Stable and durable antibody responses in SARS-recovered donors vaccinated with inactivated SARS-CoV-2 vaccine.

Whether the immune imprinting caused by severe acute respiratory syndrome coronavirus (SARS-CoV) affects the efficiency of SARS-CoV-2 vaccination has attracted global concern. Little is known about the dynamic changes of antibody response in SARS convalescents inoculated with three doses of inactivated SARS-CoV-2 vaccine although lack of cross-neutralizing antibody response to SARS-CoV-2 in SARS survivors has been reported. We longitudinally examined the neutralizing antibodies (nAbs) against SARS-CoV and SARS-CoV-2 as well as spikes binding IgA, IgG, IgM, IgG1, and IgG3 antibodies in 9 SARS-recovered donors and 21 SARS-naïve donors. Stably higher nAbs and spike antigens-specific IgA, IgG antibodies against SARS-CoV-2 were observed in SARS-recovered donors compared with SARS-naïve donors during the period with two doses of BBIBP-CorV vaccination. However, the third-dose BBIBP-CorV stimulated a sharply and shortly higher increase of nAbs in SARS-naïve donors than in SARS-recovered donors. It is worth noting that, regardless of prior SARS infection, the Omicron subvariants were found to subvert immune responses. Moreover, certain subvariants such as BA.2, BA.2.75, or BA.5 exhibited a high degree of immune evasion in SARS survivors. Interestingly, BBIBP-CorV recalled higher nAbs against SARS-CoV compared with SARS-CoV-2 in SARS-recovered donors. In SARS survivors, a single dose of inactivated SARS-CoV-2 vaccine provoked immune imprinting for the SARS antigen, providing protection against wild-type SARS-CoV-2, and the earlier variants of concern (VOCs) including Alpha, Beta, Gamma, and Delta but not against Omicron subvariants. As such, it is important to evaluate the type and dosage of SARS-CoV-2 vaccine for SARS survivors.

An early novel prognostic model for predicting 80-day survival of patients with COVID-19.

The outbreak of the novel coronavirus disease 2019 (COVID-19) has had an unprecedented impact worldwide, and it is of great significance to predict the prognosis of patients for guiding clinical management. This study aimed to construct a nomogram to predict the prognosis of COVID-19 patients. Clinical records and laboratory results were retrospectively reviewed for 331 patients with laboratory-confirmed COVID-19 from Huangshi Hospital of Traditional Chinese Medicine (TCM) (Infectious Disease Hospital) and Third Affiliated Hospital of Sun Yat-sen University. All COVID-19 patients were followed up for 80 days, and the primary outcome was defined as patient death. Cases were randomly divided into training (n=199) and validation (n=132) groups. Based on baseline data, we used statistically significant prognostic factors to construct a nomogram and assessed its performance. The patients were divided into Death (n=23) and Survival (n=308) groups. Analysis of clinical characteristics showed that these patients presented with fever (n=271, 81.9%), diarrhea (n=20, 6.0%) and had comorbidities (n=89, 26.9.0%). Multivariate Cox regression analysis showed that age, UREA and LDH were independent risk factors for predicting 80-day survival of COVID-19 patients. We constructed a qualitative nomogram with high C-indexes (0.933 and 0.894 in the training and validation groups, respectively). The calibration curve for 80-day survival showed optimal agreement between the predicted and actual outcomes. Decision curve analysis revealed the high clinical net benefit of the nomogram. Overall, our nomogram could effectively predict the 80-day survival of COVID-19 patients and hence assist in providing optimal treatment and decreasing mortality rates.