RESUMEN
BACKGROUND: Because there is no reliable risk stratification tool for severe coronavirus disease 2019 (COVID-19) patients at admission, we aimed to construct an effective model for early identification of cases at high risk of progression to severe COVID-19. METHODS: In this retrospective multicenter study, 372 hospitalized patients with nonsevere COVID-19 were followed for > 15 days after admission. Patients who deteriorated to severe or critical COVID-19 and those who maintained a nonsevere state were assigned to the severe and nonsevere groups, respectively. Based on baseline data of the 2 groups, we constructed a risk prediction nomogram for severe COVID-19 and evaluated its performance. RESULTS: The training cohort consisted of 189 patients, and the 2 independent validation cohorts consisted of 165 and 18 patients. Among all cases, 72 (19.4%) patients developed severe COVID-19. Older age; higher serum lactate dehydrogenase, C-reactive protein, coefficient of variation of red blood cell distribution width, blood urea nitrogen, and direct bilirubin; and lower albumin were associated with severe COVID-19. We generated the nomogram for early identifying severe COVID-19 in the training cohort (area under the curve [AUC], 0.912 [95% confidence interval {CI}, .846-.978]; sensitivity 85.7%, specificity 87.6%) and the validation cohort (AUC, 0.853 [95% CI, .790-.916]; sensitivity 77.5%, specificity 78.4%). The calibration curve for probability of severe COVID-19 showed optimal agreement between prediction by nomogram and actual observation. Decision curve and clinical impact curve analyses indicated that nomogram conferred high clinical net benefit. CONCLUSIONS: Our nomogram could help clinicians with early identification of patients who will progress to severe COVID-19, which will enable better centralized management and early treatment of severe disease.
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Infecciones por Coronavirus/diagnóstico , Infecciones por Coronavirus/patología , Neumonía Viral/diagnóstico , Neumonía Viral/patología , Adulto , Área Bajo la Curva , Betacoronavirus/patogenicidad , COVID-19 , China , Infecciones por Coronavirus/virología , Progresión de la Enfermedad , Femenino , Humanos , Masculino , Persona de Mediana Edad , Nomogramas , Pandemias , Neumonía Viral/virología , Pronóstico , Estudios Retrospectivos , Medición de Riesgo/métodos , Factores de Riesgo , SARS-CoV-2RESUMEN
Coronavirus disease 2019 (COVID-19) is a respiratory disorder caused by the highly contagious severe acute respiratory syndrome coronavirus 2. The immunopathological characteristics of patients with COVID-19, either systemic or local, have not been thoroughly studied. In the present study, we analysed both the changes in the number of various immune cell types as well as cytokines important for immune reactions and inflammation. Our data indicate that patients with severe COVID-19 exhibited an overall decline of lymphocytes including CD4+ and CD8+ T cells, B cells and natural killer cells. The number of immunosuppressive regulatory T cells was moderately increased in patients with mild COVID-19. Interleukin-6 (IL-6), IL-10 and C-reactive protein were remarkably up-regulated in patients with severe COVID-19. In conclusion, our study shows that the comprehensive decrease of lymphocytes, and the elevation of IL-6, IL-10 and C-reactive protein are reliable indicators of severe COVID-19.
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Infecciones por Coronavirus/inmunología , Infecciones por Coronavirus/patología , Neumonía Viral/inmunología , Neumonía Viral/patología , Anciano , Linfocitos B/inmunología , Linfocitos B/patología , Betacoronavirus/fisiología , COVID-19 , China/epidemiología , Infecciones por Coronavirus/epidemiología , Infecciones por Coronavirus/fisiopatología , Femenino , Humanos , Células Asesinas Naturales/inmunología , Células Asesinas Naturales/patología , Linfocitos/patología , Masculino , Pandemias , Neumonía Viral/epidemiología , Neumonía Viral/fisiopatología , SARS-CoV-2 , Índice de Severidad de la Enfermedad , Linfocitos T/inmunología , Linfocitos T/patología , Linfocitos T Reguladores/patologíaRESUMEN
The SARS-CoV-2 Delta variant has spread rapidly worldwide. To provide data on its virological profile, we here report the first local transmission of Delta in mainland China. All 167 infections could be traced back to the first index case. Daily sequential PCR testing of quarantined individuals indicated that the viral loads of Delta infections, when they first become PCR-positive, were on average ~1000 times greater compared to lineage A/B infections during the first epidemic wave in China in early 2020, suggesting potentially faster viral replication and greater infectiousness of Delta during early infection. The estimated transmission bottleneck size of the Delta variant was generally narrow, with 1-3 virions in 29 donor-recipient transmission pairs. However, the transmission of minor iSNVs resulted in at least 3 of the 34 substitutions that were identified in the outbreak, highlighting the contribution of intra-host variants to population-level viral diversity during rapid spread.
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COVID-19/transmisión , Trazado de Contacto/métodos , Brotes de Enfermedades/prevención & control , SARS-CoV-2/aislamiento & purificación , Animales , COVID-19/epidemiología , COVID-19/virología , Chlorocebus aethiops , Humanos , RNA-Seq/métodos , Reacción en Cadena de la Polimerasa de Transcriptasa Inversa , SARS-CoV-2/genética , SARS-CoV-2/fisiología , Factores de Tiempo , Células Vero , Carga Viral/genética , Carga Viral/fisiología , Replicación Viral/genética , Replicación Viral/fisiología , Esparcimiento de Virus/genética , Esparcimiento de Virus/fisiologíaRESUMEN
Low-density lipoprotein cholesterol (LDL-C) is a well-known risk factor for coronary heart disease but protects against infection and sepsis. We aimed to disclose the exact association between LDL-C and severe 2019 novel coronavirus disease (COVID-19). Baseline data were retrospectively collected for 601 non-severe COVID-19 patients from two centers in Guangzhou and one center in Shenzhen, and patients on admission were medically observed for at least 15 days to determine the final outcome, including the non-severe group (n = 460) and the severe group (severe and critical cases) (n = 141). Among 601 cases, 76 (12.65%) received lipid-lowering therapy; the proportion of patients taking lipid-lowering drugs in the severe group was higher than that in the non-severe group (22.7 vs. 9.6%). We found a U-shaped association between LDL-C level and risk of severe COVID-19 using restricted cubic splines. Using univariate logistic regression analysis, odds ratios for severe COVID-19 for patients with LDL-C ≤1.6 mmol/L (61.9 mg/dL) and above 3.4 mmol/L (131.4 mg/dL) were 2.29 (95% confidence interval 1.12-4.68; p = 0.023) and 2.02 (1.04-3.94; p = 0.039), respectively, compared to those with LDL-C of 2.81-3.40 mmol/L (108.6-131.4 mg/dL); following multifactorial adjustment, odds ratios were 2.61 (1.07-6.37; p = 0.035) and 2.36 (1.09-5.14; p = 0.030). Similar results were yielded using 0.3 and 0.5 mmol/L categories of LDL-C and sensitivity analyses. Both low and high LDL-C levels were significantly associated with higher risk of severe COVID-19. Although our findings do not necessarily imply causality, they suggest that clinicians should pay more attention to lipid-lowering therapy in COVID-19 patients to improve clinical prognosis.
RESUMEN
BACKGROUND: We launched a retrospective analysis of SARS-CoV-2 antibodies in 192 patients with COVID-19, aiming to depict the kinetic profile of SARS-CoV-2 antibodies and explore the factors related to SARS-CoV-2 antibody expression. METHODS: Data on 192 confirmed patients with COVID-19 between January and February 2020 was collected from the designated hospital that received patients with COVID-19 in Guangzhou, China. Moreover, a cohort of 130 suspected patients with COVID-19 and 209 healthy people were also enrolled in this study. IgM and IgG antibodies to SARS-CoV-2 were detected by the chemiluminescence immunoassay kits in different groups. RESULTS: A total of 192 COVID-19 cases were analyzed, of which had 81.8% anti-SARS-CoV-2 IgM detected and 93.2% anti-SARS-CoV-2 IgG detected, respectively, at the time of sampling. The kinetics of anti-SARS-CoV-2 IgM and IgG showed that, the confirmed cases had anti-SARS-CoV-2 IgM seroconversion occurred 5-10 days after the onset of the symptoms, and then IgM rose rapidly to reach a peak within around 2-3 weeks, maintaining at its peak for 1 week before its decline. While they had anti-SARS-CoV-2 IgG seroconversion simultaneously or sequentially with IgM, reaching its peak within around 3 to 4 weeks and began to decline after the fifth week. Besides, correlation analysis showed that in patients with COVID-19 the level of IgM was related to gender and disease severity (P < 0.01), and the level of IgG was related to age and disease severity (P < 0.001). The univariate analysis of relevant factors indicated that the level of IgG had a weak correlation with age (r = 0.374, P < 0.01). The level of IgM in male patients was higher than that in female patients (P < 0.001). The expression level of anti-SARS-CoV-2 IgM and IgG were positively correlated with the severity of COVID-19 and the duration of the virus in the patients. CONCLUSION: The findings of this study show that anti-SARS-CoV-2 IgM and IgG can be important assisting COVID-19 diagnosis, especially in the early phase of infection. Furthermore, antibody expression in patients with COVID-19 is also correlated with disease severity, age, gender, and virus clearance or continuous replication.