gender-specific effects of COVID-19 is important to develop effective therapeutic strategies. The aim of this study was to explore gender difference in perceived symptoms and laboratory investigations in suspected and confirmed cases.

METHODS

This is a retrospective study that included data from suspected COVID-19 patients during the first wave of the pandemic. Participants using the phone triaging system at Kasralainy outpatient clinics were included. The analyzed data included patient history and results of nasopharyngeal swab and laboratory data.

RESULTS

Out of 440 COVID-19 suspected cases, 56.36% were females. The perceived COVID-19 symptoms showed no significant gender difference in suspected cases while in confirmed cases females were 4 times more likely to complain of cough [OR (95% CI) 3.92 (1.316-11.68), P-value .014] and 5 times more likely to experience loss of smell or taste [OR (95% CI) 4.84 (1.62-14.43), P-value .005]. Laboratory markers revealed high levels of aspartate aminotransferase, alanine aminotransferase, blood urea, serum creatinine, creatine kinase, and serum ferritin in males and this was statistically significant (P-value <.001) in suspected and confirmed cases. Females confirmed with COVID-19 were 80%, 97%, and 97% less likely to have high levels of ALT, creatin kinase, and serum ferritin [OR (95% CI) 0.20 (0.07-0.54), 0.07 (0.01-0.38), and 0.07 (0.01-0.90), P-value .002, .002, and .041, respectively].

CONCLUSION

Gender differences were found in laboratory markers in COVID-19 suspected and confirmed cases and in perceived symptoms in confirmed cases.