[Critical coronavirus disease 2019 caused by Delta variant: a case report with literature review].

OBJECTIVE: To investigate the curative efficacy and application value of convalescent plasma (CP) in severe and critical coronavirus disease 2019 (COVID-19) caused by Delta variant. METHODS: The treatment process and results of CP therapy for a patient with critical COVID-19 caused by Delta variant were reported. The clinical application value of CP for COVID-19 caused by Delta variant was analyzed along with the literature review. RESULTS: Our case was a 50-year-old male, who was imported from abroad and had not been vaccinated against COVID-19. The novel coronavirus nucleic acid test was negative before entry. On the second day after entry, fever occurred, novel coronavirus nucleic acid test was positive. Chest CT images showed bilateral multiple mottling and ground-glass opacity with symptoms of nausea, headache, loss of appetite, diarrhea, but no running nose, nasal obstruction, dyspnea, abnormal smell and taste. The infection rapidly developed from medium to critical. On the basis of standard treatment, Delta variant CP was intravenous dripped on the 10th day of hospital admission (the 6th day after becoming severe). The patient's condition improved rapidly. CONCLUSIONS: The curative efficacy evaluation of this patient proved that CP therapy is of great value in the treatment of severe and critical COVID-19.

A Simple Clinical Prediction Tool for COVID-19 in Primary Care with Epidemiology: Temperature-Leukocytes-CT Results.

BACKGROUND Effective identification of patients with suspected COVID-19 is vital for the management. This study aimed to establish a simple clinical prediction model for COVID-19 in primary care. MATERIAL AND METHODS We consecutively enrolled 60 confirmed cases and 152 suspected cases with COVID-19 into the study. The training cohort consisted of 30 confirmed and 78 suspected cases, whereas the validation cohort consisted of 30 confirmed and 74 suspected cases. Four clinical variables - epidemiological history (E), body temperature (T), leukocytes count (L), and chest computed tomography (C) - were collected to construct a preliminary prediction model (model A). By integerizing coefficients of model A, a clinical prediction model (model B) was constructed. Finally, the scores of each variable in model B were summed up to build the ETLC score. RESULTS The preliminary prediction model A was Logit (YA)=2.657X1+1.153X2+2.125X3+2.828X4-10.771, while the model B was Logit (YB)=2.5X1+1X2+2X3+3X4-10. No significant difference was found between the area under the curve (AUC) of model A (0.920, 95% CI: 0.875-0.953) and model B (0.919, 95% CI: 0.874-0.952) (Z=0.035, P=0.972). When ETLC score was more than or equal to 9.5, the sensitivity and specificity for COVID-19 was 76.7% (46/60) and 90.1% (137/152), respectively, and the positive and negative predictive values were 75.4% (46/61) and 90.7% (137/151), respectively. CONCLUSIONS The ETLC score is helpful for efficiently identifying patients with suspected COVID-19.